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Operations and Supply Chain Management (OSCM) is the design, operation, and improvement of the systems that create and deliver the firm’s primary products and services. OCSM is concerned with the management of the entire system that produces a product or delivers a service.
For every product/service a supply network can be made. Think of a supply network as a pipeline through which material and information flow.
Success in today’s global markets requires a business strategy that matches the preferences of customers with the realities imposed by complex supply networks.
Operations refers to manufacturing and service processes that are used to transform the resources employed by a firm into products desired by customers.
Supply Chain encompasses all activities and information associated with the flow and transformation of goods and services from the raw materials stage through to the end-user.
A process is made up of one or multiple activities that transform inputs into outputs. Operations and Supply Chain processes can be categorized as follows:
Plan: Involves the processes that are needed to operate an existing supply chain strategically;
Source: The selection of suppliers that will deliver the goods and services needed to create the firm’s product;
Make: Where the product is produced or the service is provided;
Deliver: Also logistics processes. Delivering products to warehouses and customers, contact with customers and information systems need to be managed;
Return: Involves the processes for receiving worn-out, defective, and excess products back from customers and processes for supporting customers who have problems with the delivered product.
The are five essential differences between goods and services:
Intangibility: A service cannot be weighed or measured. This means that services innovations cannot be patented and customers cannot try the service beforehand;
Interaction with the customer: To be a service, the process requires a degree of interaction with the customer;
Heterogeneity: Services vary day to day between the customer and the servers, whereas variation in producing goods can be almost zero;
Perishability and time dependency: services can’t be stored;
Specification of a services can be defined as a package of features that affect the five senses, existing of supporting facility like location and layout, facilitating goods like variety, consistency and quantity, explicit services like training of the personnel and availability to the service, and implicit service like attitude of the personnel, waiting time and privacy.
Almost every product offered is a combination of goods and services. The Goods-Services Continuum demonstrates the focus of firms and spans firms that only produce products to firms that provide services only (pure products – core products – core services – pure services).
Product-service bundling refers to when a firm builds service activities into its product offerings to create additional value for the customer.
Efficiency is doing something at the lowest possible cost.
Effectiveness is doing the things that will create most value for the customer.
Value is the attractiveness of a product relative to its cost.
An interesting relation between OCSM functions and profit is the direct impact of a cost reduction in one of these functions on the profit margin.
There are two ratios that relate to the productivity of labour employed by the firm: net income per employee and revenue (or sales) per employee.
The receivables turnover ratio measures the efficiency of a company in collecting its sales on credit:
Receivable turnover = annual credit sales / average account receivable
The lower the ratio, the longer receivables are being held and the higher the risk of them not being collected.
Another ratio is the inventory turnover, which measures the average number of times inventory is sold and replaced during the fiscal year. This ratio measures how efficient the company turns its inventory into sales.
Inventory turnover = costs of goods sold / average inventory value
The asset turnover ratio is the amount of sales generated for every dollar’s worth of assets. This measures how efficient a firm is using its assets in generating sales revenue.
Asset turnover = revenue (or sales) / total assets
The historical development of OCSM:
The Manufacturing Strategy Paradigm was developed in the late 1970s and early 1980s by researchers at the Harvard Business School;
Lean manufacturing, Just-In-Time and Total Quality Management became popular by the Japanese in the 1980s;
Standardized service quality and productivity became popular by McDonalds;
Total Quality Management and Quality Certification (e.g., ISO 9000) developed in the late 1980s and 1990s by Deming, Juran and Crosby;
Business Process Reengineering (revolutionairy instead of evolutionairy changes) was necessary in the economic recession in the 1990s and was described by Michael Hammer. Taylor (scientific management) and Frank and Lilian Gilbreth were also important in this field;
Six Sigma Quality tools were extended in the 1990s and can be used in many different organisations;
Supply Chain Management is a total system approach to managing the flow of information, materials and services from material suppliers through factories and warehouses to the end customer. Mass customization is the ability to produce a unique product exactly to a particular customer’s requirements;
Electronic Commerce became popular in the late 1990s because of the rise of the Internet and the use of it as an essential element of business activity;
Service science was a direct response to the growth of services;
Business analytics is the use of current business data to solve business problems using mathematical analysis.
As operations and supply management is a dynamic field, a global enterprise challenges nowadays different issues:
Coordination between mutually supportive but separate organizations (existence of contract manufacturers that are specialized in performing focused manufacturing activities);
Optimization of global supplier, production, and distribution networks;
Management of customer touch points (the recognition that making resource utilization decisions must capture the implicit costs of lost customers as well as the direct costs of staffing);
Raising seniormanagement awareness of operations as a significant competitive weapon.
Strategy describes how a firm creates and sustains value for its current shareholders. By adding sustainability, future generations are taken into account.
Shareholders own one or multiple shares in the company.
Stakeholders are indirectly and directly influenced by the activities of the firm.
Firms focus more and more on stakeholders.
The Triple Bottom Line captures an expanded spectrum of values by evaluating a firm against the following criteria:
Social Responsibility: Pertains to fair and beneficial business practices toward labour, the community, and the region in which a firm conducts its business;
Economic Prosperity: The firm’s obligation to compensate shareholders who provide capital via competitive returns on investment;
Environmental Stewardship: The firm’s impact on the environment and society.
Operations and Supply Chain Strategy is the setting of broad policies and plans for using the firm’s resources optimally. This must be integrated with corporate strategy. Operations effectiveness is performing activities in a manner that best implements strategic priorities at minimum cost.
If you want to integrate a Operations and Supply Chain Strategy with the operational capabilities of a firm, you must make decisions about the design of the process and infrastructure needed to support these processes.
Process design is selecting the right technology, arranging the process over time, determining the role of inventory in the process and determining the location of the process.
Infrastructure decisions involve the logic associated with the planning and control systems, quality assurance and control approaches, work payment structure and organization of the operations and supply functions.
Operations capabilities is a portfolio best suited to adapting to the changing product and/or service needs of a firm’s customers.
There are seven major competitive dimensions to forming the competitive position of a firm:
Cost or price: The choice to either make the product or deliver the service cheap;
Quality: The firm’s definition of how the product or service is to be made;
Delivery speed: The firm’s ability to make the product or deliver the service quickly;
Delivery reliability: The firm’s ability to deliver the product when promised;
Coping with changes in demand: The firm’s ability to respond to the change in demand;
Flexibility and New-Product introduction speed: The firm’s ability to be flexible in order to offer a wide variety of production to its customers in a given time;
Other product-specific criteria relate to specific products or situations: Special services can increase sales of manufactured products such as technical liaison and support, meeting a launch date, supplier after-sale support, environmental impact and other dimensions (e.g. color, size, weight).
Companies cannot be good in everything. A trade-off occurs when activities are incompatible so that more of one thing necessitates less of another (e.g. high quality is viewed as a trade-off to low cost).
Straddling occurs when a company seeks to match the benefits of a successful position while maintaining its existing position.
An order winner is a specific marketing-orientated dimension that clearly differentiates a product from competing products. This dimension can be price, quality or reliability.
An order qualifier is a dimension used to screen a product or service as a candidate for purchase, for example the battery life of a new computer.
All activities that make up a firm’s operation relate to one another. Activity-System Maps are diagrams that show how a company’s strategy is executed by a set of supporting activities.
The management of risk is crucial for OCSM. Supply chain risk is the likelihood of a disruption that would impact the ability of a company to continuously supply products or services. Supply chain disruptions are unplanned and unanticipated events that disrupt the normal flow of goods and materials within a supply chain.
We can categorize risk along two dimensions:
Supply chain coordination risks that are associated with the day-to-day management of the supply chain;
Disruption risks which are caused by natural or manmade disasters, such as earthquakes, hurricanes and terrorism.
These are the three steps in the risk management process that can be applied to situations where disruptions are possible:
Identify the sources of potential disruptions;
Assess the potential impact of the risk;
Develop plans to mitigate the risk.
Productivity is a measure of how well resources are used. The formula:
Productivity = outputs / inputs
To increase productivity, this ratio must be as large as practical. However, productivity is a relative measure and should always be compared to something else. This could be competitors or the process over time.
Forecasting is essential for every organisation and is the basis of corporate long-rung planning. Strategic forecasts are medium and long-term forecasts that are used for decisions related to strategy and aggregate demand. Tactical forecasts are short-term forecasts used for making day-to-day decisions related to meeting demand.
A perfect forecast is virtually impossible. Too many factors in the business environment cannot be predicted with certainty. Therefore, rather than search for the perfect forecast, it is far more important to establish the practice of continual review of forecasts and to learn to live with inaccurate forecasts.
There are four basic types of forecasting: qualitative, time series analysis, causal relationships and simulation. Qualitative techniques are subjective and based on estimates and opinions.
Time series analysis (the focus of this chapter) is a forecast in which past demand data is used to predict future demand.
For causal forecasting the linear regression technique is used, which assumes that demand is related to some underlying factor(s) in the environment.
Simulation models allow the forecaster to run through a range of assumptions about the condition of the forecast.
Demand for products/services can be broken down into six components in most cases: average demand for the period, a trend, seasonal elements, cyclical elements, random variation and autocorrelation.
Cyclical influence on demand may come from occurrences as political elections, war or economic conditions. Random variation is caused by chance events. Autocorrelation denotes the persistence of occurrence. Trend lines are the usual starting point in developing a forecast.
Time series forecasting models try to predict the future based on past data. There are different time series models, which will be described in the following paragraphs.
Short-term refers to under three months, medium term to three months to two years and long-term to greater than two years.
Which model a company uses depends on the time horizon to forecast, data availability, the required accuracy, the size of the forecasting budget and the availability of qualified personnel. Other issues as the firm’s degree of flexibility are also important. The consequence of a bad forecast also needs to be taken into consideration.
When the demand for a product is constant and there are no seasonal characteristics, the moving average can be used: a forecast based on average past demand. Selecting the period length should be dependent on how the forecast is going to be used.
Ft = At-1 + At-2 + At-3 + … + At-n / n
Where
Ft = Forecast for the coming period
n = Number of periods to be averaged
At-1 , … , At-n = Actual occurrences in the past period/two periods ago/etc.
Each time a new forecast is made, the oldest period is discarded in the average and the newest period included.
The main disadvantage in calculating a moving average is that all individual elements must be carried as data because a new forecast period involves adding new data and removing earlier data.
A weighted moving average allows any weights to be placed on each element, provided that the sum of all weights equals 1. By forecasting this way, more recent data is given more significance than older data.
Ft = w1At-1 + w2At-2 + … + wnAt-n
Where
w1, …, wn = Weight to be given to the actual occurrence for the period t-1, …, t-n.
n = Total number of prior periods in the forecast
At-1 , … , At-n = Actual occurrences in the past period/two periods ago/etc.
The sum of all the weights must equal 1.
The major drawback of using these two methods is the need to continually carry a large amount of historical data. Also, it is more inconvenient and costly to use than the exponential smoothing method.
Exponential smoothing uses weights for past data that decrease exponentially (1 – α) for each past period. This is the most used technique for forecasting.
Exponential smoothing techniques have become well accepted for six major reasons:
Exponential models are surprisingly accurate;
Formulating an exponential model is relatively easy;
The user can understand how the model works;
Little computation is required to use the model;
Computer storage requirements are small because of the limited use of historical data;
Tests for accuracy as to how well the model is performing are easy to compute.
Three pieces of data are needed to forecast the future:
The most recent forecast;
The actual demand that occurred for the forecast period;
A smoothing constant alpha (α): the parameter in the exponential smoothing equation that controls the speed of reaction to differences between forecasts and actual demand. This is determined by both the nature of the product and the manager’s sense of what constitues a good response rate. The more rapid the growth, the higher the reaction rate should be.
Ft = Ft-1 + α(At-1 – Ft-1)
Where
Ft = The exponentially smoothed forecast for period t
Ft-1 = The exponentially smoothed forecast made for the prior period
At-1 = The actual demand in the prior period
α = The desired response rate, or smoothing constant
This equation states that the new forecast is equal to the old forecast plus a portion of the error (the difference between the previous forecast and what actually occurred).
Adaptive forecasting is adjusting the value of alpha or adding a trend factor to track actual demand more closely.
An upward or downward trend in data collected over a sequence of time periods causes the exponential forecast to always lag behind (be above or below) the actual occurrence. By adding another constant, the smoothing constant delta (δ), this trend can be corrected somewhat. Both alpha and delta reduce the impact of the error that occurs between the actual and the forecast.
Formula 4.1: Ft = FITt-1 + α(At-1 – FITt-1)
Formula 4.2: Tt = Tt-1 + δ(Ft – FITt-1)
Formula 4.3: FITt = Ft + Tt
Where
Ft = The exponentially smoothed forecast that does not include trend for period t
Tt = The exponentially smoothed trend for period t
FITt = The forecast including trend for period t or the prior period
FITt-1 = The forecast including trend for the prior period
At-1 = The actual demand for the prior period
α = Smoothing constant (alpha)
δ = Smoothing constant (delta)
These equations need to be taken step for step to make an exponential forecast that includes trend.
The smoothing constants need to be given a value between 0 and 1. Typically, values are used for alpha and delta in the range of .1 to .3. The values depend on how much random variation there is in demand and how steady the trend factor is.
Regression is a functional relationship between two or more correlated variables. It is used to predict one variable, given the other. The data should be plotted first to see if they appear linear.
Linear regression refers to a special class of regression where the relationship between variables forms a straight line. Form of the formula: Y = a + bt, where Y is the value of the dependent variable that we are solving for, a is the Y intercept, b is the slope and t is an index for the time period.
Linear regression is useful for long-term forecasting of major occurrences and aggregate planning. The biggest drawback of using linear regression forecasting is that past data and future projections are assumed to fall in about a straight line. However, it can still be used for both time series forecasting and causal relationship forecasting.
The linear least squares method tries to fit the line to the data that minimizes the sum of the squares of the vertical distance between each data point and its corresponding point on the line.
The standard error of estimate shows how well the line fits the data.
By the least squares method the formulas for a and b in the formula Yt = a +bt are:
b = (∑ty – (n*ta) * ya)/(∑t2 – nt2)
a = ya – (b*ta)
Where
a = Y intercept
b = Slope of the line
ya = Average of all ys
ta = Average of all ts
t = T value at each data point
y = Y value at each data point
n = Number of data points
Yt = Value of the dependent variable computed with the regression equation
Standard error of estimate
Syt = the root of (∑1..n (yi-Yi)(yi-Yi))/(n-2)
A time series is chronologically ordered data that may contain one or multiple components of demand: trend, seasonal, cyclical, autocorrelation and random.
Decomposition of a time series means identifying and separating the time series data into these components. The trend and seasonal component are relatively easy to identify, while cycles, autocorrelation and random components are much harder to identify.
There are two types of seasonal variation:
Additive seasonal variation: assumes that the seasonal amount is a constant, no matter what the trend or average amount is.
Forecast including trend and seasonal = Trend + Seasonal
Multiplicative seasonal variation: the trend is multiplied by the seasonal factors.
Forecasting including trend and seasonal = Trend x Seasonal factor
A seasonal factor is the amount of correction needed in a time series to adjust for the season of the year.
Using least squares regression can also do decomposition. The process is as follow:
Decompose the time series into its components:
Find seasonal component;
Deseasonalize the demand;
Find trend component.
Forecast future values of each component:
Project trend component into the future;
Multiply trend component by seasonal component.
The forecast error is the difference between actual demand and what was forecast. These errors are called residuals.
There are two factors that need to be discussed:
Sources of error: Errors can come from a variety of sources. Errors can be classified as bias or random. Bias errors occur when a consistent mistake is made, for example by using the wrong variables. Random errors cannot be explained by the forecast model being used.
Measurement of error: There are terms to describe the degree of error: standard error, mean squared error (or variance) and mean absolute deviation. De mean absolute deviation (MAD) is the average of the absolute value of the actual forecast error. It measures the dispersion of some observed value from some expected value.
MAD = (∑1...n |At-Ft|)/n
Where
t = Period number
At = Actual demand for the period t
Ft = Forecast demand for the period t
n = Total number of periods
|| = The absolute value
When the errors that occur in the forecast are normally distributed (the usual case), the MAD relates to the standard deviation as:
1 standard deviation = x MAD, or approximately 1.25 MAD
1 MAD = approximately 0.8 standard deviation
Another measure of error is the mean absolute percent error (MAPE). This measures the average error as a percentage of average demand.
MAPE = MAD / Average demand
A tracking signal (TS) is a measurement that indicates whether the forecast average is keeping pace with any genuine upward or downward changes in demand. This is used to detect forecast bias.
TS = RSFE / MAD
Where
RSFE = the running sum of forecast errors, considering the nature of the error
MAD = the average of all the forecast errors, the average of the absolute deviations
Causal relationship forecasting involves using independent variables other than time to predict future demand.
Multiple regression analysis is another forecasting method, in which a number of variables are considered, together with the effects of each on the item of interest.
S = A + Bm(M) + Bh(H) + Bi(I) + Bt(T)
Where
S = Gross sales for year
B = Base sales, a starting point from which other factors have influence
M/H/I = Other factors, such as marriages during the year/housing starts/etc.
T = Time trend (first year = 1, second year =2, etc.)
Next to these quantitative methods of forecasting, there are also qualitative forecasting techniques. The knowledge of experts is important, while it requires much judgement. Examples are market research, panel consensus, historical analogy and the Delphi method.
Collaborative Planning, Forecasting and Replenishment (CPFR) is a Web-based tool used to coordinate forecasting, production and purchasing in a firm’s supply chain.
Capacity Management in Operations is the ability to hold, receive, store or accommodate a number of customers in a system. Capacity is the amount of resource inputs available relative to output requirements over a particular period of time. However, it does not imply the duration of its sustainability. When looking at capacity, Operations managers look at inputs and outputs. Also, Operations management focus on the time dimension of capacity.
You can distinguish capacity planning in the following three time durations:
Long range: Longer than one year;
Intermediate range: Monthly or quarterly plans for the next 6 to 18 months;
Short range: Less than one month.
Strategic capacity planning is finding the overall capacity level of capacity-intensive resources to best support the firm’s long-term strategy.
Capacity is the output that a system is capable of achieving to deliver over a period of time.
The best operating level is a level of capacity for which the process was designed and thus is the volume of output the best operation level at the level where average unit cost is minimized. The determination of the minimum is difficult as it includes a complex trade-off between the allocation of fixed overhead costs and other costs.
You can calculate the capacity utilization rate to reveal how close a firm is to its best operation level:
Capacity utilization rate = Capacity used / Best operating level
By economies of scale, there is a cost advantage for companies as the volume increases because the average cost per unit of output drops. At some point, the size of a plant becomes too large and diseconomies of scale become a problem.
A focused factory means that a production facility works best when it focuses on a fairly limited set of production objectives.
This concept is focused on the capacity by operationalizing the mechanism by plant within a plant (PWP). This is an area in a larger facility that is dedicated to a specific production objective. A focused factory may have several PWPs.
Capacity flexibility is the ability to rapidly increase or decrease production levels, or to shift production capacity quickly from one to another. Flexibility can be created by:
Flexible plants: The ultimate in plant flexibility is the zero-changeover time plant. Such a plant can adapt to change by the use of movable equipment, knockdown walls, and easily accessible utilities;
Flexible processes: Flexible manufacturing processes permit low-cost switching from one product to another and enable economies of scope (multiple products can be produced at lower cost in combination than they can be seperately);
Flexible workers: Flexible workers have multiple skills and the ability to switch easily from one kind of task to another.
By changing the capacity, it is important to maintain system balance, keep track of frequency of capacity additions or reductions, and the use of external capacity.
In determining capacity requirements, the demands for individual product lines, plant capabilities and allocation of production need to be addressed. Typically this is done according to the following steps:
Use forecasting techniques to predict sales for individual products within each product line;
Calculate equipment and labor requirements to meet product line forecasts;
Project labor and equipment availabilities over the planning horizon.
Often the firm decides on capacity cushion: the amount of capacity in excess of expected demand. It is the reserve capacity that handles sudden increases in demand or temporary losses of production capacity.
To lie out the steps of a capacity problem, a decision tree can be used. A decision tree is a schematic model of the sequence of steps in a problem and the conditions and consequences of each step. To solve the decision tree, you need to start from the end of the tree.
Capacity planning in services knows several important differences with capacity planning in products:
Time: Services cannot be stored for later use.
Location: The service setting must be at the place where the customer needs it.
Volatility of demand: The volatitility of demand for a service is much higher than the volatility of demand for a product. This is because of (1) services cannot be stored, so inventory cannot smooth the demand; (2) customers interact directly with the production system of a service, and because they differ from each other, there will be more variability; (3) demand is directly affected by consumer behaviour, and this can be influenced by a lot of different things.
Planning capacity levels for services must consider the day-to-day relationship between service utilization and service quality. The best operating point is near 70 percent of the maximum capacity.
A project is a series of related jobs, usually directed toward some major output and requiring a significant period of time to perform. Projects can be categorized in four major areas: product change, process change, research and development, and alliance and partnership.
Project management is planning, directing and controlling resources (people, equipment, material) to meet the technical, cost and time constraints of a project.
There are three types of projects:
Pure projects: A structure for organizing a project where a self-contained team works full time on the project.
Functional project: A structure where team members are assigned from the functional units of the organization. The team members remain a part of their functional units and typically are not dedicated to the project.
Matrix project: A structure that blends the functional and pure project structures. Each project uses people from different functional areas. A dedicated project manager decides what tasks need to be performed and when, but the functional manager control which people to use.
A project starts out as a statement of work (SOW): a description of the objectives to be achieved, with a brief statement of the work to be done and a proposed schedule specifying the start and completion dates.
A task is a further subdivision of the project. A subtask can be used, if needed, to further subdivide the project into more meaningful pieces.
A work package is a group of activities combined to be assignable to a single organizational unit. A project milestone is a specific event in a project.
The work breakdown structure (WBS) defines the hierarchy of project tasks, subtasks and work packages. Completion of one or multiple work packages results in the completion of a subtask; completion of one or multiple subtasks results in the completion of a task; and, finally, the completion of all tasks is required to complete the project.
Activities are pieces of work within a project that consume time. The completion of all the activities of a project marks the end of the project. A Gannt chart (also bar chart) shows in a graphic manner the amount of time involved and the sequence in which activities can be performed.
Earned Value Management (EVM) is a technique that combines measures of scope, schedule and cost for evaluating project progress. Essential features of an EVM implementation are:
A project plan that identifies the activities to be accomplished;
A valuation of each activity. If a project generates revenue, its called the Planned Value (PV) of the activity. If a project generates costs, its called the Budgeted Cost of Work Scheduled (BCWS);
Predefined “earning or costing rules” (also “metrics”) to quantify the accomplishment of work, called Earned Value (EV) or Budgeted Cost of Work Performed (BCWP).
You can evaluate a project without EVM. This occurs when a project is evaluated based on costs.
A critical path of activities is the sequence of activities in a project that forms the longest chain in terms of their time to complete. If one of the activities in the critical path is delayed, then the entire project is delayed. It is possible that there are multiple paths of the same length through the network. In this case, there are multiple critical paths.
The critical path method (CPM) can be used for scheduling a project. The following steps need to be taken:
Identify each activity to be done in the project and estimate how long it will take to complete each activity.
Determine the required sequence of activities and construct a network reflecting the precedence relationships. The easiest way to do this is by identifying immediate predecessors. These are activities that need to be completed immediately before another activity.
Determine the critical path.
Determine the early start/finish and late sart/finish schedule. For some activities, there can be slack time: the time that an activity can be delayed, without delaying the entire project. It is also the difference between the late and early start times of an activity.
An early start schedule is a project schedule that lists all activities by their early start times. A late start schedule is a project schedule that lists all activities by their late start times. This schedule may create saving by postponing purchases of material and other costs associated with the project.
If a single estimate of the time required to complete an activity is not reliable, the best procedure is to use three time estimates.
- Identify each activity to be done in the project.
- Determine the sequence of activities and construct a network reflecting the precedence relationships.
- Calculate the expected time (ET) for each activity.
ET = (a+4m+b)/6
Where
ET = The expected time
a = The optimistic time
m = The most likely time
b = The pessimistic time
- Determine the critical path.
- Calculate the variances (σ2) of the activity times.
- Determine the probability of completing the project on a given date. The mechanics of deriving this probability are as follows:
- Sum the variance values associated with each activity on the critical path.
- Substitute this figure, along with the project due date and the project expected completion time, into the Z transformation formula.
Z = (D-T)/(the root of ∑σ2)
Where
D = Desired completion date for the project
T = Expected completion date for the project
∑ σ2 = Sum of variances along the critical path
Time-cost models are an extension of the critical path models that consider the trade-off between the time required to complete an activity and the cost of that activity. This is often referred as “crashing” the project. The basic assumption is that there is a relationship between activity completion time and the cost of a project. Crashing means the time to complete the project is compressed or shortened.
Costs that are associated with expediting activities are activity direct costs and add to the project direct cost. Costs that are associated with sustaining the project are project indirect costs: overhead, facilities and resource opportunity costs. Between these two costs, there is a trade-off and therefore also a optimum point.
The procedure for project crashing consists of the following five steps:
Prepare a CPM-type network diagram. For each activity, this diagram should list:
Normal cost (NC): the lowest expected activity costs;
Normal time (NT): the time associated with each normal cost;
Crash time (CT): the shortest possible activity time;
Crash cost (CC): the cost associated with each crash time.
Determine the cost per unit of time (days) to expedite each activity.
Slope = (CC – NC) / (NT – CT)
Compute the critical path.
Shorten the critical path at the least cost.
Plot project direct, indirect and total-cost curves and find the minimum-cost schedule.
Nowadays there are over 100 companies offering project management software. Two of the leading companies are Microsoft (Microsoft Project) and Primavera (Primavera Project Planner).
What is required to process a product can be divided into three simple steps: (1) sourcing the parts needed, (2) making the item and (3) sending the item to the customer.
Depending on the wishes of the customer, the lead time of products differs: the time needed to respond to a customer order.
The different products can be classified in different groups, according to the customer order decoupling point (CODP). The COOP determines where inventory is positioned to allow processes or entities in the supply chain to operate independently. It separates order-driven activities from forecast-driven activities. The closer the decoupling point is to the customer, the quicker the customer can be served.
The different groups are:
Make-to-stock: Used by firms that serve customers from finished goods inventory. Essential issue in satisfying customers is to balance the level of inventory against the level of customer service. Firms applying make-to-stock use lean manufacturing (high customer service with minimum levels of inventory investment) to achieve higher service levels for a given inventory investment
Assemble-to-order: Used by firms that combine a number of preassembled modules to meet a customer’s specification.
Make-to-order: Used by firms that make the customer’s product from raw materials, parts and components.
Engineer-to-order: Used by firms working with the customer to design the product, and then make it from purchased materials, parts and components.
Manufacturing a assemble-to-order product results in customer specific products, assembled in a similar way. The total number of combinations that can be made can be calculate as follows:
Total number of combinations = N1x N2x … x Nn
In a make-to-stock process map, it's easy to see how material flows and where inventory is held. Material in a process is in one of these two states: (1) the material is moving or “in-transit” (“work-in-process inventory”); (2) the material is sitting in inventory and acting as a “buffer” waiting to be used. A common measure is the total average value of inventory: the total investment in inventory at the firm, which includes raw material, work-in-progress, and finished goods.
The inventory turn is an efficiency measure where the cost of goods sold is divided by the total average value of the inventory. A measure directly related is days-of-supply, which is a measure of the number of days of supply of an item.
Simple systems can be analysed quickly by using Little’s Law, which says there is a long-term relationship between the inventory, throughput, and flow time. Formula:
Inventory = Throughput rate x Flow time
Throughput rate is the average rate (units/days) that items flow through a process. Flow time is the time it takes one unit to completely flow through a process. Little’s law only works if the process is stabilized.
Process selection refers to what kind of production process you use to produce a product or provide a service. There are different formats by which a facility can be arranged.
The five basic structures are:
Project layout: The product remains in a fixed location and manufacturing equipment is moved to the product rather than vice versa. Construction sites are an example.
Workcenter: Similar equipment or functions are grouped together, such as all drilling machines in one area and all stamping machines in another. This process has much flexibility and can produce much different products, but mostly on a low-volume.
Manufacturing cell: Dedicated area where products that are similar in processing requirements are produced. These cells are designed to perform a specific set of different cells in a production area, and the cells are dedicated to a limited range of products.
Assembly line: Work processes are arranged according to the progressive steps by which the product is made. These steps are defined so that a specific production rate can be achieved. An example is automobile manufacturing.
Continuous process: Similar to an assembly line in that production follows a predetermined sequence of steps, but the flow is continuous such as with liquids or drugs.
The relation between layout structures is often illustrated on a product-process matrix. The vertical axis shows the product standardization, the horizontal axis shows the volume of the products. The diagonal shows the different forms. From upper left to down right is shown the following: project, workcenter, manufacturing cell, assembly line and continuous process.
The most common assembly line is a moving conveyor that passes a series of workstations in a uniform time interval called the workstation cycle time, which is the time between successive units coming off the end of an assembly line. The work performed at each station is made up of many bits of work, called tasks. The total work to be performed at a workstation is equal to the sum of the tasks assigned to that workstation. The assembly-line balancing problem is the problem of assigning tasks to a series of workstations so that the required cycle time is met and idle time is minimized. The precedence relationship complicates this, because there is a required order in which tasks must be performed in an assembly process.
The steps in balancing an assembly-line are:
Specify the sequential relationships among tasks by using a precedence diagram;
Determine the required workstation cycle time (C):
Cycle time (C) = production time per day / required output per day (in units)
Determine the theoretical minimum number of workstations (Nt):
Theoretical minimum (Nt) = sum of task times (T) / cycle time (C)
Select a primary and secondary assignment rule for tasks;
Assign tasks to workstations until the sum of the task times is equal to the workstation cycle time or no other tasks are feasible because of time or sequence restrictions.
Evaluate the efficiency of the balance:
Efficiency = Sum of task times (T) / (actual number of workstations (Na) x workstation cycle time (C))
Rebalance if needed.
If there are problems in lines/balancing, possibilities to accommodate tasks are:
To split the task;
To share the task;
To use parallel workstations;
To use a more skilled worker;
To work overtime;
To redesign.
Assembly line balancing frequently results in unequal workstation times. Flexible line layouts are a common way of dealing with this problem. The U-shaped line with work sharing at the bottom can also solve the imbalance.
A service is an output of a process that is intangible. Every service has a service package, a bundle of goods and services that is provided in some environment.
A service package bundle consists of five features:
Supporting facility;
Facilitating goods;
Information;
Explicit services;
Implicit services.
Classifying services can be done according customer contact: the physical presence of the customer in the system. Creation of the service refers to the work process involved in providing the service itself. Service systems with a high degree of customer contact are more difficult to control and to rationalize than systems with a low degree of customer contact, because the influence of the customer. The extent of contact is the percentage of time the customer must be in the system relative to the total time it takes to perform the customer service.
Configuring services can be done with the help of a service-system design matrix. There are six different alternatives. The top of the matrix shows the degree of contact.
There are different degrees of customer/server contact:
Buffered core: Physically separated from the customer;
Permeable system: Penetrable by the customer (telephone, face-to-face contact);
Reactive system: Both penetrable and reactive to the customer’s requirements.
The greater the amount of contact, the greater the sales opportunity is. The left side of the matrix shows this. The right side shows the impact on production efficiency as the customer gets more influence on the operation. The ways a service can be delivered are: contact via e-mail, Internet and on-site technology, phone contact, face-to-face tight specs, face-to-face loose specs and face-to-face total customization.
The design matrix shows the changes in workers, operations and types of technical innovations as the degree of customer/service system contact changes.
With the advent of virtual services through the Internet, we need to account not just for a customer's interactions with a business, but for his or her interaction with other customers as well. There are two categories of contact:
Pure virtual customer contact: Companies enable customers to interact with one another in an open environment;
Mixed virtual and actual customer contact: Customers interact with one another in a server-moderated environment such as product discussion groups.
A Service Blueprint is a standard flowchart tool for service process design. It emphases what is visible and what is not visible to the customer. Blueprinting does not provide any direct guidance for how to make the process conform to that design. Therefore you can use poka-yokes: procedures that prevent mistakes from becoming defects.
A main problem in service settings is the management of waiting lines. The manager has to measure out the cost of waiting against the added cost of providing more service.
Managing queues, the following suggestions are made:
Segment the customers;
Train your servers to be friendly;
Inform your customers of what to expect;
Try to divert the customer’s attention when waiting;
Encourage customers to come during slack periods.
The Queuing System consists of three major components: (1) The source population and the way customers arrive in the system, (2) the servicing system, and (3) the condition of the customers exiting the system (back to the population or not).
Customer arrivals
Finite population: Limited-size customer pool that will use the service and at times form a line.
Infinite population: Large enough in relation to the service system so that the population size caused by subtractions or additions to the population does not significantly affect the system probabilities.
Distribution of arrivals
Arrival rate: the expected number of customers that arrive each period. A constant arrival distribution is periodic, while variable (random) arrival distributions is much more common. There are two ways to look at service arrivals: (1) analyse the time between successive arrivals to see if the times follow some statistical distribution. Usually, this time is exponentially distributed. (2) Choose a time length and try to determine how many arrivals might enter the system within this time (T). Usually, this time is Poisson distributed.
Exponential distribution: a probability distribution associated with the time between arrivals.
F(t)= λ e-λt, where λ is the mean number of arrivals per time period.
Poisson distribution: probability distribution for the number of arrivals during each time period. This is obtained by finding the probability of exactly n arrivals during T. If the arrival process is random, the distribution is the Poisson and the formula is:
PT(n) = ((λT)ne-λT)/ n!
The exponential and Poisson distributions can be derived from one another. The mean and variance of the Poisson are equal and denoted by λ. The mean of the exponential is 1/ λ and its variance is 1/ λ2.
Arrival patterns: Another characteristic. The arrivals at a system are far more controllable than is generally recognized.
Size of arrival units: A single arrival is one unit. A batch arrival is some multiple of the unit.
Degree of patience: A patient arrival is one who waits as long as necessary. An impatient arrival is one who decides to leave after seeing the length of the line (balking) or joins the line but departs after a while (reneging).
Factors to consider with waiting lines include:
Length: A waiting line can be infinite or finite, caused by legal restrictions or physical space characteristics. The length influences the arrival distribution.
Number of lines: There can be a single line or multiple lines.
Queue discipline: Rules for determining the order of service to customers in a waiting line (First come, first served (FCFS)).
Service rate: capacity of the server in number of units per time period. If this is random, μ refers to the average number of units/customers that can be serviced per time period.
There are different line structures to distinguish. The choice depends on the volume of customers served and on the restrictions imposed by sequential requirements governing the order in which service must be performed. The opportunities:
Single channel, single phase: Simplest type of waiting line, can be found in a one-person barbershop.
Single channel, multiphase: Series of services; e.g. carwash.
Multichannel, single phase: Teller’s window in a bank. The difficulty with this format is the uneven service time given each customer results in unequal speed/flow among the lines.
Multichannel, multiphase: Same to the preceding one, except that two or more services are performed in sequence. Example: admission of patients in a hospital. Because several servers are available for this procedure, more than one patient at a time may be processed.
Mixed: Multi-to-single channel and alternative path structures.
Once a customer is served, two exit fates are possible:
The customer returns to the source population and immediately become a competing candidate for service again;
Low probability of reservice.
Identify the appropriate waiting line model;
Determine: h and m;
Identify the appropriate performance measure;
Find the correct formula;
Fill out the formula.
To identify the appropriate waiting line model, there are two options given: M/M/1 (refers the arrival process) and M/D/1(refers to the service process). There are three waiting line models: (1) simple system, (2) constant service time system and (3) multichannel system. The equations for these models are:
Model 1:
Lq= λ2/ µ (µ - λ)
Ls= λ / µ - λ
Wq= Lq/ λ
Ws= Ls/ λ
Pn= (1 -λ/µ ) (λ/µ)n
ρ = λ/µ
Model 2:
Lq= λ2/ 2µ (µ - λ)
Ls= Lq+λ/µ
Wq= Lq/ λ
Ws= Ls/ λ
Model 3:
Ls= Lq+ λ/µ
Wq= Lq/ λ
Ws= Ls/ λ
Pw= Lq(λ/µ – 1)
Where
ρ = Average utilization
λ = Mean number of arrivals per time period.
µ = Mean number of people (or items) served per time period.
Wq = Average queue time
Lq = Average queue length
Ws = Average time in system
Ls = Average number in system
P0 = Probability of idle service facility
Sometimes, using a simple formula cannot solve waiting line problems. Therefore, computer simulation can be used. Some examples where simulation is used are: simulation of trucking or airline systems and simulation of factory production systems.
Sales and operations planning is a process that helps firms to better manage demand of the customer. An aggregate operations plan translates annual and quarterly business plans into broad labor and output plans for the intermediate term, with the objective to minimize the cost of resources needed to meet demand over that period.
The sales and operations planning process consists of a series of meetings, finishing with a high-level meeting where key decisions are made. The idea of this meetings is to put the operational plan in line with the business plan. To achieve that, various departments have to come to an agreement on the best course of action to achieve the optimal balance between supply and demand. The balance must occur at an aggregate level and also at the detailed individual level.
Sales and operations planning (S&OP) is the process that companies use to keep demand and supply in balance and to coordinate distribution, marketing and financial plans. Product families do aggregation on the supply side and groups of customers do this on the demand side.
Long-range planning is generally done annually and focuses on a horizon greater than one year. Intermediate-range planning covers mostly a period from 3 to 18 months. Short-range planning focuses from one day to six months.
The main purpose of an aggregate plan is to specify the optimal combination of production rate, workforce level and inventory on hand. Production rate is the number of units completed per unit of time. Workforce level refers to the number of workers needed for production (production = production rate x workforce level). Inventory on hand is unused inventory carried over from the previous period.
Internal and external factors constitute the production-planning environment. In general, the external environment is not manageable. However, there are companies in which demand for the product can be managed. If there are cyclical demand fluctuations, demand can be smoothed by using complimentary products. To manage internal factors, accurate response is used: the refined measurement of historical demand patterns blended with expert judgement to determine when to begin production of particular items. Even so, there are limits to how much demand can be controlled.
Production planning strategies are plans for meeting demand that involve trade-offs in the number of workers employed, work hours, inventory and shortages. These strategies can be helpful in managing demand. There are three different strategies:
Chase strategy: Match the production rate to the order rate by hiring and laying off employees as the order rate varies. The success of this strategy depends on having a pool of easily trained applicants to draw on as order volumes increase. This strategy influences the motivation of employees;
Stable workforce – variable work hours: Vary the output by varying the number of hours worked through flexible work schedules or overtime. This strategy provides workforce continuity and avoids the motivational impacts on employees as with a chase strategy;
Level strategy: Work with a stable workforce and a constant output rate. Shortages and surpluses are absorbed by fluctuating inventory levels, order backlogs and lost sales. Employees benefit from a stable environment, but there can be potentially decreased customer service levels and increased inventory costs.
If one of these strategies is used to manage demand, a pure strategy is used. If more than one strategy is used, a mixed strategy is used.
There are four costs relevant to the aggregate production plan:
Basic production costs: The fixed and variable costs of producing a product; direct and indirect labour costs and compensation are included;
Costs associated with changes in the production rate: Typical costs are hiring, training and laying off personnel. Hiring temporary help is a way of avoiding these costs;
Inventory holding costs: The costs of inventory, storing, insurance, taxes, spoilage and obsolence;
Backordering costs: Very hard to measure. Includes costs of expediting, loss of customer goodwill and loss of sales revenue resulting from backordering.
An aggregate production plan is the key for the success of budgeting. Accurate medium-range planning increases the likelihood of (1) receiving the requested budget and (2) operating within the limits of the budget.
Companies often use cut-and-try charting and graphic methods to develop an aggregate plan.
A cut-and-try approach involves drafting alternatives and choosing the best one. First, you formulate alternative production plans. Then, you calculate the cost of each plan. The final step is to tabulate and graph each plan and compare their costs. The cut-and-try approach does not guarantee finding the minimum-cost solution.
Charting and graphic techniques are also useful for aggregate planning in service applications.
Yield management is the process of allocating the right type of capacity to the right type of customer at the right price and time to maximize revenue or yield, given that capacity is limited. Yield management can be used to making demand more predictable. From an operational perspective, yield management is most effective when:
Demand can be segmented by the customer;
Fixed costs are high and variable costs are low;
Inventory is perishable;
Product can be sold in advance;
Demand is highly variable.
Yield management only works if pricing structures appear logic to the customer and justify the different prices. Such justification, also called rate fences, may have either a physical basis (a room with a view) or a nonphysical basis (unrestricted access to the Internet). Pricing also should relate to addressing specific capacity problems. A second issue in yield management is handling variability in arrival or starting times, durations and time between customers. This entails using forecasting methods. A third issue relates to managing the service process. A last and most critical issue is training workers and managers to work in an environment where overbooking and price changes are standard occurrences that directly impact the customer.
Enterprise resource planning (ERP) is a computer system that integrates application programs in accounting, sales, manufacturing and the other functions in a firm. Different application programs share 1 database, which can significantly benefit a firm.
The emphasis is on material requirements planning (MRP), which is the key piece of logic that ties the production functions together from a material planning and control view. The system is based on dependent demand. MRP is most valuable in industries where a number of products are made in batches using the same productive equipment.
A master production schedule (MPS) is a time-phased plan specifying how many and when the firm plans to build each end item. MPS states when the end items need to be finished. This can be used as an input to the MRP process, except if the end item is quite large or expensive. Making a MPS is dependent on the pressures from various functional areas and deadlines that are set. To ensure a good MPS, the master scheduler (the person) must:
Include all demands from product sales, warehouse replenishment, spares and interplant requirements;
Never lose sight of the aggregate plan;
Be involved with customer order promising;
Be visible to all levels of management;
Objectively trade off manufacturing, marketing and engineering conflicts;
Identify and communicate all problems.
First an aggregate operations plan need to be made, then a MPS and finally the MRP program can be used.
Flexibility of a MPS depends on the production lead-time, commitment of parts and components to a specific end item, the relationship between the customer and vendor, the amount of excess capacity and the reluctance or willingness of management to make changes. The goal of time fences is to maintain a reasonably controlled flow through the production system. A time fence is a period of time having some specified level of opportunity for the customer to make changes.
Each firm has its own time fences and operating rules. Frozen means that absolutely no changes/only minor changes can be made. Slushy refers to changes in specific products within a product group as long as parts are available. Liquid may allow almost any variations in production, with the provision that capacity remains the same and there are no long lead-time items involved.
Available to promise is a feature of MRP systems that identifies the difference between the numbers of units currently included in the master schedule and the actual (firm) customer orders.
The MRP system works as follows: the MPS states the number of items to be produced during specific time periods. A bill of materials (BOM) file identifies the specific materials used to make each item and the correct quantities of each. The inventory records file states the number of units on hand and on order. These three sources (MPS, BOM file and inventory records file) are input for the material requirements program.
The demand for products comes primarily from two main sources: (1) from customers who have placed specific orders and have a promised delivery date; (2) from the aggregate production plan, which reflects the firm’s strategy for meeting demand in the future.
The BOM file contains the complete product description and lists the materials, parts and components, and also the sequence in which the product is created. It is also called the product structure file or product tree because it shows how a product is put together. To simplify the purchasing process, all identical items need to be placed at the same level.
Inventory records contains a variety of information. The MRP program accesses the status segment of the record according to specific time periods (time buckets). A MRP program performs its analysis from the top of the product structure downward, calculating requirements level by level. Sometimes it is desirable to identify the parent iteam that caused the material requirement.
The following is a general description of the MRP explosion process, the process of calculating the exact requirements for each item managed by the system:
The requirements for level 0 items ("end items") are retrieved from the master schedule. These items are referred to as "gross requirements" by the MRP program;
The program uses the current on-hand balence together with the schedule of orders that will be received in the future to calculate the "net requirements";
Using net requirements, the program calculates when orders should be received to meet these requirements;
Next, a schedule for when orders are actually released needs to be found;
After these steps have been completed for all the level zero items, the program moves to level 1 items;
The gross requirements for each level 1 item are calculated from the planned-order release schedule for the parents of each level 1 item;
Next, net requirements, planned-order receipts and planned-order releases are calculated as described in steps 2-4 above;
This process is repeated for each level in the BOM.
The determination of lot sizes in a MRP system is complex and difficult. Lot sizes are the part quantities issued in the planned order receipt and planned order release sections of an MRP schedule. There are different techniques. The different forms are:
Lot-for-lot (L4L) is the most common technique. It sets planned orders to exactly match the net requirements, it produces exactly what is needed each week without carrying over into future periods, it minimizes carrying cost and it does not take into account setup costs or capacity limitations.
Economic Order Quantity is discussed in Chapter 11. In an EOQ model there is either fairly constant demand or safety stock must be kept to provide for demand variability. The EOQ model uses an estimate of total annual demand, the setup/order cost and the annual holding cost. It assumes that parts are used continuously during the period. The generated lot sizes do not always cover the entire number of periods.
EOQ = the root of 2DS/H, where D is the annual demand, H is the annual holding cost and S is the setup cost.
Least Total Cost is a dynamic lot-sizing technique that calculates the order quantity by comparing the carrying cost and the setup/ordering costs for various lot sizes, and then selects the lot size in which these costs are almost the same.
Least Unit Cost is a dynamic lot-sizing technique that adds ordering and inventory carrying cost for each trial lot size and divides by the number of units in each lot size, picking the lot size with the lowest unit cost.
Total quality management (TQM) may be defined as ‘managing the entire organization so that it excels on all dimensions of products and services that are important to the customer’. It has two fundamental operational goals:
Careful design of the product or service;
Ensuring that the organization’s systems can consistently produce the design.
The Malcolm Baldrige National Quality Award is an award established by the U.S. Department of Commerce and given annually to companies that excel in quality.
Fundamental to any quality program is the determination of quality specifications and the costs of achieving or not achieving those specifications. Design quality refers to the inherent value of the product in the marketplace and is thus a strategic decision for the firm. The dimensions of design quality are:
Performance: Primary product or service characteristics;
Features: Added touches, bells and whistles, second characteristics;
Reliability/durability: Consistency of performance over time;
Serviceability: Ease of repair;
Aesthetics: Sensory characteristics (sounds, feel, look..);
Perceived quality: Past performance and reputation.
Conformance quality refers to the degree to which the product or service design specifications are met. It involves activities essential in achieving conformance.
Quality at the source is concerned with a person’s work responsibility for making sure that the output corresponds the specification.
Cost of Quality (COQ) analysis is one of the primary functions of the QC departments. Cost of quality means all of the costs attributable to the production of quality that is not 100 percent perfect. The COQ can be classified into four types:
Appraisal costs: Inspection, testing;
Prevention costs: Finding quality problems, training;
Internal failure costs: Scrap, rework, repair in a company;
External failure costs: Repair, loss of goodwill, warranty replacement.
ISO 9000 and ISO 14000 are international standards agreed upon by the International Organization for Standardization (ISO). This approach was adopted in 1987 in more than 160 countries. The standards are designed to help companies document that they are maintaining an efficient quality system.
ISO 9000 has become an international reference for qualitiy management requirements in business-to-business dealing and ISO14000 is primarily concerned with environmental management.
External benchmarking goes outside the organization to examine what industry competitors and excellent performers outside of the industry are doing. Benchmarking involves the following steps:
Identify processes needing improvement;
Analyze data.
Six Sigma refers to the methods companies use to eliminate defects in their products and processes. It seeks to reduce variation in the processes that lead to product defects. Six-Sigma thinking allows managers to describe the performance of a process in terms of its variability and to compare it using the defects per millions opportunity (DPMO) metric. Defects per million opportunities (DPMO) requires three pieces of data:
Unit: The item produced or being serviced;
Defect: Any item/event that does not meet the customers’ requirements;
Opportunity: A chance for a defect to occur.
DPMO = (Number of defects/Number of opportunities for error per unit x Number of units) x 1.000.0000
The methodology side of Six-Sigma are project-oriented through the Define, Measure, Analyse, Improve, and Control (DMAIC) cycle. It is used to set the focus on understanding and achievingw what the customer wants. By the integration of analytical tools for Six-sigma, DMAIC categories can be illustrated. These tools are flowcharts, run charts, Pareto charts, checksheets, cause-and-effect diagrams, opportunity flow diagram and process control charts. Other tools are failure mode and effect analyse and design of experiments (DOE).
Statistical quality control (SQC) covers the quantitative aspects of quality management. Processes that provide goods and services usually exhibit some variation in their output. Assignable variation is the deviation in the output of a process that can be clearly identified and managed, e.g. workers are not trained. Common variation is the deviation in the output of a process that is random and inherent in the process itself, for example caused by the type of equipment used to complete a process. Statistical values involved by this are the mean and standard deviation.
Mostly, when variation is reduced, quality is improved. However, it is impossible to have zero variability. Therefore there are upper and lower specification limits: the range of values in a measure associated with a process that is allowable given the intended use of the product or service. However, Taguchi (Japanese) argues that being within specification is not a yes/no decision, but rather a continuous function.
Motorola made process capability and product design famous by adopting Six Sigma limits. The consistency of a process can be measured by the standard deviation. If the process deviates more than three standard deviations, the process is stopped. Process capability is the ability of a process to produce output within specification limits. This concept only holds meaning for processes that are in state of statistical control. The capability index is used to measure how well the process is capable of producing relative to the design specifications. The capability index (Cpk) is the ratio of the range of values produced by a process, divided by the range of values allowed by the design specification. The more off-centre, the greater the chance to produce defective parts.
Cpk = min[(Xbar-LSL/3sigma) or (USL-Xbar/3sigma)]
Sometimes it is useful to calculate the actual probability of producing a defect. Firstly, the Z score associated with the upper and lower specification limits needs to be calculated.
Zlsl = (LSL-Xbar/sigma)
Zusl = (USL-Xbar/sigma)
An easy way to get the probabilities associated with these Z values is to use the NORM.S.DIST function built into Excel.
Process control is concerned with monitoring quality while the product or service is being produced. Statistical process control (SPC) involves testing a random sample of output from a process to determine whether the process in producing items within a preselected range. Attributes are quality characteristics that are classified as either confirming or not conforming to specification.
A p-chart can be used to decide whether the item is good or bad. The upper and lower control limits need to be defined and be drawn on a graph. After that, the fraction defective of each individual sample tested need to be plotted.
UCL = p bar + zsp
LCL = p bar - zsp or 0 if less than 0
P bar is the fraction defective; sp is the standard deviation, n the sample size and z the number of standard deviations for a specific confidence.
In the case of the p-chart, the item is either good or bad. There are times when the product/service can have more than one defect. A c-chart can be used to monitor the number of defects per unit. The c-chart is the Poisson. If c is the number of defects for a particular unit, than c bar is the average number of defects per unit, and the standard deviation is the square root of c bar.
X-bar and R- (range) charts are widely used in statistical process control. No attribute sampling is used, but variables sampling: the actual weight/volume/number of inches or other variable measurements are measured. Based on these measurements, control charts are developed to determine the acceptability or rejection of this process. There are four important issues to address in creating a control chart: (1) the size of the samples, (2) the number of samples, (3) the frequency of samples and (4) the control limits.
If the standard deviation of the process distribution is known, the X bar-chart may be defined:
UCLX bar = X two bars + zSx bar
LCL = X two bars - zSx bar
An X bar-chart is a plot of the means of the samples that were taken from the process. X two bars is the average of the means.
In practice, the standard deviation of the process is not known. Therefore, an R-chart is often used, which is a plot of the average of the range within each sample. The range is the difference between the highest and lowest numbers in that sample.
X bar = (X1 + ... + Xn/n)
X two bars = (X bar 1 + ... + X bar m/m)
R bar = (R1 + ... + Rm/m)
Where X two bars is the average of the means of the samples, j the sample number, m the total number of samples, Rj the difference between the highest and lowest measurement in that sample and R bar the average of the measurement differences R for all samples.
Acceptance sampling is performed on goods that already exist to determine what percentage of products conforms to specifications.
You should try to get down inventory as far as possible. There are three inventory models. The techniques described here are most appropriate when demand is difficult to predict with great precision:
The single-period model: Used when a one-time purchase of an item is made, for example a T-shirt for a one-time sporting event.
Fixed-order quantity model: Used when we want to maintain an item in-stock, and when the item is resupplied, a certain number of units must be ordered each time. Inventory is monitored until it gets down to a level where the risk of stocking out is great enough that we are compelled to order.
Fixed-time period model: Also used when the item should be in-stock and ready to use, but the difference is that the item is ordered at certain intervals of time, for example each Thursday morning.
Inventory is the stock of any item or resource used in an organization. An inventory system is a set of policies and controls that monitor levels of inventory and determine what levels should be maintained, when stock should be replenished and how large orders should be. Manufacturing inventory are items that contribute to or become part of a firm’s product output. Inventory refers to the tangible goods to be sold and the supplies necessary to administer the service.
Purposes of having a supply of inventory can be:
To maintain independence of operations;
To meet variation in product demand;
To allow flexibility in production scheduling;
To provide a safeguard for variation in raw material delivery time;
To take advantage of economic purchase order size;
Many other domain-specific reasons.
In making decisions that affects inventory size, the following costs must be considered:
Holding or carrying costs: All costs for holding goods and the storage facilities, taxes, insurance etc.;
Setup (production change) costs: The costs of making each different product;
Ordering costs: The managerial and clerical costs to prepare the purchase or production order;
Shortage costs: The costs of having a stock out.
In independent demand, the demands for various items are unrelated to each other. In dependent demand the need for any one item is a direct result of the need for some other item, usually an item of which it is a part.
An inventory-control-system design matrix is a framework that describes how demand, transaction cost and the risk of obsolete inventory map into different types of systems. Transaction cost is dependent on the level of integration and automation iincorporated in the system. Manual systems use a two-bin logic, which are dependent on human posting of the transactions to replenish inventory, which is relatively expensive compared to using a computer to automatically detect when an item needs to be ordered.
An inventory system provides the organizational structure and the operating policies for maintaining and controlling goods to be stocked.
In a single-period inventory model, a decision is just a one-time purchasing decision where the purchase is designed to cover a fixed period of time and the item will not be reordered. An example is the “newsperson” problem. The optimal stocking level occurs at the point where the expected benefits derived from carrying the next unit are less than the expected costs for that unit. Co is the cost per unit of demand overestimated, Cu is the cost per unit of demand underestimated. The expected marginal cost equation becomes:
P(Co) ≤ (1 – P)Cu
Where P is the probability that the unit will not be sold and 1 – P the probability of it being sold. P is:
P ≤ Cu / (Co + Cu)
Multiperiod inventory systems involve items that will be purchased periodically where inventory should be kept in stock to be used on demand. There are two types of systems. The fixed-order quantity model (EOQ/Q-model) is an inventory control model where the amount requisitioned is fixed and the actual ordering is triggered by inventory dropping to a specified level of inventory. The fixed-time period model (P-model) is an inventory control model that specifies inventory is ordered at the end of a predetermined time period. The interval of time between orders is fixed and the order quantity varies.
The differences between this two types of inventory systems are:
The fixed-time period model has a larger average inventory because it must also protect against stock out during the review period T.
The Q-model favors more expensive items because average inventory is lower.
The Q-model is more appropriate for important items such as critical repair parts, because there is closer monitoring and therefore quicker response to potential stock out.
The Q-model requires more time to maintain because every addition or withdrawal is logged.
When each of the two models is put into use and becomes an operating system, the fixed-order quantity system focuses on order quantities and reorder points and in the fixed-time period system a decision to place an order is made after the stock has been counted or reviewed.
The fixed-order quantity model tries to determine the specific point R, at which an order will be placed and the size of that order, Q. Order point R is always a specified number of units. The inventory position is the amount on-hand plus on-order minus backordered quantities. When inventory has been allocated for special purposes, the inventory position is reduced by these allocated amounts.
In constructing any inventory model, the first step is to develop a functional relationship between the variables of interest and the measure of effectiveness. When you are concerned with cost, the following equation pertains:
Total annual cost = annual purchase cost + annual ordering cost + annual holding cost
TC = DC + (D/Q)S + (Q/2)H
The point where the total cost is a minimum, Qopt, can be calculated as follows:
TC = DC + (D/Q)S + (Q/2)H
(dTC/dQ) = 0 + (-DS/Qsquare) + (H/2) = 0
Qopt = the root of (2DS/H)
Where
TC = Total annual cost
D = Annual demand
C = Cost per unit
Q = Quantity to be ordered
S = Setup cost or cost of placing an order
R = Reorder point
L = Lead time
H = Annual holding and storage cost per unit of average inventory
Because this simple model assumes constant demand and lead time, neither safety stock nor stock-out is necessary, and the reorder point R is simply: R = d (bar) L, where d bar is the average daily demand and L is the lead time in days.
If there is variety in demand, there needs to be safety stock (SS): the amount of inventory carried in addition to the expected demand.
If demand varies, the reorder point is:
R = d (bar) L + zσL
Where
R = reorder point in units
d bar = average daily demand
L = lead time in days
z = number of standard deviations for a specified service probability
σL = standard deviation of usage during lead time
Demand can be determined by:
d bar = (d1 + ... + dn)/n
If the standard deviation needs to be computed over several days, it is:
σL = the root of (σ1square + ... +σlsquare)
Safety stock (SS) = zσL
In a fixed-time period system, inventory is counted only at particular times. Reorders need to be placed on time T and the SS that needs to be reordered is:
Safety stock = zσT+L
The quantity to order, q, is:
Order quantity = average demand over the vulnerable period + SS – Inventory currently on hand (plus on order, if any)
q = d bar (T+L) + zσ – I
Where
q = Quantity to be ordered
T = The number of days between reviews
L = Lead time in days
d bar = Forecast average daily demand
z = Number of standard deviations for a specified service probability
σT+L = Standard deviation of demand over the review and lead time
I = Current inventory level
Inventory is managed directly and is related to the financial performance of the firm. The average inventory and the inventory turn for an individual item is:
Average inventory value = (Q/2 + SS)C
Inventory turn = costs of goods sold/average inventory value
Inventory turn = DC / ((Q/2 + SS)C) = D / (Q/2 + SS)
Price-break models are used for products where the selling price of an item varies with the order size.
The Pareto principle states that 20 percent of the people controlled 80 percent of the wealth. This is also true in inventory systems, where a few items account for the bulk of an investment.
ABC inventory classification divides inventory into dollar volume categories that map into strategies appropriate for the category. A means high dollar volume, B moderate dollar volume and C low dollar volume. By using this classification, not every inventory needs to go through counting; the focus can be on the most important items in stock. This is related to the Pareto principle: the few having the greatest importance.
Cycle counting is a physical inventory-taking technique in which inventory is counted on a frequent basis rather than once or twice a year. The key to effective cycle counting and to accurate records lies in deciding which items are to be counted and by whom. The easiest time for stock to be counted is when there is no activity in the stockroom or on the production floor.
Lean production are the integrated activities designed to achieve high-volume, high-quality production using minimal inventories of raw materials, work-in-process, and finished goods. Lean production refers to a focus on eliminating as much waste as possible. Customer value is, in the context of lean production, something for which the customer is willing to pay. Waste is anything that doesn’t add value from the customer’s perspective.
There are seven types of waste: production of defect products, waste of overproduction, inventory waste, waste of waiting time, unnecessary processing (repairs), waste of motion and transportation waste.
Services operate in a sea of uncertainty and variability that are much harder to control, because of uncertainty in task times, uncertainty in demand and customers’ production roles. Lean production and Six Sigma work best in repeatable, standardized operations, but can be applied to services as well.
The Toyota Production System was developed to improve quality and productivity and is predicated upon two philosophies that are central to the Japanese cultur: elimination of waste and respect for people.
As the concepts have been evolved and become applied to the supply chain, the goal of maximizing customer value has been added. The value stream consists of value-adding and non-value-adding activities required to design, order, and provide a product from concept to launch, order to delivery, and raw materials to customers. Waste reduction relates to the optimization of value-adding activities and elimination of non-value-adding activities that are part of the value stream. These are different components of a supply chain that should use a lean focus:
Lean suppliers;
Lean procurement;
Lean manufacturing;
Lean warehousing;
Lean logistics;
Lean customers.
Value stream mapping (VSM) is a graphical way to analyze where value is or is not being added as material flows through a process. Value stream mapping is a two-part process: first depicting the “current state” of the process and second a possible “future state”. Kaizen is the Japanese philosophy that focuses on continuous improvement. The Kaizen bursts identify specific short-term projects that teams work on to implement changes in the process.
There is a set of key principles that can guide the design of lean supply chains. The first and second one relate to internal production processes, the third applies lean concepts to the entire supply chain. The principles include:
Lean Layouts:
Group technology
Quality at the source
JIT production
Lean Production Schedules:
Uniform plant loading
Kanban production control system
Determination of number of Kanbans needed
Minimized setup times
Lean Supply Chains:
Specialized plants
Collaboration with suppliers
Building a lean supply chain
Preventive maintenance is emphasized to ensure that flows are not interrupted by downtime or malfunctioning equipment. This involves periodic inspection and repair designed to keep equipment reliable.
Lean concepts:
Group Technology (GT) is a philosophy in which similar parts are grouped into families, and the processes required to make the parts are arranged in a manufacturing cell;
Quality at the source means do it right the first time and, when something goes wrong, stop the process or assembly line immediately;
Just-in-time (JIT) is a philosophy of continuous and forced problem solving that drives out waste (storage, inspection, waiting etc.). It is typically applied to repetitive manufacturing. JIT exposes problems that are otherwise hidden by inventory.
Lean production requires a stable schedule over a lengthy time horizon. This is accomplished by:
Level schedule: A schedule that pulls material into final assembly at a constant rate and allows the various elements of production to respond to pull signals;
Freeze window: The period of time during which the schedule is fixed and no further changes are possible. Backflush is calculating how many of each part were used in production and using these calculations to adjust actual on-hand inventory balances. This eliminates the need to actually track each part used in production;
Underutilization and overutilization of capacity.
Uniform plant loading is smoothing the production flow to dampen schedule variation. When a change is made in a final assembly, the changes are magnified throughout the line and the supply chain.
Kanban is the Japanese translation for sign or instruction card. In Kanban production control systems, only cards or containers are used to make up the Kanban pull system and regulate JIT flows. Level scheduling requires material to be pulled into final assembly in a pattern, which is uniform enough to allow the various elements production to respond to pull signals. Kaban significantly reduces the setup costs and changeover times achieving a smooth flow.
The determination of the number of Kanbans needed can be done according to:
k = (Expected demand during lead time + SS) / size of the container
= (DL(1+S))/C
where k = number of kanban card sets, D = average number of units demanded per period, L = lead time to replenish an order, S = safety stcok expressed as a percentage of demand during the lead time and C = container size.
A Kanban system does not produce zero inventory, but it controls the amount of material than can be in process at a time.
Minimized Setup Times are reductions in setup and changeover times that are necessary to achieve a smooth flow.
The following concepts are related to lean network design:
Specialized plants: Small specialized plants rather than large vertically integrated manufacturing facilities are important. Speed and quick response to changes are keys to the success of a lean supply chain;
Collaboration with suppliers: If a firm shares its projected usage requirements with its vendors, vendors have a long-run picture of the demands and the firm can further reduce their buffer inventories. Maintaining stock at a lean level requires frequent deliveries during the day;
Building a lean supply chain: A supply chain is the sum total of organizations involved. To be lean, everyone’s got to be on the same page! Muda = waste.
10 of the more successful techniques applied to service companies to become more lean are:
Organize problem-solving groups;
Upgrade houskeeping;
Upgrade quality;
Clarify process flows;
Revise equipment and process technologies;
Level the facility load;
Eliminate unneccessary activities;
Reorganize physical configuration;
Introduce demand-pull scheduling;
Develop supplier networks.
Strategic sourcing is the development and management of supplier relationships to acquire goods and services in a way that aids in achieving the immediate need of the business. Depending on the contract duration, transaction costs and specificity (how common the item is) of the product, a firm’s purchasing can be classified into these types of processes: strategic alliance, spot purchase, request for proposal (RFP), request for bid and reverse auctions, vendor managed inventory and electronic catalog.
The Bullwhip Effect describes the phenomenon of variability magnification as we move from the customer to the producer in the supply chain. It indicates a lack of synchronization among supply chain members.
Fisher has developed a framework to help managers understand the nature of demand for their products and then devise the supply chain that can best satisfy that demand. Because each category requires a distinctly different kind of supply chain, the root cause of supply chain problems is a mismatch between the type of product and type of supply chain.
Functional products are staples that people buy in a wide range of retail outlets, such as grocery stores and gas stations. Because such products satisfy basic needs, which do not change much over time, they have stable, predictable demand and long life cycles. However, there is a lot of competition and therefore low profit margins.
Innovative products are products such as fashionable clothes and personal computers that typically have a life cycle of just a few months. The newness of these products makes demand for them unpredictable.
Hau Lee expands on Fisher’s ideas by focusing on the supply side of the supply chain. His framework is illustrated in a two by two matrix resulting from low/high uncertainty and low/high demand uncertainty. A stable supply process is one where the manufacturing process and the underlying technology are mature and the supply base is well established. An evolving supply process is where the manufacturing process and the underlying technology are still under early development and are rapidly changing.
There are four types of supply chain strategies:
Efficient supply chains utilize strategies aimed at creating the highest cost efficiency
Risk-hedging supply chains utilize strategies aimed at pooling and sharing resources chains in a supply chain to share risk
Responsive supply chains utilize strategies aimed at being responsive and flexible chains to the changing and diverse needs of the customers
Agile supply chains utilize strategies aimed at being responsive and flexible to customer needs, while the risks of supply shortages or disruptions are hedged by pooling inventory and other capacity resources
Outsourcing is the act of moving a firm’s internal activities and decision responsibility to outside providers. This allows a company to create a competitive advantage while reducing cost. Applying to this capability, an entire function (e.g. distribution, manufacturing) or some elements of an activity (e.g. producing parts) may be outsourced. Reasons to move firm’s activities outside the firm can be motivated by organizational and financial factors as well as the factor of improvement.
Logistics is a term that refers to the management functions that support the complete cycle of material flow: from the purchase and internal control production materials to the planning and control of work-in-process to the purchasing, shipping and distribution of the finished product. Outsourcing logistics is for more common nowadays.
Green sourcing refers to the finding of new environmentally friendly technologies and the increasing of the use of recyclable materials. It helps to reduce drive cost in a variety of ways: product content substitution, waste reduction, and lower usage. To transform a traditional process to a green sourcing one, the Six-step process can be applied:
Assess the opportunity;
Engage internal supply chain sourcing agents;
Assess the supply base;
Develop the sourcing strategy;
Implement the sourcing strategy;
Institutionalize the sourcing strategy.
Total Cost of Ownership (TCO) is a financial estimate of the cost of an item, which determines direct and indirect costs of a product or system. It includes all the costs related to the procurements and use of items, including any related costs in disposing of the item after it is no longer useful. It can be applied to internal costs or more broadly to costs throughout the supply chain.
The costs can be categorized into three broad areas:
Acquisition costs
Purchase planing costs
Quality costs
Taxes
Purchase price
Financing costs
Ownership costs
Energy costs
Maintenance and repair
Financing
Supply chain/supply network costs
Post-ownership costs
Disposal
Environmental costs
Warranty costs
Product liability costs
Customer dissatisfaction costs
To evaluate supply chain efficiency, two common measures are used: inventory turnover and weeks of supply.
The inventory turnover are the costs of goods sold divided by the average inventory value, whereas the days of supply are the inverse of inventory turn scaled to days.
Inventory turnover = cost of goods sold / average aggregate inventory value
Cost of goods sold are the cost for a company to produce goods or services provided to customers. This does not include the selling and administrative expenses of the company. The average aggregate inventory value is the total value of all items held in inventory for the firm valued at cost. It includes the raw material, work-in-process, finished goods and distribution inventory considered owned by the company.
Weeks of supply is the preferred measure of supply chain efficiency that is mathematically the inverse of inventory turn.
Weeks of supply = (Average aggregate inventory value/cost of goods sold) * 52 weeks
Logistics is a part of the supply chain process that plans, implements, and controls the efficient, effective flow and storage of goods/service. It is the art and science of obtaining, producing and distributing material and product in the proper place and in the proper quantities.
International logistics is concerned with managing all functions of logistics internationally. Global and local supply chains can differ in distances and time differences, forecasting, exchange rates, infrastructure, variety of products and foreign rules.
Third-party logistics companies are companies that manages all or part of another company’s product delivery operations.
When discussing logistics, different decisions have to be made. One of them concerns transportation modes (The logistics-system design matrix):
Highway (truck): Almost all products use highway transportation. The highway offers great flexibility for moving goods to virtually any location not separated by water;
Water (ship): High capacity and low cost, but transit times are slow and large areas of the world are not directly accessible;
Air: Fast, but expensive. Small, light, expensive items are most appropriate for this mode of transportation;
Rail (trains): Fairly low cost, but transit times can be long and can vary. The suitability of rail depends on the rail infrastructure;
Pipelines: Highly specialized for liquids, gases and solids in slurry forms. The costs per mile are low, and no packaging is necessary. However, the initial costs are very high;
Hand Delivery: The last step in many supply chains. Getting the product to the customer is often a slow and costly activity due to the high labour content.
Another decision that has to be made when discussing logistics is the warehouse design.
Cross-docking is an approach used in consolidation warehouses where, rather than making larger shipments, large shipments are broken down into small shipments for local delivery in an area. This often can be done in a coordinated manner so that the goods are never stored in inventory.
Hub-and-spoke systems are systems that combine the idea of consolidation and that of cross-docking. The warehouse is a “hub” and its sole purpose is sorting goods. These goods are shipped as soon as possible to a specific location.
An important element in designing a company’s supply chain is the location of its facilities. Criteria that influence the manufacturing plant and warehouse location planning are:
Proximity to customers: The closer the customers, the sooner they have the product and the more influence they have on developing and building a product;
Business Climate: The presence of similar(-sized) businesses in the neighbourhood, government legislation and local government intervention all influence the business climate of a company;
Total costs: The objective is to select a location with the lowest total cost. The total cost consists of regional cost, inbound distribution costs and outbound distribution costs. There can be hidden costs;
Infrastructure: Adequate road, rail, air and see transportation infrastructure is vital, as well as energy and telecommunications requirements;
Quality of labour: The educational and skill levels of the labour pool must match the company’s needs;
Suppliers: High-quality suppliers makes a given location suitable;
Other facilities: The location of other plants or distribution centers of the same company may influence a new facility’s location in the network. The product mix and capacity are also important;
Free trade zones: A closed facility under the supervision of government customs officials into which foreign goods can be brought without being subject to the payment of normal import duties;
Political risk: These risks determine the location in both the country of location and the host country;
Government barriers: A lot of barriers are removed today. However, there can still be nonlegislative and cultural barriers which should be considered;
Trading blocs: A group of countries that agree on a set of special arrangements governing the trading of goods between member countries. Companies may locate in places affected by the agreement to take advantage of new market opportunities;
Environmental regulation: The regulation influences both the costs and the relationship with the local community;
Host community: The host’s interest in having the plant in its midst is important, just as the local educational facilities and the quality of life;
Competitive advantage: The most important in choosing a location is that it should give a competitive advantage to the company. Innovation should be stimulated and needs to provide the best environment for global competitiveness.
There are several techniques available to decide about the plant location. The first one is factor-rating system, which uses weights to assign importance of qualitative and quantitative factors. There are no exact results dues to subjectivity of weights.
The steps for using this method:
List relevant factors;
Assign importance weight to each factor (0 - 1);
Develop scale for each factor (1 - 100);
Score each location using factor scale;
Multiply scores by weights for each factor and total;
Select location with maximum total score.
A major disadvantage of this method is that the factors do not account for the wide range of costs.
Transportation method is a special linear programming method that is useful for solving problems involving transporting products from several destinations. It estimates the costs of using a network of plants and warehouses.
The centroid method is a technique for locating single facilities that considers the existing facilities, the distances between them and the volumes of goods to be shipped. In its simplest form, this method assumes there is no difference between inbound and outbound transportation costs, and it does not include special shipping costs for less than full loads. This technique begins by placing the existing locations on a coordinate grid system. Coordinates are usually based on longitude and latitude measures due to the rapid adoption of GPS.
The formulas:
Cx = (∑Dix*Vi)/∑Vi
Cy = (∑Diy*Vi)/∑Vi
Where
Cx = X coordinate of the centroid
Cy= Y coordinate of the centroid
Dix = X coordinate of the ith location
Diy = Y coordinate of the ith location
Vi = volume of goods moved to or from the ith location
In determining the location of service facilities, other factors are important. It depends on the number of locations and the size and characteristics of the places.
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