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Chapter 1-17

Operations - Chapters 1-17 Complete Chapter Notes.doc

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Wilfrid Laurier University
Paul Iyogun

Chapter One: Introduction to Operations Management Operations Management – the management of processes or systems that create goods and/or provide services Process – a series of linked actions, changes, or functions bringing about a result Three types of processes: 1) Core - directly create goods/services 2) Support - support core processes 3) Managerial - govern the system Using example of an airline: a) Core Processes: reservations, boarding and flying the planes, handling luggage b) Support Processes: forecasting, scheduling, managing inventories c) Managerial Processes: capacity planning, locating facilities, employee motivation Efficiency – operating at minimum cost and time Effectiveness – achieving the intended goals (quality and responsiveness) Transformation Process Food Processor: Inputs Processes Output Raw vegetables Cleaning Canned vegetables Metal sheets Making cans Water Cutting Energy Cooking Labour Packing Building Labelling Equipment Value Added – the difference between the cost of inputs and the value or price of outputs In non-profit organizations, the value of outputs (police, fire protection) is their value to society. In for profit organizations , the value of outputs is measured by the prices customers are willing to pay. A company may find that it is producing an item much earlier than the scheduled delivery. This causes the item to sit in storage longer than necessary which adds no value. Reducing storage time would reduce the transformation cost and increase the value added. Lead Time – the time between ordering a good/service and receiving it Other Functions Supporting Operations: - Accounting – supplies info to management on costs of labour/materials - Logistics – storage, transportation of raw material to the plant, warehouse, retail outlets, customers - Product Design – create goods/services - Maintenance – general upkeep and repair of equipment, buildings and grounds etc. - Manufacturing engineering – design or purchase of the machines and equipment needed in the production process - MIS – provides management with information it needs to effectively manage mainly through design systems (hardware/software) to capture relevant information and prepare reports - Purchasing – procurement of materials, supplies, equipment and services - Personnel/HR – concerned with recruitment and training of personnel, labour relations etc. Certain decisions affect the design of the system and others are operational. Costs, space, capacities, and quality are directly affected by design decisions. Even though operations management is not solely responsible for making all design decisions, it can provide a wide range of information that will have an effect on the decisions. Responsibilities of Operations Managers 1. Planning - capacity, location, layout 2. Organizing - departments, staffing, suppliers 3. Directing - scheduling, job assignments, purchasing 4. Controlling - quality control, motivation, inventory control Decision Making 1) Models – an abstraction of reality; a simplified representation of something - models ignore the unimportant details so that attention can be concentrated on the most important aspects of a situation, thus increasing the opportunity to understand a problem and its solution 2) Quantitative Approaches - an attempt to obtain optimum solutions to the mathematical models of managerial problems, sometimes done by solving a set of equations (linear programming, queuing techniques etc.) 3) Analysis of Trade-offs - ex. deciding on the amount of inventory to stock, the manager may take into account the trade-off between the increased level of customer service that the additional inventory would yield and the increased costs required to stock that inventory - in scheduling overtime, the manager may weigh the value of the increased output against the higher costs of overtime (higher labour costs, lower productivity, lower quality) 4) Systems Approach System – a set of interrelated parts that must work together - the output and objectives of the organization as a whole take precedence over those of any one part - this is essential whenever something is being designed, redesigned, improved or changed An example of the systems approach is when investigating whether the upcoming model of a car will have antilock brakes, a designer make take into account how customers will view the change, instructions for using the brakes, chances for misuse, the cost of producing the new brakes, installation, recycling worn-out brakes, and repair procedures. 5) Establishing Priorities - managers must direct their efforts to where they will do the most good to avoid wasting time Pareto phenomenon – a few factors account for a high percentage of results achieved 6) Ethics - when making decisions, managers must consider how their decisions will affect shareholders, employees, customers, the community, and the environment Craft Production – system in which highly skilled workers use simple, flexible tools to produce small quantities of customized goods - production was slow and costly and when parts failed, the replacements had to be custom made Division of Labour – breaking up a production process into small tasks so that each worker performs a small portion of the overall job Interchangeable Parts – parts of a product made to such precision that they do not have to be custom fitted Mass Production – system in which lower-skilled workers use specialized machinery to produce high volumes of standardized goods Total Quality Management – involving every employee in a continual effort to improve quality and satisfy the customers Lean Production – systems that use minimal amounts of resources to produce a high volume of high-quality goods with some variety Craft Production Mass Production Lean Production Description High variety, High volume of Moderate to high customized output, standardized volume of output, with one or a few output, emphasis with more variety skilled workers on volume than mass responsible for an production entire unit of output Examples Home remodelling, Sugar, steel, Automobile landscaping, hotels, paper components, painting, surgery industrial equipment, furniture Advantages Wide range of Low cost per unit, Flexibility, variety, choice, output requires mostly high quality of tailored to low-skilled workers goods customer needs Disadvantages Slow, requires Rigid system, No safety nets to skilled workers, few difficult to offset any system economies of accommodate breakdowns, fewer scale, high cost changes in output opportunities for and low volume, product employee standardization design, or process advancement, design more worker stress, requires higher-skilled workers than mass production E-Commerce – use of the Internet and other electronic networks to buy and sell goods and services Supply Chain – a sequence of activities and organizations involved in producing and delivering a good or service Organizations must constantly monitor current trends and take them into account in their strategies and operations management: a) The Internet and e-commerce b) Technology c) Globalization d) Supply chains Chapter Two: Competitiveness, Strategic Planning, and Productivity Competitiveness – ability and performance of an organization in the marketplace compared to other organizations that offer similar goods or services Strategy – the long-term plans that determine the direction an organization takes to become (or remain) competitive Strategic Planning – the managerial process that determines a strategy for the organization Key purchasing Criteria – the major elements influencing a purchase: price, quality, variety and timeliness (the availability of goods/services when they are needed by the customer) Value = quality, timeliness, etc. this equation represents the “best buy” or best “value” price In complex purchases, customers may use two categories of criteria: order qualifiers and order winners: Order Qualifiers – purchasing criteria that customers perceived as minimum standards of acceptability to be considered for purchase - these may not be sufficient to get a customer to purchase from the organization Order Winners – purchasing criteria that cause the organization to be perceived as better than the competition Over time, a characteristic that once was an order winner may become an order qualifier, or vice versa. Organizations compete by emphasizing one or more of the key purchasing criteria in their goods/services. These are called “competitive priorities.” Competitive Priorities – the importance given to operations characteristics: cost, quality, flexibility, and delivery - in this context, flexibility means being able to produce a variety of goods/services in one facility and delivery means being able to consistently meet promised due dates (usually through Just-in-Time inventory systems) Strategic Planning is the process of determining a strategy, long-term plans that will set a new direction for an organization, and implementing it through allocation of resources and action plans. Progressive organizations perform strategic planning regularly, while others may only perform is when facing a crisis. Strategic planning starts with top management soliciting the performance of the industry and where it is headed in the next 1-5 years. Next management may form/adjust the organization’s mission and vision and brainstorm/evaluate ways to achieve them. Finally, the chosen strategy is implemented by determining a set of action plans at the operating department level. The analysis usually concerns the competitiveness of the organization. The SWOT (strength, weaknesses, opportunities, and threats) analysis will be used to build strengths, take advantage of market opportunities, and avoid/neutralize its weaknesses to defend against threats. See page 30. Mission – where the organization is going now Vision – where the organization desires to be in the future Values – shared beliefs of the organization’s stakeholders See page 32 for examples. Mission/Vision  Goals  Organizational Strategy  Functional Strategies  Finance/Marketing/Ops Tactics – medium term plans used as components of a strategy Action Plan – a medium or short term project to accomplish a specific objective, assigned to an individual, with a deadline and the resources needed An example for a high school student: Mission/Vision: Live a good life Goal: Successful career, good income Strategy: Obtain a university education Tactics: Select a university and a major; decide how to finance the education Action Plans: Register, buy books, take courses, study See page 34, figure 2-2 for an example of objectives and an action plan Operations Strategy – the approach that is used to guide the operations function - comprises a set of well-coordinated policies, objectives, and actions plans, directly affecting the operations function, which is aimed at securing a long-term sustainable competitive advantage Nine Strategic Decision Categories 1. Facility – how to specialize or focus each facility (by market, product group, or production process) 2. Capacity – long-term capacity decisions relate to size of plants and major equipment - the main issue is whether and how to change the capacity in anticipation of future demand 3. Vertical Integration – the ownership of a major part of the supply chain 4. Vendor Relations – work with a supplier to assure/control its production processes 5. Product Mix and New Products – flexible production systems are necessary for new products 6. Process Types and Technology – choosing the appropriate technologies and degree of automation 7. Human Resources – workers/staff are appraised, selected, developed, motivated, promoted etc. 8. Quality – product quality is determined during the design/production 9. Operations Infrastructure and Systems – choosing a computerized planning and control system - whether to use JIT production, operations policies, and the type of production/delivery system Formulation of an Operations Strategy 1. Link the organization goals to the operation strategy 2. Categorize the customers into types (major and other) and determine which of the four competitive priorities (cost, quality, delivery and flexibility) should be emphasized 3. Group product lines into types (ex. low volume and high volume) 4. Conduct an operations audit to determine the strengths and weaknesses of the current operations strategy in each of the nine strategic decision categories 5. Assess the degree of focus at each plant 6. Develop an operations strategy and re-allocate product lines to plants if necessary Generic Operations Strategies - theme based operations improvement programs (such as JIT and total quality management) - an example is the continuous improvement strategy where a company can introduce new product features and continuously improve both products and processes Time-Based Competition – strategy that focuses on reduction of time needed to accomplish tasks Outsourcing – buying a part of a good/service or a segment of production/service process from another company or supplier Productivity = Output Input - this is a measure of productive use of resources Productivity Growth = Current Period Productivity – Previous Period Productivity Previous Period Productivity Ex. If productivity increased from 80 to 84, the growth rate would be: 84 – 80 = 0.05 or 5% 80 To measure productivity, it depends on the type of job performed. The following are examples of labour productivity: Square metres of carpet installed = Square metres of carpet installed per labour hour Labour hours Number of offices cleaned = Number of offices cleaned per shift Number of shifts Units of output = Units of output per hour of machine use Machine Hour Determine the productivity: a) Four workers installed 720 square metres of carpet in eight hours Productivity = Square metres of carpet installed Labour hours worked = 720 square metres 4 workers x 8 hours = 22.5 square metres/worker hour b) A machine produced 68 usable pieces of a part in two hours Productivity = Usable pieces Production time = 68 pieces 2 hours = 34 pieces/hour Calculations of inputs in a multifactor productivity measure use a common unit of measurement, such as dollars. For example: Quantity of production _ Labour cost ($) + Materials cost ($) + Machine overhead ($) Output = 7,040 units Input costs: Labour $1,000, Materials $520, Machine Overhead $2,000 Multifactor Productivity = Output = ____7,040 units_______ Labour + Materials + Machine Overhead $1,000 + $520 + $2000 = 2 units/dollar Chapter Three: Demand Forecasting Demand Forecast – the estimate of expected demand during a specified future period Features Common to All Forecasts 1. Forecasting techniques generally assume that the same underlying causal system that existed in the past will continue to exist in the future 2. Forecasts are rarely perfect; actually results usually differ from predicted values - no one can predict precisely how related factors will impinge upon the variable in question - allowances should be made for inaccuracies 3. Forecasts for groups of items tend to be more accurate than forecasts for individual items - ex. forecast for total sales of a new T shirt will be more accurate than the forecast for each size/colour 4. Forecast accuracy decreases the farther the forecasted time period is into the future Forecasting Horizon – the range of time periods we are forecasting for Elements of a Good Forecast 1. Forecasting horizon must be long enough so that its results can be used 2. The degree of accuracy of the forecast should be stated 3. The forecasting method/software chosen should be reliable; it should work consistently 4. The forecast should be expressed in meaningful units Steps in the Forecasting Process 1. Determine the purpose of the forecast - the level of detail required, the amount of resources that can be justified and the level of accuracy 2. Establish a forecasting horizon 3. Select a forecasting technique 4. Gather and analyze relevant historical data 5. Prepare the forecast 6. Monitor the forecast There are two general approaches to forecasting: judgemental and quantitative. Judgemental methods consist mainly of subjective inputs. Quantitative methods involve either the use of a time series model to extend the historical pattern of data into the future or the development of associative models that attempt to utilize causal variables to make a forecast. Judgemental Methods – use non-quantitative analysis of historical data and/or analysis of subjective inputs from consumers, sales staff, managers, executives, similar products, and experts to help develop a forecast Time Series Models – extend the pattern of data into the future Associative Models – use explanatory variables to predict future demand for the variable of interest Judgemental Methods - executive opinions - sales force opinion - consumer surveys - historical analogies (looking at the demand for a similar product in the past) - expert opinions Delphi Method – experts complete a series of questionnaires, each developed from the previous one, to achieve a consensus forecast (a part of the “expert opinions” method) Time Series – a time-ordered sequence of observations taken at regular intervals of time Analysis of time series data requires the analyst to identify the underlying behaviour of the series: 1. Level (Average) – a horizontal pattern of time series – constant 2. Trend – persistent upward/downward movement in data 3. Seasonality – regular wavelike variations related to the calendar, weather, or recurring events 4. Cycle – wavelike variation lasting more than one year 5. Irregular Variation – caused by unusual one-time explainable circumstances (not typical behaviour) 6. Random Variation – residual variations after all other behaviours are accounted for Naive Forecast – for a stable series, the naive forecast for the period equals the previous period’s actual rate Period 1, actual 50 Period 2, actual 53 (change from previous value of +3) Naive forecast would estimate Period 3 to have a value of 56 (53+3) Moving Average – technique that averages a number of recent actual values as forecast for current period; it is updated as new values become available Ex. Calculate a three-period moving average forecast for the demand for a product, given its demand for the last five periods: Period Demand 1 42 2 40 3 43 4 40 5 41 F6= 43 + 40 + 41 = 41.33 3 Weighted Moving Average – a variation of moving average where most recent values in the time series are given larger weight in calculating a forecast Period Demand Weight 1 42 - 2 40 0.1 3 43 0.2 4 40 0.3 5 41 0.4 F6= 0.1(40) + 0.2(43) + 0.3(40) + 0.4(41) = 41.0 The advantage of a weighted moving average over a simple moving average is that the weighted moving average is more reflective of the most recent observations. Exponential Smoothing – weighted averaging method based on previous forecast plus a percentage of the different between that forecast and the previous actual value Forecast = Previous forecast + a(Previous actual – Previous forecast) Suppose that the previous forecast was 42 units, previous actual demand was 40 units and a = 0.1. The new forecast would be computed as follows: Ft= 42 + 0.1(40-42) = 41.8 Then if actual demand turns out to be 43, the next forecast would be: Ft= 41.8 + 0.1(43-41.8) = 41.92 Adaptive Exponential Smoothing – a version of exponential smoothing where the smoothing constant is automatically modified in order to prevent large forecast errors from occurring Linear Trend Equation – y =ta + bt, used to develop forecasts when linear trend is present Consider the trend t = 45 + 5t. The intercept is 45 and the slope is 5. On average, the value of forecast will increase by 5 units for each time period. If t=10, the forecast t = 45 + 5(10) = 95 units. Refer to the example on the next page. Cell phone sales of a company over the last 10 weeks are shown (first two columns). Determine the equation of the linear trend and predict the sales of cell phones for weeks 11 and 12. The coefficients of the line, a and b, can be computed using the following equations: 2 Week Unit ty t (t) Sales (y) 1 700 700 1 2 724 1448 4 3 720 2160 9 4 728 2912 16 5 740 3700 25 6 742 4452 36 7 758 5306 49 8 750 6000 64 9 770 6930 81 10 775 7750 100 55 7407 41358 385 b = 10(41358) – 55(7407) = 6195 = 7.51 10(385) – 55(55) 825 a = 7407 – 7.51(55) = 699.4 10 Therefore, the trend line is t = 699.4 + 7.51t F11= 699.4 + 7.51(11) = 782.01 F12= 699.4 + 7.51(12) = 789.52 Trend-Adjusting Exponential Smoothing – variation of exponential smoothing used when a time series exhibits trend See pages 71-72 for formulas and examples. Seasonal Variations – regularly repeating wavelike movements in series values that can be tied to recurring events, weather or calendar Ex. Q1= 1.2, Q 2 1.1, Q =30.75, Q = 4.95. The trend is projected using equation yt= 124 + 7.5t The trend values at t = 15 and t = 16 are: y15 = 124 + 7.5(15) = 236.5 y15 = 124 + 7.5(16) = 244.0 Multiplying the trend value by the appropriate quarter relative yields a forecast that includes both trend and seasonality. F15= 236.5(1.10) = 260.15 F16= 244.0(0.75) = 183.00 Centered Moving Average (CMA) – a moving average positioned at the centre of the data that were used to compute it A three period average is positioned at period 2. See pages 76 and 77 for examples. Predictor Variables – variables that can be used to predict values of the variable of interest Regression – technique for fitting a line to a set of points Least Squares Line – minimizes the sum of the squared deviations around the line See pages 80-82 for examples of simple linear regression. Correlation Coefficient – a measure of the strength of relationship between two variables See page 83 for the equation to compute the correlation coefficient. Forecast Error – difference between the actual value and the forecast value for a given period Forecast Error = Actual Value – Forecast Value et= A t F t If actual demand for a month is 100 units and forecast demand was 90 units the forecast was too low and the forecast error is 100 - 90 = +10. Mean Absolute Deviation (MAD) – the average of absolute value of forecast errors Mean Squared Error (MSE) – the average of square of forecast errors Mean Absolute Percent Error (MAPE) – the average absolute percent forecast error MAD = MSE = MAPE = Bias – the sum of forecast errors It is necessary to monitor forecast errors to ensure that the forecasting process is performing adequately and remains accurate enough. Control Chart for Forecast Errors – a time series plot of forecast errors that has limits for individual forecast errors If forecast errors are not randomly distributed around a mean of zero (no bias) or the distribution of forecast errors isn’t normal, corrective action is needed. An alternative measure to control the forecasting performance is tracking signal. Tracking Signal – a measure used to control the forecasting process: sum of forecast errors divided by mean absolute forecast error Chapter 4: Product Design Product Design – determining the form and function of the product Reverse Engineering – dismantling a competitor’s product to discover what it is composed of and how the components work, searching for own-product improvements Research and Development – lab scientists and engineers involved in creative work on a systematic basis to increase knowledge directed toward product and process innovation Life Cycle – incubation, growth, maturity, saturation and decline Incubation - item is introduced Growth - design improvements create a more reliable and less costly product Maturity - demand levels off, few design changes Saturation - decline in demand Decline - in decline, companies attempt to prolong the useful life of a product by improving its reliability, reducing costs of producing it, or redesigning it Standardization – extent to which there is absence of variety in a part or product Mass Customization – producing basically standardized goods or services but incorporating some degree of customization Delayed Differentiation – producing, but not quite completing, a product until customer preferences are known Modular Design – parts are grouped into modules that are easily replaced or interchanged - the product is composed of a number of modules or components instead of a collection of individual parts Reliability – the ability of a product, part, or system to perform its intended function under normal conditions Failure – situation in which a product, part, or system does not perform as intended Robust Design – design that can function over a broad range of conditions Product Liability – a manufacturer is liable for any injuries or damages caused by a faulty product Remanufacturing – refurbishing used products by replacing worn-out or defective components Design for Disassembly – design so that used products can be easily taken apart Recycling – recovering materials for future use Concurrent Engineering – bringing engineering design, manufacturing engineers, and staff from marketing, manufacturing and purchasing together early in the design phase Computer-Aided-Design (CAD) – product design using computer graphics Design For Manufacturing (DFM) – takes into account the organization’s manufacturing capabilities when designing a product Design For Assembly (DFA) – focuses on reducing the number of parts in a product and on assembly methods and sequence Quality Function Deployment (QFD) – a structured approach that integrates the “voice of the customer” into product design Chapter 5: Strategic Capacity Planning Capacity – the upper limit on the workload that an operating unit can handle - capacity is also measured as maximum production rate Strategic Capacity Planning – systematic
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