PLANNING FOR PRODUCTION

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1 PLANNING FOR PRODUCTION Forecasting Forecasting is the first major activity in the planning, involving careful study of past data and present scenario to estimate the occurence, timing or magnitude of future events. It provides input to the planning and scheduling process. As defined by American Marketing Association "An estimate of sales in physical units (or monetary value) for a specified future period under proposed marketing plan or programme and under the assumed set of economic and other forces outside the organisation for which the forecast is made." Benefits Effective handling of uncertainty Balanced work load Minimisation in the fluctuations of production Better use of production facilities Better material management Better utilization of capital & resources Better customer service Better design of facilities and production system Forecasting and Prediction Forecasting Prediction Objective Subjective Scientific Intuitive Free from personal bias & preferences Governed by personal bias & preferences Reproducible i.e. everytime same result would be obtained by any particular technique. Non-Reproducible Error analysis is possible Error analysis is not possible Forecasting Types Long Range : forecast consists of time period of more than years. Applicable in New Product Planning Plant Location Capital Planning Medium Range : forecast generally consists of time period between to years. Applicable in Production Planning Inventory Planning Sales Planning Short Range : forecast generally consists of time period between hour to year. Applicable in Loading & Scheduling Machine Maintenance Purchasing

2 Forecasting Error It is almost impossible to obtain an exactly right forecast every time. Therefore, some error in forecasted value and actual value is quite common. Measures of Forecasting Error. MAD (Mean Absolute Deviation) : This is calculated as the average of absolute value of difference between actual and forecasted value. n where, Dt = Actual value of demand for period t Ft = Forecasted demand for period t n = number of periods considered for calculating the error Dt - Ft t= MAD = n. MSE (Mean Sum of Square Error) : The average of square of all errors in the forecast is termed as MSE. n where, Dt = Actual value of demand for period t Ft = Forecasted demand for period t n = number of periods considered for calculating the error ( Dt - Ft ) t= MSE = n. BIAS : Bias is a measure of over-estimation or under-estimation. A positive bias indicates under-estimation while a negative bias indicates over-estimation. n where, Dt = Actual value of demand for period t Ft = Forecasted demand for period t n = number of periods considered for calculating the error ( Dt - Ft ) BIAS = t= n Forecasting Techniques Qualitative Models Delphi Method Quantitative Models Time Series Models Causal Models Sales Force Composite Consumer Panel Survey/ Market Research Moving Averages Exponential Smoothing Historical Estimate Trend Projection Simple Regression Multiple Regression

3 Historical Estimate It is used when the new product or new technology is strongly similar to an established product whose demand data is known. This approach is effective for medium to long range forecast and it is quiet cost effective. Estimation by Salesman Salesforce is a team that is closest to the customer. Their estimates are compiled to assess the future demand. e.g. In pharmaceutical market, the estimates given by medical representatives of all territories are oftenly used to determine the sales forcast of a particular machine. Used for short range forecast. Delphi Technique In Delphi method, a panel of outside experts are identified. They are given a series of structured questionnaires. The answers of each questionnaire are used as input for the design of the next questionnaire. In this way, after few rounds of questionnaires, the final forecast is derived. Delphi is used for long range forecast. It is generally used for new product demand, technological forecast for new technology, changes in society etc. Market Research In Market research, a survey instrument is generally used to gather data regarding the nature of consumption. The details about various factors which influence the demand like location, buyer occupation, prices quantity, quality, consumer income etc. are collected and the factors are related to get the forecast. It is generally used for short or medium rage of forecasting. Moving Average It is a simple statistical method to extrapolate ans establish trend of past sales. This method uses a past data and calculates a rolling average for a constant period. At each period fresh average is computed at the end of each period by adding the demand of most recent period and deleting the data of the old period since the data in this method changes from period to period. Larger the period of moving average, the greater is the smoothing effect. Moving Average = Sum of demands for periods chosen number of periods t Ai Ft+ = where i=t-n+ n Ft+ = forecast for period t + n = number of periods used to calculate moving average, and Ai = actual demand in period i. Weighted Moving Average In moving average, all periods are equally weighted. Generally the forecaster wants to attach more weightage to the most recent data or to the most important data. The sum of these weights should be equal to one. This is a better method as compared to moving average as it gives a better forecasting by attaching more weightage to the more important data. t wiai Ft+ = i=t-n+ where Ft+ = forecast for period t + n = number of periods used in determining moving average Ai = actual demand in period i, and wi = weight assigned to period i (with wi = ).

4 Exponential Smoothing In exponential smoothing, demand for the most recent data is given more weightage and the weights assigned to older periods decrease exponentially. Thus exponential forecasting ensures that the forecast made by this method keeps pace with changing business trend. Ft+ = Ft + where [At - Ft) Ft+ = forecast for period t + Ft = forecast for period t At = actual demand for period t, and = smoothing constant (0 ). Trend - Adjusted Exponential Smoothing In exponential smoothing, demand for the most recent data is given more weightage and the weights assigned to older periods decrease exponentially. Thus exponential forecasting ensures that the forecast made by this method keeps pace with changing business trend. Ft = At + ( - ) (Ft- + Tt-) Tt = (Ft - Ft-) + ( - ) Tt- and the trend-adjusted forecast, TAFt + m = Ft + m Tt where Ft = exponentially smoothed average in period t At = actual demand in period t Tt = exponentially smoothed trend in period t = smoothing constant (0 ) = smoothing constant for trend (0 ).

5 Q One of the product groups of a manufacturer of office furniture is desks. The number of desks sold during the past 0 years is as follows: Year Number of Desks Year Number of Desks For production planning purposes, annual sales are estimated for this product group and then broken down by type of desk. What would these annual group forecasts have been for year through with each of the following techniques? i) An unweighted four year moving average approach ii) A weighted four year moving average approach in which a weight of 0. was assigned to first year; 0. to the second year, 0. to the third year and 0. to the fourth iii) An exponential smoothing approach in which a smoothing factor of 0.0 was used and in which the weighted four year moving average was used as the forecast for year. Sol (i) Year Demand for the year Four Year moving total Four Year average moving 0 0/ = 0 0 0/ =. / = / =. / =. / = 0. / =. The moving average for the th, th, th and 0th year is.. Thus the forecast for th year is 0. (ii) Year Demand for the year Four Year weighted moving total Four Year average moving x.+0x.+00x.+x. 0 0x.+00x.+x.+x.. 00x.+x.+x.+0x.. x.+x.+0x.+x. 00 x.+0x.+x.+x.. 0x.+x.+x.+x. 0. x.+x.+x.+0x. 0. The moving average for the th, th, th and 0th year is 0.. Thus the forecast for th year is 0.

6 (iii) Using the relation where, Ft = Ft- + [Dt- - Ft-) Ft is the forecast for the current or year t Ft- is the forecast for the previous or year t- is smoothing factor Dt- is the actual demand for the previous or year t- The weighted four year moving average for th year from previous table comes out to be 0 and actual demand for th year is, is given as 0.0. Substituting these values F = ( - 0) = 0. or 0 i.e. forecast for the th year = 0 Now, forecast for the th year can be calculated using forecast for th year as 0 and actual demand for th year given as 0. F = (0-0) =. or 0 Similarly, F = ( - 0) =. or F = ( - ) =. or F0 = ( - ) =. or F = (0 - ) =. or

7 Regression Regression is an estimation of the dependent variable, say Y, from the independent variables, say X, X,... Xn. where a0,a,a... an are partial regression coefficients. Y = a0 + ax+ ax anxn Normal equations for finding coefficients of regression consisting of two independent variables: Y = a0 N + a X+ a X Y X = a0 X + a X + a X X Y X = a0 X + a X X+ a X Question: The number of patients visiting a hospital appear to depend upon (a) the facilities available at the hospital, (b) the fees charged by the hospital for tis services. Factors are measured by score on 0 to 0 scale. Hospital believes there is a direct and linear relationship between number of patients and these factors. Data collected on various hospitals in the metropolis are: Hospital No. 0 Facilities available (score) 0 0 Fees (score) Average Number of patients (per month, 000).. Guideline for Solution: Hospital No. Facilities available Fees 0 N=0 X 0 0 X Normal equations are: Average Number of patients Y square (X) square (X) Y.X = 0a0 + a + a = a0 + a + 0a = a0 + 0a + a Solve equations to find coefficients. Insert coefficients into following equation: Y = a0 + ax+ ax Y.X 0 X.X 0 0 0

8 MRP INTRODUCTION MRP stands for material requirement planning. It is a computer based system that takes master production schedule (MPS) to explode it into required amount of raw materials, parts, sub-assemblies, and assemblies needed in each of the planning horizon, and then reducing these material requirements to account for materials that are in inventory or on order and finally developing a schedule of order for purchased materials and produced parts over the planning horizon. In simple terms American Production and Control Society (APICS) defines it : "MRP constitutes a set of techniques that use bill of material, inventory data, and the master production schedule to calculate requirements for materials." -APICS Dictionary The core of MRP is its relationship with bill of materials and use of MRP records to calculate the time-phased release of orders for manufacturing, planning and control (MPC) system. TERMS USED IN MATERIAL REQUIREMENTS PLANNING Bills of material file: It is a file containing the bills of material for all end items. It contains listing of all raw materials, parts, sub-assemblies, and assemblies that go into an end item. The amount of each component that is'required to produce one end item is included. Bucket: It is the principal unit of time measurement in MRP systems. It refers to a particular period of time in the planning horizon. Capacity requirements planning: It is the process of reconciling the master production schedule to the labour and machine capacities of the production departments over the planning horizon. Dependent demand: It is the demand for a raw material, part, or other lower-level component that is dependent on the demand for the end item into which the component goes. It is a major pre-requisite of MRP system. End item: It is generally a product, service part, or any other output that has a demand from customers, distributors, or other departments. It is independent of the demands for other components or other end items. Gross rcquirements: These are the total requirements for a particular material, without considering any availability of the material in inventory or scheduled receipts. Independent demand: It is the demand for a material that is independent of the demands for other materials. Inventory status file: It contains material on hand or on order, planned orders, planned order release, lot sizes, safety stock levels, lead times costs and supplies. Lumpy demand: It is the demand for a material that appears as an irregular period-to-period pattern. Master production schedue (MPS): lt is the schedule, which shows the number and timing of all end items to be produced over a planning horizon. Net requirement: It is the material that must be added from production or purchasing. It is known by subtracting material available from gross requirements. Offsetting for lead time: It is the number of period between the requirement and the release in the offset and is equal to the lead time. On-hand inventory: It is the amount of a material actually present in inventory. Planned order receipt: It is the quantity of material to be received in any time period of the planning horizon. Planned order release: It is the material to be ordered in each time period of the planning horizon. Planning horizon-the number of period included in the MPS, MRP, and other production planning. Safety stock: It means quantity of material held in inventory that is dedicated to be used in emergency shortages, which may be due to uncertain demand or lead times. Service parts: It is the materials demanded as end item when ordered by service centers for repairing some end items.

9 Independent Demand Dependent Demand Product demand, unrelated to demand for other items. Product demand, related to demand for other items as item is component of other product. Example : End product, spare-parts Example : Raw material, sub assembly, workin-process inventory Calculations, such as MRP is needed to know its value. Usually known by forecast. Delivery schedule determined by customer requirement (by order or forecast). Delivery schedule is determined by its leadtime plus due date for end product. Continuous Demand Lumpy Demand Demand for an item is at continuous and gradual rate. Demand is sudden or in large quantity / increments so as to make a certain batch of final product. Order point system (like EOQ, in conventional inventory management) is the useful way to handle. Many mathematical models are available for different situation, such as EOQ with shortages, EOQ with discount, etc. MRP calculations are useful way to handle lumpy demand situation. Calculation based on simple MRP logic is sufficient. INPUTS TO MRP MRP uses master-production schedule (MPS) and converts it into a detailed schedule for raw material and individual component/sub-assembly. Therefore, MPS is the starting input to MRP. In addition to MPS, MRP also uses the product structure, which is derived from bill-of-material file. Another input to MRP is the status record of inventory, which is derived from inventory record file. This information pertains to quantity of inventory which is yet not consumed till the date of ordering. INPUT TO MRP I. Master Production Schedule (MPS) and other order data not contained in MPS. Bill of Material (BOM) file defining the product structure. Inventory status file Master Production Schedule (MPS) It is a list of items, indicating end products to be produced. This contains item name (and code), quantity to be produced, and timings for completing the production. MPS is based on the accurate estimations of product demand, which is available from sales forecast figure for the given period. Another input to MPS is a realistic assessment of the production capacity, which determines whether the production of the forecasted item is possible or not. Bill of Material (BOM) File It provides a list of materials and their quantities required to produce the end item. It is also called as product structure file or indented bill of material. It contains the list of finished products, material needed for each finished product in units, assembly structure, sub-assemblies, parts, and material. BOM file also provides relationship of each end product with sub-assemblies and raw material. BOM file is revised every time there is a change in product design or specification.

10 Product # A Sub-assembly # Component X Sub-assembly # Component Y Component X Component Z Sub-assembly # Component Y Component Z Component Y An example of BOM structure for product # A, which has three sub-assemblies : #, # and #, is shown above. These three sub-assemblies are constituted from three components X, Y and Z. The BOM structure shown above indicates that each product #A needs two components X, three components Y and two components Z. Inventory Status File It provides a computerized list of recojds_pf each.material, physically held in the system. There will be only one inventory status for individual material, even if it is used at different level of production or in different end products. It indicates : (i) material code (ii) material name (iii) inventory on-hand (physically available) (iv) material on-order (ordered but yet to arrive) (v) customer order for the item The updating of inventory status file should be regular and frequent. This requires entering following information for updating : (i) Receipt of material (add) (ii) Disbursement of inventory (subtract) (iii) Scrap reported for the material (subtract) (iv) Wastages, pilferage and theft, if any (subtract) (v) Planned orders (add) (vi) Order release (subtract). This file also contains standing informations, such as:. (i) Lot size (ii) Lead times (iii) Safety stock level (iv) Scrap-rate Since the order for service department, or individual customer for a particular part (and not the end product) for servicing is not entered in MPS, therefore, inventory status file is fed with this information separately.

11 Service Parts Requirements Master Production Schedule Inventory Status File MRP Computer Program Engineering Changes MRP System Bill of Materials Changes to Planned Orders Planned Order Schedule Primary Outputs Inventory Transaction Data Planning Reports Performance Reports Exception Reports Secondary Outputs Structure of MRP system MRP Output Customer Order MRP Inputs Sales Forecast

12 HOW MRP WORKS The logics under which MRP works are simple to understand. Following steps are included: Step : Bucketing With the information contained in MPS, it is known which end product is needed : (a) at what point of time, and (b) in how much quantity. MRP starts with consolidating each period requirements for different end products. In MRP we call different time periods as buckets. Step : Add Service (Spare) Parts, which are not included in MPS There may be a need to produce few components, such as spare parts for service department. These service parts don't find a place in MPS. But, since these parts are ultimately needed, we have to produce them. Therefore, MPS adds the service parts demand to demands, mentioned in MPS record. Total Production Requirement for any component in any period = Demand figure in MPS record + service part requirement during that period Step : Part Explosion Each item in MPS and service inventory record are exploded into their constituent material or basic component requirement. For example, a car needs four tyres. Now, for a demand of 0,000 cars, it may be exploded into 0,000 demands for tyres. Similarly, we explode the final product for its constituent components/raw material. The important point, which we must note, is the final figure after explosion comes from combining MPS (which gives how much is needed during a given period) and BOM file (which gives product structure, i.e., for each final product, how many sub-assemblies/components/raw material needed). Step : Offsetting Offsetting means displacing requirement by a period equal to the lead-time of the product. The purpose of offsetting is to bring the requirement to an actual date when order is to be placed for each component/raw-materials. Step : Aggregation This involves finding the gross requirement for each component/raw materials. This is done by adding the requirement for any component in a given slot of time period. For example, if a component (say, tyre) is needed by two models of scooters A and B, the lead time for tyres (i.e., time between placing the order and receipt of tyre from its supplier) is weeks. The demand for car A is 00 and car B is 00 in I Oth week. Each car needs four tyres. Let us examine the process of aggregation. Due to backward offsetting by lead time, the demand of tyres is 00x for car A and 00x for car B. Thus, total is equal to 00 tyres. This has been aggregated. The offset demand is in weeks (lead time) ahead of 0th week, i.e., on th week. Step : Netting This involves the modification of aggregated (or gross) requirement by subtracting the amount of same material in stock (on-hand inventory) and stock on-order during that period. On-hand inventory during a period is available in inventory status file. On-order inventory is due to the requirements by spare and service department. On-hand inventory is not included in MPS. Therefore production, over and above requirements derived from MPS, would be needed. To accommodate the safety-stock (to meet contingency and uncertainty in forecasted demand), we also subtract it from gross-requirement. If in case net requirement is positive (i.e., greater than zero), order for material must be placed in that time period. Step : Procurement Schedule The requirement is now advanced by a lead time for final assembly. The process is same as offsetting. This leadtime pertains to production process lead time, while lead time in Step was due to supplier lead time. Step : Lot Sizing This is used to consolidate the requirements in pre-specified lot sizes, so that "economic order quantity" may be ordered. Economic order quantity (EOQ) concept is applied to MRP output pertaining to the order-quantity for each bucket (time-period).

13 CLOSED-LOOP MRP The common MRP (open loop) discussed so far answers questions like : what and when an item is to be produced or ordered. It is well linked to MPS. However, this system is static in the sense that problems with production machines, quality, labour, late delivery, etc., make the output of the MRP more or less irrelevant. Manual updating is not only difficult and time consuming, it is error-prone also. Closed-loop MRP is designed to handle this problem of updating. It is done by interfacing the purchase and production activities control modules with MRP-module. Dynamic updating of order-status is done by purchasing interface. This dynamically generates updated order-status from which new planned order releases. In case of updates, new schedule is generated. Shop-floor interlace updates MRP production status by collecting daily production and operator time-sheet data. These feedbacks to MRP constitute closed-loop MRP MPS, MRP and Capacity Requirement Planning Production Process Order Review and Release Order Control Detailed and Priority Scheduling Detailed Production Planning and Manufacturing Manufacturing Operation Yes Production Monitoring and Data Collection Production Monitoring and Feedback In Control? No Problem Correctable? Yes No Order Control? Yes Order Disposal Order Disposition Feedback for Evaluation Closed-loop MRP Completed Orders Rework Scrap

14 Manufacturing Resource Planning (MRP-II) Business Planning Market Demand Finance Marketing Production Plan Manufacturing Adjust Production Plan Rough-cut Capacity Planning Yes Problem? No Adjust MPS Master Production Schedule (MPS) MRP Adjust CRP Capacity Requirement Planning (CRP) No Realistic? Yes Requirement Schedules Execute Capacity Plans Execute Material Plans MRP II System

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