Wednesday, December 23, 2009
Given below the figure which contains overall process involved in the production planning.
So far we have seen Demand Management, Aggregate Production Planning(APP), Master Production schedule(MPS) and Material Requirement Plan(MRP) in our earlier blogs. We will not focus our attention to Production Activity Control (PAC) which is hard core production function. However we need to know the fundamentals of various capacity Planning techniques used in the production plan and its relevance.
A problem commonly encountered in operating MRP systems is the existence of an overstated MPS. An overstated master production schedule is one that orders more production to be performed (released) than the expected production capacity. For example in Maruti Suzuki car plant, rough cut capacity plan states that a worker can paint 2 Alto model cars in a day (8 Hours), there are 20 workers are allotted to do painting job per shift and there are two shifts per day(i.e., totally 16 Hrs production). As per rough cut capacity plan the company can paint roughly 80 Alto model cars per day (i.e., 20 workers, 2 shift, 2 cars/worker). Let us assume the Master production schedule without checking the rough cut capacity plan has agreed to paint 100 units of Alto models per day. In such case 100 units of Alto model car will be waiting in the production line to be painted on a particular day but the company can paint only 80 units as per the rough capacity plan and release them for next activity. An overstated MPS causes raw materials and WIP inventories to increase because more materials are purchased and released to the shop (i.e., 100 units of Alto model are given to paint work shop) than are completed and shipped (i.e., 80 units of Alto models are completed on that day as per capacity). It also causes a buildup of queues on the shop floor (i.e., balance 20 units of Alto model need to be painted and released to the next job). Since jobs have to wait to be processed, actual lead times increase, causing ship dates to be missed (Maruti factory expected 100 units of painted Alto model to be released on particular day but actually ending up with releasing 80 units). Thus, overstated master production schedules lead to missed due dates and other problems. Otherwise the company can think of going for additional man power or extra shift to meet the demand. Validating the MPS with respect to capacity is an extremely important step in MRP. This validation exercise has been termed rough cut capacity planning (RCCP).
Material requirements planning (MRP) uses a master production schedule (MPS) of end items to determine the quantity and timing of component part production. MRP system assume that capacity available is infinite. It assumes that sufficient capacity is available to produce components at the time they're needed. But in reality the capacity (e.g., machine or worker production capacity) is finite. Hence the MRP system should be finalized after checking against the capacity requirement plan.
Given below the figure which explain the overall relationship exist between Demand and Production (supply) planning.
I have covered the important aspects of Production Planning related to SCM in this blog. I would like to invite query / comments from the users. In my next blog I intend to cover Inventory Management concepts.
I wish the readers
"MERRY X-MAS AND HAPPY & PROSPEROUS NEW YEAR 2010"
Monday, December 21, 2009
Techniques for Aggregate Planning
Techniques for aggregate planning range from informal trial-and-error approaches, which usually utilize simple tables or graphs, to more advanced mathematical techniques like Transportation method, Linear Decision Rule (LDR), etc. The general procedure consists of the following steps:
1. Determine demand for each period and capacity for each period. This capacity should match demand, which means it may require the inclusion of overtime or subcontracting.
2. Identify company, departmental, or union policies that are pertinent. For example, maintaining a certain safety stock level, maintaining a reasonably stable workforce, backorder policies, overtime policies, inventory level policies, and other less explicit rules such as the nature of employment with the individual industry, the possibility of a bad image, and the loss of goodwill.
3. Determine unit costs for units produced. These costs typically include the basic production costs. The production cost computed based on fixed and variable costs as well as direct and indirect labor costs. Also included other costs like set up costs which associated with making changes in capacity. Inventory holding costs, so as storage, insurance, taxes, spoilage, and obsolescence costs. Finally, backorder costs must be computed. While difficult to measure, this generally includes expediting costs, loss of customer goodwill, and revenue loss from cancelled orders.
4. Develop alternative plans for Chase and Level strategy and compute the cost for each method.
5. If satisfactory plans emerge, select the one that best satisfies objectives. Frequently, this is the plan with the least cost.
Aggregate Planning Method
• Graphical & Chart Technique
o Trial and Error approach
• Mathematical Technique
o Transportation Method
o Linear Decision Rule
o Management Coefficients Model
In this blog we will focus our attention to graphical & Chart technique and general models used in computing the overall cost under chase and level strategy, to understand the basis concept.
Let us take an example of Sony Ericson company mobile and using monthly demand data to arrive graphical model and compute low production cost on chase and level strategy. The data is given below.
Based on the above data we give below the graphical model by plotting Monthwise cumulative demand data and monthwise cumulative average demand.
The graphical models are heuristic in nature and not give optimum solution. Hence we will see now how to compute low cost production basis chase and level strategy and compare the two costs to take decision.
Given below the production cost computation based on Chase (demand) strategy model by varying work force and output rate.
Now we will learn about the production cost computation based on Level startegy model by keeing constant work force and output rate.
Now the user can compare the total cost computed by using Chasing and Level startegy and decide on model to be adopted. However as explained earlier we need to think twice before manipulating work force as it will bring bad reputation to the company and also we may not get skilled labour as when require.
I trust this will give you foundation with regards to Aggregate Production Planning. In this blog I am not explaining Transportation model. Based on the users request the transportation model will be covered in the subsequent blog.
Thursday, December 17, 2009
Aggregate Production Plan (APP) is the exercise of developing approximate schedule of the overall operation plan for a company which specifies how resources (total number of workers, hours of machine time, or tons of raw materials) of the company are going to be committed over the next six months to one year for a given demand forecast.
Objectives of Aggregate Production Planning
• Minimize Costs/Maximize Profits
• Maximize Customer Service
• Minimize Inventory Investment
• Minimize Changes in Production Rates (Setup cost)
• Minimize Changes in Workforce Levels
• Maximize Utilization of Plant and Equipment
Let us understand the above definition through simple example. Hitachi company which manufacturing Window Air Conditioners with 0.75 Ton, 1 Ton, 1.5 Ton and 2 Ton models. During the year 2009 the total expected sales are 1 Lac pieces of all models put together in Indian Market. With aggressive Marketing plan the company expected to Sell 1.5 lac pieces (aggregation of all models) at product family level (Window AC) to customer during the year 2010. Also the company received an Institutional orders (firm order) of 10,000 pieces (all models) for the year 2010. Now the company need to produce totally 1,60,000 pieces of different models during the year 2010, i.e., 60,000 pieces extra over the current year production with the existing production facility (machines / labour force). During year 2009 the company produced 1 Lac units in 2 shifts (6AM – 1 PM and 2PM – 10 PM) with 300 workers in each shift. Since the ACs sales are driven by seasonality, the sales across the month during 2009 were not uniform. The sales were peak during summer and low during winter season. Please note that Aggregate Production Planning does not distinguish among sizes, colors, features etc.
By looking at the components of the APP definitions, as explained above, the following questions arise in our mind.
• Why Aggregate Plan and not SKU level Plan ?
• Why Approximate Plan and not exact Plan ?
• How the resources are going to be committed and its modus operandi?
Aggregate production plan (APP) is based on estimated / forecast volume, institutional firm orders and back orders. Back orders are the pending orders. As already seen in our blog (refer the characteristic of forecast) the forecast are always wrong and aggregate forecast are more accurate than SKU level forecast. Since the forecast volumes are estimated figures and hence the production plan based on forecast volume are also approximate plan and not exact plan. Aggregate forecast are more accurate than individual SKU level forecast. Even in the Hitachi company case, if you compare the individual SKU wise forecast for the year against the confirmed / actual sales volume there will always be variations. For one SKU the variation will be positive (i.e., the forecast volume are greater than actual sales and hence surplus stock) and another SKU of the same family group the variation will be negative (i.e., the actual volume are greater than forecast and hence back order). If you aggregate the individual SKUs of the same family group, the positive and negative variations will negate each other and the net result is less variation at family group level. The top management of the company who is responsible in strategic decision making is interested to know the company growth at aggregate level rather than individual SKU level.
In simple terms, aggregate planning is an attempt to balance production capacity and demand in such a way that costs are minimized. The term "aggregate" is used because planning at this level includes all resources "in the aggregate", for example, as a product line or family (not SKU level). Aggregate resources could be total number of workers, hours of machine time, or tons of raw materials. Aggregate units of output could include tons, liters etc. The Aggregate Production Planning Function is given below.
There are two pure planning strategies available to the aggregate planner: a Level strategy and a Chase strategy. Firms may choose to utilize one of the pure strategies in isolation, or they may opt for a strategy that combines the two.
A level strategy allows a firm to maintain a constant level of output and still meet demand. This is desirable from an employee relations standpoint. Negative results of the level strategy would include the cost of excess inventory, subcontracting or overtime costs, and backorder costs, which typically are the cost of expediting orders and the loss of customer goodwill.
2) Chase Strategy
A chase strategy implies matching demand and capacity period by period. This could result in a considerable amount of hiring, firing or laying off of employees; insecure and unhappy employees; increased inventory carrying costs; problems with labor unions; and erratic utilization of plant and equipment. It also implies a great deal of flexibility on the firm's part. The major advantage of a chase strategy is that it allows inventory to be held to the lowest level possible, and for some firms this is a considerable savings. Most firms embracing the just-in-time production concept utilize a chase strategy approach to aggregate planning.
Most firms find it advantageous to utilize a combination of the level and chase strategy. A combination strategy (sometimes called a hybrid or mixed strategy) can be found to better meet organizational goals and policies and achieve lower costs than either of the pure strategies used independently.
Given below the table which contains pros and cons of pure strategies against the peak and slack season.
Friday, November 20, 2009
As already seen in our earlier blog, the logic used in MRP computation are
1. Input from MPS, BOM, Inventory Status, Lead time
2. Part Explosion
3. Offset by lead time
4. Netting from gross by considering existing inventory
5. Lot sizing of net requirement for procurement
In the last session we have got all input data from MPS, BOM, Inventory status and lead time. Now we will explore how the logics are used.
Given below the chart 1 meant for Products level (General & Sports) data computation
Currently the cycle factory is having 10 units of General cycle and 20 units of Sport Cycle (finished products) with them i.e., on hand stocks. Now we can arrive Net Requirement by deducting on hand quantity from gross requirements. Hence the net requirement of General cycle on 7th has come down to 90 instead of 100. Similarly the net requirement of Sports cycle on 6th has come down to 180 instead of gross requirement 200. This step is known as Netting.
Let us assume on hand quantity of General cycle is 120 units instead of 10 units. Now the net requirement for general cycle on 7th is 0, as the on hand quantity 120 units is more than gross requirements of 100 units. At the end of 7th day the company still left out 20 units of General cycle without producing any General cycle. On 10th the company need to produce only 180 units against gross requirement of 200 units as they have 20 units of finished on hand.
Since the lead time for General Cycle (P1) is 2 days (refer lead time chart in my previous blog), cycle body from sub assembly 1 and wheel from sub assembly 2 should be made available 2 days (refer BOM Structure – General Cycle in my previous blog) earlier. In other words 90 unit of cycle body from sub assembly 1 and 90 units of wheel from sub assembly 2 should be made available on 5th to produce 90 units of General cycle finished product by 7th meant for dispatch. To produce 200 units of General cycle on 10th, 200 units of cycle body and wheel should be available on 8th due to 2 days lead time. In order to meet the net requirement timelines you need to release the planned order to subassembly 1 & 2 considering their manufacturing lead time. This process is called as offset by lead time.
Similarly the lead time for Sports Cycle (P2) is 3 days (refer lead time chart in my previous blog), cycle body from sub assembly 3 and wheel from sub assembly 4 should be made available 3 days (refer BOM Structure – Sports Cycle in my previous blog) earlier. In other words 180 unit of cycle body from sub assembly 3 and 180 units of wheel from sub assembly 4 should be made available on 3rd to produce 180 units of Sports cycle finished product by 6th meant for dispatch. To produce 500 units of Sports cycle on 9th, 500 units of cycle body and wheel should be available on 6th due to 3 days lead time.
So far we have considered the process at Product level (General and Sports Cycle). Now we need to look at sub assembly level requirements. For simplicity we need to consider only General cycle model i.e., sub assembly 1 & 2. If you understood the logic, you can apply this logic on any model.
Given below the chart 2 meant for sub assemblies 1 & 2 associated with General cycle product only.
Note if there is any schedule receipt quantity then the net requirement calculation become Gross Requirement - Schedule Receipt – On hand Quantity.
Since the lead time (refer lead time chart in my earlier blog) for sub assembly 1 is 2 days and for sub assembly is 1 day, the net requirement quantities of sub assembly 1 is offset (work backward) by 2 days. Similarly the net requirement quantities of sub assembly 2 is offset by 1 day.
Now we are moving to the final stage i.e., raw material computation. We are looking raw materials attached to sub assembly 2 i.e., Wheel (2 units), tyre/tube (2 units), pedal (2 units) and chain (1 unit). I would like you to refer BOM structure of General cycle in my earlier blog. In advertently I have not mentioned 1 unit against chain in the BOM structure of General cycle.
Given below the chart 3 meant for raw material level explosion associated with sub assembly 2 of General cycle product only.
Since we are considering raw materials for the sub assembly 2 only, the gross requirements for these raw materials are coming from Planned order release from sub assembly 2. However the gross requirement quantity are increased due to the number of units goes against each components. For example Wheel, Tyre/tube, Pedal require 2 units and chain 1 unit (refer BOM Structure), the gross requirements for these components also increased accordingly. If you notice Wheel, Tyre/tube, Pedal gross quantities are doubled as against the sub assembly 2 planned order release quantity due to 2 units of components are used as input. It is obvious cycle require 2 wheels, tyre/tube and pedals. Since 1 unit of cycle chain is required the gross quantity of chain remain same as sub assembly 2 planned order release quantity. This process is referred as Part Explosion.
The Net Requirements are computed after adjusting on hand quantity against gross requirements. The planned order release for these components are offset by ordering lead time of 5 days. The Purchase order against the suppliers are raised based on planned order release quantity of each components as per Planned order release period. Normally Purchase order quantity for components are raised against the supplier according to lot size. We will learn more about lot size in the Inventory Management session.
Now the question arise if two products General and sports cycle uses the same components (commonly used items) then the planned order release quantity for those components which are used by both products are consolidated and then Purchase order is raised to the supplier, provided Planned order release date is closely related. For example Tyre/tube raw materials are used in both General and Sports cycle model and hence one can consolidate the total requirements and raise indent to the suppliers. But Planned order release date for tyre/tube in respect of general and sports cycle vary widely, we cannot consolidate both items and place order to the suppliers. In this case we need to raise indent separately according to planned order release date.
I have explained MRP concepts with simple example. But in reality MRP is more complex and require lot of skill set to handle. With this we have completed MRP module and we will focus our attention to MPS, Aggregate Planning and Capacity Planning in our next blog.
Wednesday, November 18, 2009
Lead time is one of the basic input to MRP. MRP system is concerned with two types of Lead Time i.e., Ordering Lead time and Manufacturing Lead time. Ordering lead time deals with procurement of components. In our example Maruti company places order for 4000 units of tyres and tubes from Bridgestone company. Bridgestone takes 7 days to supply the tyres and tubes from the date of receiving purchase order from Maruti, the ordering lead time is 7 days.
There are certain components which are produced within the company and the process takes time. This refers as manufacturing lead time. In our example Maruti produces 1000 units of Alto model car. The doors of the car are manufactured in the Maruti plant itself. The company procure steel and make 4 doors according to the Alto model in their plant. This sub assembly process involves cutting steel sheet then make doors . This entire door making process takes some time and this referred as Manufacturing lead time. The manufacturing process will be carried out in lot batches.
Lead time are critical input to MRP system and if any inaccurate data will hamper the production schedule. Manufacturing lead time can be established by observing the process time on regular basis and keep update record periodically. But ordering lead time is the critical as it depends on our supplier. In our above example if Bridgestone company take 10 days to deliver 4000 units of tyres and tubes against the normal 7 days delivery time the production of Maruti Alto model will be held up for three days. Hence one has to exercise appropriate control over ordering lead time to run MRP system smoothly.
Now let us see MRP calculation with simple cycle manufacturing example. Let us take an Hero cycle company for example and assume that they are manufacturing only two models of cycle i.e., general, sports and try to understand the MRP computation method. Let us consider the inputs to MRP system.
Master Production Schedule (MPS) – It contains
a) What end products are to be produced ?
b) How many of each products ?
c) When the products are ready for dispatch ?
Given below the sample MPS format
The above format contain information like 200 units of sports cycle to be made available on 6th of the months and 500 units of sports cycle by 9th. Similarly 100 units of General cycle to be available on 7th and 200 units by 10th. The MPS gives direction to production department what are the products to be products with exact quantity by what period. Please note that time period could be day, week, fortnight etc.
Bill of Material (BOM) – Sample BOM structure is given below.
Sub assembly of cycle body require 1 unit of handle bar, cycle frame, seat as components. Whereas Sub assembly of wheel requires 2 units of wheels, tyre and tubes, pedals and 1 unit of chain as components. These components are procured from different suppliers and hence it has ordering lead time.
In case of Sports cycle Gear unit is the additional component in the sub assembly of cycle body.
One must remember any engineering changes affecting the product structure must be incorporated in to the BOM file. Since we have taken simple example for MRP computation, the BOM look so simple. If you take Maruti Alto BOM it will be so complex due to lot of sub assembly line and 1000 of components involved to make one unit.
Inventory Status : Now let us focus our attention to Initial Inventory status report for raw material Handle bar.
The company will have inventory status report for all components like gear, tyre & tubes etc. The information available in inventory file should be accurate otherwise it will affect the MRP and Production planning.
Lead time details are given below for manufacturing (assembly) and ordering (raw materials).
The above table require little bit of explanation and one may require to refer BOM structure of General and Sport cycles. The final product P1 to be assembled from sub assembly 1 & 2 and it take 2 days to produce General cycle. Similarly final product P2 to be assembled from sub assembly 3 & 4 and it take 3 days to produce Sports cycle.
Sub assembly 1 (S1) take 2 days to assemble general cycle frame from raw materials (R1, R2 & R3) and similarly sub assembly 2 (S2) take 1 day to assemble general cycle wheel from raw materials (R4, R5, R6, R7).
Sub assembly 3 (S3) take 2 days to assemble Sport cycle frame from raw materials (R8, R9 & R10,R11) and similarly sub assembly 4 (S4) take 2 days to assemble general cycle wheel from raw materials (R12, R13, R14, R15).
In the above example we are getting components and assembled the same for final product. In this model we are not manufacturing any thing. For example we are getting cycle frame from suppliers directly. Instead if we get steel tube from the suppliers and manufacture cycle frame separately by cutting steel tube, shape it and weld it in our factory this involves another sub routine process. Hence manufacturing lead time is eliminated in this process.
For simplicity we assume, Ordering lead time for all raw materials / components are 5 days. In other words if we place order for any component, the supplier take 5 days to deliver the product. In real scenario the ordering lead time for each component differ.
Now we got the all inputs (MPS, BOM, Inventory Status, Lead time). In the next session we will see how to compute MRP using the logic as explained in previous blog.
Thursday, November 12, 2009
In a manufacturing industry there are two types of inventory, i.e., Finished Goods (Saleable items) Inventory and Raw material Inventory. Finished Goods Inventory through which company earns revenue and Raw materials Inventory are components required to produce the desired finished goods. For example, in Maruti Suzuki company Zen, Esteem, Alto are finished goods and by producing and marketing these products the company earn revenue, whereas tyre, tube, Steel to make body, AC, glass for windows, seat, paint etc are raw materials which goes into product to make different models of car. To procure these raw materials the company incurs expenditure.
Let us understand the demand pattern of Finished Goods and Raw Materials. Finished Goods demand pattern are decided through forecast or estimation and to the extent of firm order. For example an Institution (government hospital) places an order of 1 Lac strips of paracetamol tablets on monthly basis for one year to a pharmaceutical company is considered as Firm order. The pharmaceutical company is legally bind to supply this tablet to institution on monthly basis, apart from regular sales to end consumers. Other than firm order the finished goods sales to consumers are decided by the forecast method. The estimate or forecast quantity are decided by the external factor like consumer behavior, price, government regulations, competition etc. For example Indian Government policy to curb tobacco sales has prompted ITC Company who is major player in cigarette business to divert their business to consumer durables and other business line. Since the demand pattern for finished goods are decided by external environment and difficult to exercise control over them, termed as “Independent Demand”.
In case of raw materials demand pattern can be derived from production plan and it is termed as “Dependent Demand”.
For example Maruti Suzuki company decided to produce 1000 units of Alto model cars (finished goods) during Dec’09 based on forecast. Even the Maruti company cannot assure that it can sell all 1000 units of Alto model produced during a given month due to external factor (independent demand) as explained above. If Hyundai company (competitor to Maruti) provide discount of Rs. 25,000 to their Santro model (similar to Maruti Alto model) then the demand for Alto model will go down and it may end up with selling 600 units during the given month leaving 400 units of Alto model cars as pipeline stocks (unsold inventory) to be sold in the subsequent months.
Whereas components (raw materials) for these 1000 units of Alto cars can be decided easily. We all knew a car has 4 wheels, tyres and tubes (assuming there is no stepny) and one can easily say the maruti company require 4000 units of wheels, tyres and tubes to produce 1000 units of Alto model apart from other components. As discussed in our earlier blog by using “Bill of Material (BOM)” meant for Maruti Alto model, we can derive the component requirements precisely for these 1000 units of Maruti Alto model. Hence raw materials demand pattern is considered as “Dependent Demand”. Raw material demand pattern is influenced by production plan.
BOM – Specifies the product structure. How many components /subassemblies required to make the final product and how are they related to each other. You can recall, BOM is similar to recipe in cooking process which contains required quantity of each ingredient (item / components) along with preparation (routing) method.
As explained in the previous blog, to prepare the Masala tea, the tea shop owner require ingredients (components) tea powder, milk, water, sugar and masala powder. The shop owner can procure all these ingredients from the shop to prepare masala tea. In case if he feel like to make masala powder by himself instead of getting the ready made powder from shop then he need to procure ingredients of masala and initiate another process of preparing the masala powder, other than masala tea prepartion process. Now the masala tea making process involve one more sub routine process i.e., to make masala powder. This sub routine process in production terminology termed as sub-assembly process.
Let us explain this through practical illustration. Dell computer manufacture who planned to produce 10,000 units of desk top. For this they can get all components like CPU, Hard disk, CD Drive, Monitor etc from different vendors and assemble the desktop. This process involves only assembling the different components in sequential steps (routing) to make desk tops. In case if they decide to produce monitor then it involve additional sub process ie they need to procure raw materials for monitor and assemble (sub assembly) it separately. The sub assembled monitor will go as input in main assembly to make desk top. We will learn more about BOM in a separate blog.
Now the question arise from where, you will get the quantity to be produced (i.e., 1000 units of Maruti Alto model). This data come Master Production Schedule (MPS) for end items. MPS will provide the details like how many units of final products you would like to have in different period. i.e., a) what end products to be produced b) how many of each products to be produced and c) when the products are ready for shipment. We will learn more about MPS in subsequent session.
So far we have seen MPS and BOM are necessary input to MRP. Along with MPS & BOM, existing inventory (opening stock) records of raw materials (not finished goods details) are needed, in order to place net requirement to the suppliers. For example Sony Ericson mobile company is planning to produce 50000 units of mobile with camera 4.0 mega pixel model. For this the company need to produce 50000 mobile camera unit with 4.0 mega pixel capacity. If the company is already having inventory of 10000 units of camera with 4.0 mega pixel, it need to produce only 40000 units only after adjusting the existing inventory. Assume that company over looked the existing inventory and produce 50000 units of camera with 4.0 mega pixel and the existing inventory will carry forward for future requirement. Due to rapid change in technology the demand for 4.0 mega pixel has reduced and demand for new model with 5.0 mega pixel started increasing. Now the company cannot produce and sell 4.0 mega pixel model due to poor demand and hence existing 10000 units become obsolete and the amount invested on these 4.0 mega pixel camera unit cannot be recovered. Hence raw material inventory record with correct details is very important input to MRP process.
Now we will explore more complex situation. So far we have discussed about Maruti Alto one particular model production plan for a given month. But in reality the company would like to produce 1000 units each of other models like Esteem, WagonR, Dezire, Zen for a given month. That means the total demand for all model cars are 5000 units. Let us assume tyres and tubes used in all models are same. In other words tyres and tubes commonly used items across all models. Now the question is how MRP is computed for commonly used items like tyres and tubes. We will learn this in the next session.
Let us see the logic used in MRP computation. They are
1. Input from MPS, BOM, Inventory Data, Lead time
2. Part Explosion
3. Offset by lead time
4. Netting from gross by considering existing inventory
5. Lot sizing of net requirement for procurement
We will learn lead time and logic and terminology used in MRP with practical example in the next blog.
Tuesday, September 15, 2009
• Long Term (Capacity Planning)
• Medium Term (Aggregate Planning)
• Short Term (Operational Planning)
Diagrammatic representation production planning overview is given below.
- Upto 5 Years ahead or more
- Capital Intensive in nature
- This deals with Strategic and business issue. In the long term we deal with those issue which help us to create demand for our products and generating sufficient revenue for the company.
- Reflect in process choice and equipment selection. Since selection of equipment and facilities require lot of investment and decision is irreversible, one should pay utmost care keeping in mind customer requirements.
Medium Term (Aggregate Planning)
- How demand can be met from existing facilities and resources. Here we are trying to utilizing our existing resources (manpower, machine, facilities etc) to satisfy the market demand
Short Term (operational Planning)
- In short term we monitoring the production activities on day to day basis and compare the output against the plan and take corrective action.
Master Production Schedule (MPS) - Is a statement of how many finished items are to be produced and when they are to be produced.
Material Requirement Planning (MRP) - System that uses net demand from the MPS and explodes it using the bill of materials (BOM).
Now we must understand the terminology related to Unit of Measure. This will help us to understand the production planning concept clearly.
- Items (SKU or Stock Keeping Unit) - The final products delivered to the downstream customers. The downstream customer is the one who intend to consume or use the product for personal use.
- Product Families – Group of items that share a common manufacturing setup cost. In other words those items that have similar production requirements. For example Complan drink sold in different flavor but they have similar production requirements.
Let us understand the production planning concept through example. Pepsico, India who is manufacturing soft drinks Pepsi, Miranda and other products. But we will focus our attention to Pepsi and Miranda alone to understand the production planning concept. Readers are requested to note that the Pepsi actual production planning may differ from the example given below.
Long term capacity Planning - Marketing does the yearly forecast at Product group like Pepsi and Miranda (not SKU level) and country (India) level for next 5 to 10 years based on expected yearly product growth rate. This aggregated yearly plan quantities are compared against the existing capacity planning in terms of facility, manpower, current production rate etc. If the existing capacity is not sufficient to meet long term (5 to 10 years) expected sales volume growth then the management will go for increasing the existing capacity by increasing manpower, deploying additional machines, having more shift in the plant. Even this does not meet the long term yearly demand then the management may feel like to go for additional plant which is capital incentive or looking for third party manufacture to produce their products under their brand name and sell it in the market. The reason for Long term capacity planning to meet increasing demand for existing products and also to launch new products in future to generate more revenue for the company.
Caution : Company used to go for higher capacity (plant, machinery etc) to meet future expected sales volume growth. There are company which constructed new plant expecting high sales volume growth for next few years (more than 5 years), is still meeting the current demand from the existing old plants as the demand has not gone up to the expected level. The new plant has become thorn in their flesh. Hence as an SCM professional, we must explore for alternative like third party manufacturing facilities while deciding capacity planning and put forth our case strongly with top management for approval
Medium term Aggregate Planning - Marketing does the monthly Rolling Forecast at SKU and Distribution centre level, for one year. One should note that one year is rolling period and not calendar year. For example if marketing is forecast during July’09, one year period means July’09 to June’10 which is called rolling forecast. The SKUs of Pepsi and Miranda are 100ml bottle, 200 ml can, Pet bottle size of 500ml, 1 liter and 2 liters. Let us assume they are having 6 distribution centre. Sales & Marketing and customers are concerned about pack wise product. But production department aggregate the quantity /Net demand (refer blog on Demand Planning – DRP) of all sizes pertaining to particular product ( Pepsi and Miranda separately) at country (India) level and arrive total quantity required to manufacture that particular product on monthly basis. If the monthly production rate is less than expected demand rate then the company will go for overtime, hiring more temporary workers etc. Due to unavoidable circumstances if the company is not able to increase the production capacity then the current production rate will be treated as expected demand rate. This process is termed as Aggregate Planning. During recent global spread of Swine Flu epidemic, most of the pharma company still not able to match production rate of tamiflu (drug) to the expected demand rate.
Short Term Planning (MPS & MRP) - Once the Aggregate planning quantity at Product family and country level is decided for a month then this quantity is disaggregated in to SKU and Distribution level as the plant need to produce products as per selling units. Now the production unit can sent the entire demand quantity in single lot to distribution centre. But the logistics team require the part quantities against the demand to be dispatched to distribution centers on different date in order to utilize the warehouse space and manpower efficiently. Hence the part quantity and schedule receipt date at distribution centre will be worked out and agreed upon by demand and supply planners. This process is called Master Production Schedule (MPS).
Now the Production unit is having the quantity to be produced and date of production as per distribution center requirement from MPS. But the product Pepsi drink require certain ingredients (raw materials) at certain quantity. The Pepsi company will be having BOM (refer my earlier blog) for each SKU. BOM will contain all raw materials and packing items the quantity required to produce one unit. According to BOM details the raw materials quantity are calculated and then purchase orders are placed to the suppliers based on lead time. Lead time is the time taken by the supplier to produce and deliver the raw materials to the Pepsi plant against the order date. This explosion from finished goods to the raw materials is called Material Requirement Plan (MRP).
Very Short Term Plan - Day to day production activities are monitored and the output are compared against the plan for better control.
For example perfume manufacturing plant importing their raw materials from abroad with lead time 4 months. The production lead time i.e., raw material conversion to finished product at plant takes one month. Consider, September being the current month and forecast quantity for September has already been decided and Purchase order already been placed in April itself. By placing order to the supplier by 15th April the plant will receive the stocks on 15th July due to 4 months lead time. However the finished goods will be produced by 15th August due to 1 month production lead time . The plant require few days to transport the finished goods to distribution centers located at various places . Through this planning process the plant can ensure that finished goods are connected to the distribution centre as per the Sales and Marketing requirements. Now one can understand how complex the production planning.
The above explanation is sufficient to understand the production planning concept.
We so far discuss about the manufacturing unit. This rise the question how the service industry planning their operation ? Given below diagram compare the components of production planning in respect of manufacturing and service industry.
Monday, September 14, 2009
Production Planning is a pre-production function intended to match the production capacity (machine, labor) with the estimated market demand (forecast) in the most feasible and cost efficient manner. Production Planning is based on the forecast in terms of the quantity and quality requirements of the product. These forecast /targeted volumes and quality levels are to be achieved within the budgeted cost allocated for producing the products. So it is essential to understand the importance of forecast in relation to production planning.
Production Planning is a managerial function which deals with the following important issues.
• Product selection and design - Selection of the most suitable product that fulfils the market demand and the design of the product to meet the customer requirements. This involves cross function like Sales and Marketing for product selection and R&D for design and finance for resource availability. SCM will play anchor role in getting the product and design.
• Process selection and Planning – Selection of the appropriate process that includes choosing the right kind of technology, equipment, machines, material handling system (conveyors, fork lift etc), mechanization and automation involved in the production of a product. Also perform efficient process planning by specifying different process involved in resource conversion and the order of occurrence in the process.
• Facility Location – Finding the appropriate location for establishing manufacturing plant in order to minimize the production cost and distribution cost. SCM will play main role in deciding facility location and we will explore more about this in latter session.
• Facility layout and material handling – This involves determining the optimal distance between different department like Welding, Grinding, Soldering , Assembling etc. This facilitates the transfer of material and processing of a product in a most efficient way through the shortest possible distance with minimal wastage of time.
• Capacity Planning – Is a process that helps in identifying the capacity of production unit to meet the changing customer demand for its product. We will learn more about capacity planning in latter session.
• Estimation – Involves determining the quantity to be produced (Sales forecast) and cost associated in manufacturing the quantity. Also helps in determining the machine capacity, manpower and raw material requirement to meet the production objective.
• Routing, Scheduling and Loading – We will see in latter session.
Production plan is dynamic in nature and always remains in fluid state as production plans may have to be changed in line with the change in circumstances. Production plan can change due to change in customer requirements, uncertainty in production line due to breakdown and raw material availability.
In the next session we will learn more about production planning Hierarchy and their time horizon with Unit of Measure.
Saturday, August 22, 2009
Before proceeding production planning terminology, we must understand how the Demand and Supply process are integrated. Demand & Supply process overview diagram is given below and users are requested to click on the diagram to view clearly.
Let us look in details about the Demand and Supply Process.
Demand Planning consist of Sales Forecast (explained in our earlier blogs) and Sales Orders are firm orders received from the customers (eg Institutional orders).
In manufacturing industry Supply (Production) encompass material management, procurement and production of finished goods.
Let me explain through simple example how demand and supply process are integrated. A tea shop owner sells on an average 100 cups of tea per day (expected sales) to the customers. He kept two workers (manpower), one to prepare tea and another to serve and wash the glass. He consumes roughly say three liters of milk, half kilo sugar and tea (raw materials) to make 100 cups of tea per day. He got two gas stoves with cylinder, boiler, tea filter and kettle to serve hot tea, two vessels to boil milk and two bottles to keep tea and sugar (equipments). Nearby factory owner approached him to serve 200 cups of tea in the morning and evening (400 cups per day) on working days to factory workers.
Now tea shop owner is expected to sell (forecast) of 100 cups of tea from regular customers and firm order of 400 cups of tea for the factory workers. From next week onwards he has to make 500 cups of tea instead of 100 cups of tea.
The tea shop owner will analyze, whether he can meet the increasing demand with the existing capacity of manpower (2 workers) and equipments (gas stove, boiler etc). This process is termed as capacity planning. This capacity planning will enable the tea shop owner to take decision either to go for additional capacity of manpower and equipment or not, to meet the expected demand. For simplicity we will assume that the existing capacity of manpower and equipments are sufficient to meet the increasing demand.
For 100 cups of tea per day he consumes three liters of milk, half kilo sugar and tea (raw materials). These items and quantity (recipe) become Bill of Material (BOM) to make 100 cups of tea. In order to meet demand of 500 cups of tea he has to procure 15 liters of milk, 2-1/2 Kg sugar and tea every day. This is simple mathematical calculation. This process is termed as Material Requirement Planning (MRP). MRP is the process of calculating raw material requirements basis BOM to meet the future demand.
Basis the calculation (MRP) the tea shop owner will procure the raw materials of tea, milk and sugar from a grocer shop and he negotiate the rate effectively as he purchase these items on daily basis.
We will add some more complexity in the existing process. Suppose the tea shop owner decided to serve masala tea to every body. To prepare masala tea he has to add one more ingredient (raw material) ie masala powder in that tea. The composition of the tea is changed due to masala powder. Let us assume he is using 20 grams of masala powder to prepare 100 cups of tea. The change in recipe (In Production Terminology this is termed as "Engineering Change") leads to change in Bill of Material (BOM). Once the BOM changes it automatically triggers changes in Material Requirement Plan. In this case the tea shop owner has to purchase 100grams of masala powder extra along with 15 liters of milk and 2-1/2 kgs of tea and sugar every day to prepare 500 cups of masala tea. We will see more complex method in the subsequent session.
The Material Management function in a factory handles raw material requirement planning (MRP), purchase, raw material issue and maintaining the records. Depending upon the organization structure of the company, the purchase department may function independently, come under Material Manager or reporting directly to Production Head.
In the next session we will learn in details about Production Planning and other concepts.
Wednesday, July 29, 2009
As stated earlier CDC act as a serving point to three Regional DCs. Hence, the Order Planned quantity (not Forecast Quantity or Net Requirement) of three regional DCs are aggregated to the CDC forecast quantity. For CDC we have assumed that the safety stock is nil. The Lot quantity for CDC is 300 units and lead time to get the stocks from CDC is 2 days.
We give below the DRP model used to compute the Order Planned quantity for CDC.
The Forecast Qty split is the aggregation of Order Planned Quantity of all three Regional DCs. Since the Safety stock is 0, Gross requirement is the same as Forecast Qty Split. Rest of the calculations are same, as explained in our earlier session.
- DRP is a scheduling and Stocking Algorithm. It replaces the forecasting mechanism above the base Inventory level.
- DRP does not determine the Lot Size and Safety stock. However Lot Size and Safety stocks are used as input to the DRP process
- DRP system can deal with market uncertainty through Safety stock and Lead time.
From the example, one can presume that DRP system is not that complicated as perceived. So far we are working under the assumption that there is no change in the demand (i.e., Forecast Quantity Split).
But in reality Market is more dynamic and hence the demand. What Happens when the actual demand differ from the forecast ? In such case should we follow the same DRP model as we worked out earlier. The DRP network in change in demand scenario is given below.
Option 1 – Manufacturing Plant should produce more to meet the Regional DC 1 requirement. Change in production schedule involves more cost and it is not viable option. Also the question arise what we are going to do with excess stock lying at Regional DC 2 ?
The Demand Planner is expected to take decisions on these issue in DRP system to meet the market demand. However he should be fully conversant with process mapping and IT architecture also. For example as per process if Regional DC 2 is expected to cater only Local DC3 & DC4 then Demand planner cannot transfer the stocks directly from Regional DC1 to Local DC1 & DC2. He has to transfer the stocks from Regional DC2 to Regional DC1. Regional DC1 will serve the Local DC1 and DC2 as per architecture.
So far we have discussed about Sales function modules like forecast and demand planning. In the next session we will focus our attention to Production function related topics like MRP (Material Requirement Planning) and MPS (Master Production Schedule), PPC (Production Planning & Control) etc.
Tuesday, July 28, 2009
We will explore through the following illustrations how time phasing and lead time impact the order planning and Net Requirement calculation. Let us assume we are having the following “Distribution Network System”.
In this model we have a manufacturing plant dispatch items to central Distribution Centre (CDC). CDC in turn send items to various Regional DCs (RDC). We will learn how net requirement is computed through various advanced models.
Before we proceed further, we understand few terminology related to “Inventory Management”, which we will be used in the Net Requirement calculation. We will learn more about “Inventory Management” concepts and calculations in our latter session shortly.
Lot Size or Lot Quantity - A “Lot or Batch” size is the quantity that company either produces or purchases at a time.
The number of units of a product or item (Lot Quantity) to be manufactured at each setup or purchased on each order so as to minimize the cost of purchasing or setup and the cost of holding the average inventory over a given period usually annual.
Safety Stock - Safety Stock (also called Buffer Stock) exists to counter uncertainties in supply and demand. Safety stock is defined as extra units of inventory carried as protection against possible stock outs. It is held when an organization cannot accurately predict demand and/or lead time for the product.
Lead Time - is the time from the moment the supplier receives an order to the moment it is shipped
In the above explained model CDC is only serving point and catering to the need of Regional DCs. Hence safety stocks are calculated at Regional DC level and not at Central DC level. Net Requirements and planned orders are calculated at Regional DC and getting rolled up to CDC. We give below Net Requirement and order Planned calculations of three regional warehouses for clear understanding.
Let us take Regional Distribution Centre -1 as an example and explain how the calculation has been performed. In this case the Safety stocks is 30 units, Lot Quantity i.e., the minimum quantity required at this distribution centre for a given order is 200 units and lead time i.e., time taken to deliver stocks from CDC is 2 days.
Opening Inventory - Previous day Closing Inventory will become today Opening Inventory
Since the lead time is two days as per our example the closing Inventory as on day 1 should be sufficient enough to cover next two days (day 2 and 3) gross requirements (Forecast quantity + Safety stocks). If the closing stocks is not sufficient then we need to plan order as per lot quantity.
In our above example the closing Inventory for DC 1 as on day 1 is 170 units. The Gross requirement for day 2 and day 3 is 190 units (100 + 90 units). There is shortfall of 20 units (closing inventory – 2 days cumulative gross requirements). Since the lead time is 2 days we need to consider next two days gross requirements as the stocks will get connect the DC after two days. If the lead time is 3 days (refer Regional Distribution centre 3 with lead time 3 days model) then we need to consider 3 days gross requirements. Even though the short fall quantity is 20 units only, we need to place order as per lot quantity i.e., 200 units. Order planned formula is given below
Planned Receipt – Order planned quantity received as per lead time. As per our example we have ordered 200 units on day 1 to meet cumulative gross requirements. Since the lead time is 2 days the stocks will be reaching DC on day 3 against the order planned on day.
Friday, July 17, 2009
DRP systems operate by breaking down the flow of finished goods from the manufacturing plant through the “Distribution Network” of warehouse and transportation modes. This is undertaken on a time-phased basis (in DRP terminology referred as time bucket) to ensure that the required goods flow through the distribution network system are available as and when required at right place, at the right time.
Integrated systems (Production, warehouse, transportation, forecast, Inventory etc) of this nature require sophisticated, computerized information systems as their basis.
Information Requirements :
a) Base Level Usage Forecast - Forecast data should be at SKU / Item level for Product axis and any level below warehouse or DC for customer. Product axis is SKU / Item level as the Company raise invoice at SKU / Item level to customer, whereas “Distribution Network Design” of that company decides the customer axis level.
b) Distribution Network Design - Distribution Network Design may change from company to company of similar Industry. For example HP and Dell company manufacturing computer machines belong to computer hardware industry but their distribution network design differ as per given below diagram.
c) Inventory Status - Inventory availability status at various distribution centre level. This includes Transit stocks (ie stocks already dispatched from factory but not reached DC)
d) Ordering data - Time phasing or schedule flow, the factory should deliver the materials to each DC. For example factory can be asked to dispatch an item to DC at Kolkata on weekly basis (Monday) whereas to another DC at Mumbai on Fortnightly basis due to lower demand in that region.
DRP Process Requirements :
a) Net Requirement (NR) computation - Forecast at SKU / DC level is used in the DRP process. However some Inventory referred as “opening stock” are already available at DC. There could be materials lying “In transit” i.e., materials which has already been dispatched from factory are yet to reach DC. These inventory i.e., opening and In transit stocks has to be adjusted or netted against the forecast volume to arrive net stock requirement at each SKU / DC.
Since demand is volatile in nature, the company may prefer to keep buffer stock referred as “Safety Stock” to meet unexpected demand fluctuation. Safety Stock criteria will differ for each item as per nature of product and each DC due to demand nature. For example Hundai Car company will keep different safety stock Norms for Santro and Accent Model due to categorization. Similarly the company keep different safety stock norms for Santro between DC at Northern and Southern Region due to demand nature.
Net Requirement is computed based on Forecast Volume + Safety Stock – opening physical stock – In transit stock.
Let us take an example of Santro car at Delhi DC. The forecast volume for next two months are 9,000 and 7,500 Units respectively. Delhi DC is already having 1,500 Units as opening stock and expected to receive In Transit stock of another 1,000 units in next two days. DC is expected to keep 5 days stocks of second month forecast volume as safety stock. Assuming 25 days are working days in a month. Then how to compute Net Requirements ?
Ist Month Forecast Volume - 9,000 units
2nd Month Forecast Volume - 7,500 units
Opening Stock - 1,500 Units
In Transit Stock - 1,000 Units
Safety Stock - 2nd Month Forecast Volume *(Safety stock days/No of Working days)
- 7500 *(5/25) = 1,500 Units
Net Requirement = 1st Forecast volume + Safety Stock – opening Stock – In Transit Stock
Net Requirement (NR) = 9000 + 1500 – 1500 – 1000 = 8000 Units
Hence the Hundai Manufacturing plant will produce 8000 units of Santro instead of 9000 units against the Delhi DC requirements. Please note that Safety Stock computation methodology differ from company to company.
b) Time Phasing Requirement : Time Phasing means when the company wants to move the products from Manufacturing plant to DC. This could be monthly, fortnightly, weekly basis. As per above example if the Hundai plant decided to send 8000 units of Santro car so as to reach Delhi DC by 3rd of August to meet August Sales. Delhi DC has to keep huge godown to accommodate all 8000 units and require more manpower to maintain the santro cars at their end. However if the company decide to send 45% of NR i.e., 3600 units on 3rd, 35% of NR i.e., 2800 units on 13th respectively and 20% of NR i.e., 1600 units on 23rd August to Delhi DC. This enable the DC to keep minimal stocks at hand with optimum storage space and manpower by providing the good service level to the customers. For FMCG company like Cadbury the time phasing for Bournvita product could be once in 3 days. Time Phasing differs for each Product and DC.
Time Phasing depends on “Distribution Network Design”. For example if manufacturing plant is located at Singapore and Central Distribution is located at Mumbai, the lead time i.e., shipping the product from Singapore to Mumbai is three months then the time phasing could vary according to demand for the product. Let us assume perfumes manufacture at French has got CDC at Mumbai and their lead time is three months. In this case the CDC may plan to get three months consolidated stocks once in three months to avoid stock out situation.
c) Planned order Release - In the earlier time phase we have given exact quantity and schedule date of stocks to be received at DC. However we need to communicate when the dispatch to be effected from plant so that the materials reach DC on scheduled date. In order to calculate the Planned order Release, we need to know the Lead time from Plant to various DCs. For example in the Hundai example the plant is located at Chennai and Lead time from Chennai plant to DC at Delhi is 7 days. The planned order release date should be 7 days less of schedule date and also to ensure that that day is working day.
One can understand that DRP is effective only if there is timely data sharing between different functions. Managing time phasing manually is another cumbersome process and hence it is recommended to have proper DRP package at your disposal which should be flexible and properly designed to cater the “Distribution Network Design” changes. DRP package should be more robust and flexible so that it can compute the quantity basis UOM, FTL (Full truck load).
So far we have learnt about DRP and computation methodology with simple example. At the outset it may look easy but in reality defining time phase for each SKU at DC level is difficult part and this will keep on changing as per market dynamics. When the company is having more Products and DC then it lead to more complication and maintenance will become big issue. When the company changes its “Distribution Network Design” by opting for more plant or DC then the DRP module has to realigned accordingly.
In the next session we will learn more about DRP.