Wednesday, December 23, 2009

Aggregate Production Planning - Part III

We will learn few more terminology related to Production Planning and then finally link whatever we learnt to understand the Production Planning concept in a comprehensive way.

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


Monday, December 21, 2009

Aggregate Production Planning - Part II

In this blog, we will learn how various techniques used to compute the total cost of aggregate production using Chase strategy and Level Strategy and compare the cost advantage.

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
       o Simulation

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.

The Chase (Demand) strategy require explanation. The above table consist of volume and total cost in terms of value. Since in the chase model we are keeping our production rate in line with demand pattern and hence there is no inventory or lost sales in terms of volume and value. However we are changing work force and output rate this resulted in overtime / under time cost along with rate change cost due to set up changes. Since each month we are varying the production quantity to meet the demand this involves set up changes and cost.
In the above example, we are holding Inventory in the beginning of the year (1000 units as ending inventory). Hence we are producing 700 units in January against the sales quantity of 1700 units after adjusting the inventory holding. During January end there is no inventory, we are matching production as per monthly demand requirements.

The manufacturing plant can produce 2400 units (Normal production rate) during any given month. During January the company is planning to produce 700 units the plant capacity is under utilized to the extent of 1700 units (Normal production rate – Actual quantity produced to meet the demand, i.e., 2400-700) which involves under time / utilization cost (i.e., Qty 1700 * Rs. 3/unit – Rs. 5100). Similarly in April, the demand (2800 units) exceed the normal production rate of 2400 units, the excess 400 units need to be produced to meet the demand and this involves over time cost (400 units * Rs. 7 / unit – Rs. 2800).

As regards production rate change cost, during January we are falling short of 1700 units against normal production rate of 2400 units and hence the cost will be Rs. 8500 (i.e., 1700 units * Rate change cost/ units Rs. 5). But in February we are changing the production rate from 700 units which is actual production rate to meet January demand to 1200 units to meet

February demand. The rate change cost computed basis change in production units of 500 units (1200 units in Feb – 700 units in Jan) and Rate change cost (Rs.5) per unit. During Feb the rate change cost will be Rs. 2500 and so on.

The total cost can be computed by adding all cost like production cost, inventory cost, lost sales cost, over time cost, under time cost and rate change cost.

Now we will learn about the production cost computation based on Level startegy model by keeing constant work force and output rate.

In the Level startegy we are keeping work force and production rate constant and hence there will be uniform production cost (2400 units * Rs. 75 Production rate / unit) across all month. Also there will be no over time or under time and there will no set up cost also due to constant production rate.  This level strategy involves only Inventory holding cost and Lost Sales Cost.

For example during January we are producing 2400 units against our actual requirement of 700 units (after adjusting inventory holding) and hence there will be excess stock of 1700 units (i.e., 2400 - 700).  The inventory holding cost during January will be 1700 units multiplied by Inventory holding cost of Rs.2 per unit (i.e., 1700 * 2 = Rs. 3400).

During August, we are producing 2400 units against the demand of 3,200 units and hence there will be sales lost to the extent of 800 units (i.e., Demand during August - Actual production during august). Lost sales cost per unit is Rs. 90 the lost sales cost during August will be Rs. 72000 (i.e., 800 * 90). 
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 Planning - Part I

In this session we will learn about Aggregate Production Planning (APP).

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.

Also the production facility of the company are used judiciously for the product family group, the production plan is done at aggregate level rather than individual SKU. In our Hitachi company example currently the factory facility to cater Window AC production. Let us assume they are planning to produce Split AC also then they will draw the production plan in such a way they will use the existing Window AC facility to produce certain parts of Split AC and for rest of the parts which cannot be produced through the existing facility, they can plan for additional facilities. In this case the Hitachi production plant are effectively used for Window and Split AC models. Once the company commit the facility (machine and workers) and resources (raw materials) to produce Window ACs 1 Ton model during first week (1 – 7) of Jan’2010 they cannot plan any other activity (i.e., to produce Window ACs of 1.5 Ton) during that period. If the company would like to produce 1.5 Ton Window ACs during the second week (i.e., 8 – 14), they have to make small alteration in the production facility (in production engineering terminology referred as setup changes) to produce 1.5 Ton Window AC from the existing 1 Ton Window AC. This is due to size, change in production type etc as compared to 1 Ton model. This set up changes is always associated with cost which referred as setup cost.

We will focus our attention how the company is going work out a plan during year 2010 to commit the existing resources/capacity (facilities, workers, materials) to meet the expected demand of 1,60,000 units during in such a way costs are minimized. For one year expected growth (60% over year 2009) the company will not go for additional factory / facility as they are capital intensive, which involve long term capacity planning. Also the sales volumes are not consistent and fluctuating throughout the month. The demand is more during summer season (ie March to October) and less during Winter season (November to February). Given below management option to meet the monthly fluctuating demand.

Management option to meet the Fluctuating Demand (Capacity Adjustment)

• Build inventories in slack period (November - February) in anticipation of meeting higher demand in peak period (March – October)
• Carry backorders / Pending orders or tolerate lost sales during peak period
• Use over time in peak periods, under time in slack period to vary output, while holding work force and facilities constant. Part time / casual labour is also utilized during peak period.
• Vary capacity by changing size of the work force through hiring and firing. This is not the good option as this will spoil the reputation of the company and getting skilled labour will also become problem which affect the quality of the product.
• Each option involves cost which could be tangible or intangible. Aim in aggregate production planning is to choose best option.
• Not considering capital intensive option like erection of new plant where facilities are constant and work force may vary.
• Subcontracting. Frequently firms choose to allow another manufacturer or service provider to provide the product or service to the subcontracting firm's customers. By subcontracting work to an alternative source, additional capacity is temporarily obtained.

Aggregate planning is considered to be intermediate-term (as opposed to long- or short-term) in nature. Hence, most aggregate plans cover a period of three to 18 months. Aggregate plans serve as a foundation for future short-range type planning, such as production scheduling, sequencing, and loading.

Aggregate Production Plan - Cost

• Procurement Cost
• Regular-Time Costs (production Cost)
• Overtime Costs
• Hiring and Layoff Costs
• Inventory Holding Costs
• Backorder and Stock out Costs
• Production rate changing cost

Aggregate Production Plan - Strategies

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.


Pure Strategy

1) Level Strategy

A level strategy seeks to produce an aggregate plan that maintains a steady production rate and/or a steady employment level. In order to satisfy changes in customer demand, the firm must raise or lower inventory levels in anticipation of increased or decreased levels of forecast demand.

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.

Mixed Strategy

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.

In the next session we will learn about the various techniques used in Aggregate Planning with few examples.