Capacity planning and control

 

SEASONALITY OF DEMAND

 

In many organizations, capacity planning and control is concerned largely with coping with seasonal demand fluctuations.

 

Almost all products and services have some demand seasonality

 

and some also have supply seasonality, usually where the inputs are seasonal agricultural products – for example, in processing frozen vegetables.

 

These fluctuations in demand or supply may be reasonably forecastable, but some are usually also affected by unexpected variations in the weather and by changing economic conditions.

 

Figure 11.3 gives some examples of seasonality, while the short case ‘Producing while the sun shines’ discusses the sometimes unexpected link between weather conditions and demand levels.

The seasonality demand patterns are shown in Figure 11.4.

 

the woollen knitwear business - climatic patterns (cold winters, warm summers)

 

and the hotel - demand from business people, who take vacations from work at Christmas and in the summer.

 

The retail supermarket is a little less seasonal, but is affected by pre-vacation peaks and reduced sales during vacation periods.

 

The aluminium producer shows virtually no seasonality, but is showing a steady growth in sales over the forecast period.

WEEKLY AND DAILY DEMAND FLUCTUATIONS

 

The daily and weekly demand patterns of a supermarket will fluctuate, with some degree of predictability.

 

Demand might be low in the morning, higher in the afternoon, with peaks at lunchtime and after work in the evening.

 

Demand might be low on Monday and Tuesday, build up during the latter part of the week and reach a peak on Friday and Saturday.

 

Banks, public offices, telephone sales organizations  and electricity utilities all have weekly  and daily, or even hourly, demand patterns  which require capacity adjustment. 

 

The extent to which an operation will  have to cope with very short-term demand  fluctuations is partly determined by how  long its customers are prepared to wait  for their products or services. 

 

An operation whose customers are incapable  of, or unwilling to, wait will have  to plan for very short-term demand fluctuations.

 

Emergency services, for example, will need  to understand the hourly variation in  the demand for their services and plan  capacity accordingly.

 

MEASURING CAPACITY

 

The main problem with measuring capacity is the complexity of most operations.

 

Only when the operation is highly standardized and repetitive is capacity easy to define unambiguously.

 

So if a television factory produces only one basic model, the weekly capacity could be described as 2000 Model A televisions.

 

A fast ride at a theme park might be designed to process batches of 60 people every three minutes – a capacity to convey 1200 people per hour.

 

In each case, an output capacity measure is the most appropriate measure because the output from the operation does not vary in its nature.

 

For many operations, however, the definition  of capacity is not so obvious.

 

When a much wider range of outputs  places varying demands on the process,  output measures of capacity are less useful.

 

Here input capacity measures are frequently used to define capacity.

 

Almost every type of operation could  use a mixture of both input and output  measures, but in practice most choose  to use one or the other (see Table  11.1).

CAPACITY DEPENDS ON ACTIVITY MIX 

 

The hospital measures its capacity in terms of its resources, partly because there is not a clear relationship between the number of beds it has and the number of patients it treats.

 

If all its patients required relatively minor treatment with only short stays in hospital, it could treat many people per week.

 

If most of its patients required long periods of observation or recuperation, it could treat far fewer.

 

Output depends on the mix of activities in which the hospital is engaged and, because most hospitals perform many different types of activities, output is difficult to predict.

 

Certainly it is difficult to compare directly the capacity of hospitals

which have very different activities.

WORKED EXAMPLE

 

Suppose an air-conditioner factory produces  three different models of air-conditioner unit: the deluxe, the standard and the economy.

 

The deluxe model can be assembled in 1.5 hours, the standard in 1 hour and the economy in 0.75 hours.

 

The assembly area in the factory has 800 staff hours of assembly time available each week.

 

If demand for deluxe, standard and economy  units is in the ratio 2:3:2, the  time needed to assemble 2 + 3 + 2 = 7 units =

= (2 х 1.5) + (3 х 1) + (2 х 0.75) = 7.5 hours

 

The number of units produced per week  is = (800/7.5)x 7 = 746.7 units

If demand changes to a ratio of  deluxe, economy, standard units of 1:2:4,  the time needed to assemble 1 + 2 + 4 = 7 units is:

(1  х 1.5) + (2 х 1) + (4 х 0.75) = 6.5 hours

 

Now the number of units produced per  week is = (800/6.5) x 7 = 861.5 units

DESIGN CAPACITY AND EFFECTIVE  CAPACITY 

 

The theoretical capacity of an operation – the capacity which its technical designers had in mind when they commissioned the operation – cannot always be achieved in practice.

 

For example, a company coating photographic paper will have several coating lines which deposit thin layers of chemicals onto rolls of paper at high speed.

 

Each line will be capable of running at a particular speed.

 

Multiplying the maximum coating speed by the operating time of the plant gives the theoretical design capacity of the line.

 

 

But in reality the line cannot be  run continuously at its maximum rate. 

 

Different products will have different coating  requirements, so the line will need to  be stopped while it is changed over.

 

Maintenance will need to be performed  on the line, which will take out  further productive time.

 

 Technical scheduling difficulties might mean more lost time.

 

 Not all of these losses are the operations manager’s fault;