By A. S. Carrie, D. T. S. Perera (auth.), P. F. McGoldrick (eds.)
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Extra info for Advances in Manufacturing Technology: Proceedings of the First National Conference on Production Research
Even in this case, the situation is parameter bound and the answer could well be 'at the moment, planning is not your problem, it is the factors at the process level which make planning impractical'. To move from the general to the particular, why should planning be difficult? Production Planning and Control 47 It's just a question of deducting capacity from known levels, or is it? If just one resource was involved we may get reasonable results but suppose a manufacturing sequence involves say 15 resources, or more, and our process control information tells us that our data is very 'noisy'.
The company's system, based on control by minicomputer, broadly achieved this. However, the forecasting of promotion response by sales staff remained a difficulty and caused distortion of inventories. Sales staff often estimated in terms of local economic factors, such as buyer preferences, the price competitiveness of the promoted line and the expected response from competitors. There were risks with fast moving lines which could not entirely be solved by systems improvements. Notwithstanding this, a clearer distinction between base demand and promotional response was recommended to improve production scheduling and to reduce the risk of excess stock holding on certain volatile lines.
Ideally the chosen subset of patterns should minimize the total cost of stock holding, the reduction process and material wastage in the form of trim loss. g. slitting parent rolls to small widths, cropping standard bar lengths to shorter lengths, give rise to what are classed as 'one-dimensional' trim loss problems. The earliest scientific approaches 1 •2 to this class of problems were based on mathematical programming methods in which the objective function was to minimize trim loss. g. g. number of set-ups required) which introduce non-linearities in the problem formulation and which cannot be accommodated easily by classical optimization techniques.