Performance Analysis of Manufacturing System at the Operational Level
Abstract
In this paper, we propose a method to control of make-to-order (MTO) manufacturing system for the operation level. Control achieved with the proposed method is based on modeling the relationship between cost and time, two very important elements of manufacturing process performance evaluation. In order to better represent the specified goal of manufacturing process we propose (as a novelty) as a criteria the Earning Power (EP). It is both synthetic (because it reflects the essential motivation of manufacturing process) as compliant with the most important five performance aspects, namely: profitability, conformance to specifications, customer satisfaction, return on investment and materials/overhead cost, selected by researchers in order of importance.
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Introduction
By definition, Earning Power is an operating income divided by total assets. Here, operating income is an income resulting from a firm's primary business operations, excluding extraordinary income and expenses. It gives a more accurate picture of a firm's profitability than gross income. Asset is something that an entity has acquired or purchased, and that has money value (its cost, book value, market value, or residual value). An asset can be: something physical, such as cash, machinery, inventory, land and building; an enforceable claim against others, such as accounts receivable; right, such as copyright, patent, trademark or an assumption, such as goodwill. For determination of EP it must be estimated: cost, time, asset, and price. Current methods for estimating the cost and time are based on breakdown of the product into elements, cost estimation of each element and summing of other costs [1,2]. As an element, we can consider one product component, one manufacturing component or one activity component. To estimate the cost for each element there are used element’s different features that are closely related to cost. With few exceptions, estimation methods lead to cost estimation without a mathematic model describing relation between cost and element’s different features. As a plus, those methods have a slight adaptation capacity to different specific situations because the information that is provided in order to estimate is general and does not adapt to specific case. Therefore, in this paper, cost and time will be estimated by techniques that are based on analytical modeling, neuronal modeling, or k-nearest neighbor regression. Each of these techniques cover a range of specific cases, namely: analytical technique covers process cases with all known regularities. The technique based on neuronal modeling covers cases when a large number of similar products are manufactured, slightly different. Moreover, k-NN regression technique covers cases when there is little data to produce a model (production is diverse and manufactured series are few).
It is not difficult to estimate the asset because in the balance sheet there are quite accurate and updated data. Price estimation goes from costs and represents the company mission in relation to the market.
Conclusion
The three operations comprising the order were modeled by means of different techniques: turning by analytical method, drilling by data mining technique, and welding by neural network technique. By the three methods there was determined the value of a maximal EP resulting the optimal value of the process parameter, i.e. speed. Thus, for turning operation EP decreases by 34%, for a number of 5 pieces, if v=100 m/min to the case when we work with v=voptimal=50m/min. For drilling operation, if work speed is v=100 rev/min EP decreases by 1.3 times to the case when the optimal work speed is, v=227 rev/min. For welding operation, if the process is performed at the speed v=2.2 mm/s then the value of EP will decrease 78 times to the case when v=voptimal =5.2mm/s. It follows that, for an operation, the optimal operation control can be made by knowing the maximal EP.
Depending on the maximum value of the order EP, the manager can decide whether to perform all operations to accomplish the job within the company or not. The manager can choose to outsource those operations that EP does not have a positive effect.