Holistic customer requirements and the design-select decision

Article Abstract:

A study was conducted to empirically investigate the issue of when companies can benefit from the design of product-specific parts regardless of who actually designs the components. More specifically, the problem considered is that of when firms ought to invest in designing product-specific parts given the economic advantages of selecting existing parts. It will be theoretically argued and empirically illustrated that the nature of customer needs and requirements influences the design-select decision. Holistic customer requirements and customer needs involving mass and variable cost are significant in determining the magnitude to which companies design product-specific components. The specific concepts and results of the analysis are analyzed in terms of their relation to broader published research in management, production and economics.

Customer Relations, Research, Planning, Influence, Make-or-buy decisions, Make or buy decisions

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Solving semi-Markov decision problems using average reward reinforcement learning

Article Abstract:

Sequential decision making under conditions of uncertainty is used in a broad range of business problems such as manufacturing and electronic communications. The use of a computer simulation-based, stochastic approximation framework called reinforcement learning has been proposed to calculate near optimal policies for a subset of these problems called Markov decision problems. A study presents an average reward reinforcement learning algorithm called semi-Markov average reward technique (SMART) to address semi-Markov decision problems. The SMART algorithm is used to solve a combinatorial optimization problems. It can be applied to a much larger class of problems for which stochastic approximation algorithms based on average reward reinforcement learning have not been applied.

Decision-making, Models, Decision making, Usage, Mathematical models, Markov processes, Combinatorial optimization, Stochastic approximation

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Measuring the effectiveness of overlapping development activities

Article Abstract:

The overlapping of activities has been shown to be a powerful method for reducing time-to-market in product development both in the automobile and aircraft industries. However, evidence has been produced to show that such overlapping activities can lead to development re-work particularly if uncertainties in development are not resolved during the course of a project. Thus, the overlap benefits of parallel task implementation to reduce project completion times in product development may be outweighed by the consequences of such re-work. A study was conducted to statistically measure the effectiveness of parallel task execution in reducing project completion time. Results indicate the need for the development of new measures of uncertainty resolution.

Engineering Services, Product Development Engineering, Concurrent engineering, Product engineering

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