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We sketch the integral transform method in a close connection with its historical development and survey newer applications to problems in production economics and finance. Keywords: Laplace transform; Fourier transform; Production planning

A study was conducted to analyze a framework for simultaneously obtaining the optimal run length and the production rate for a single item. In line with this, the item's output rate was characterized as a decision variable. It was then assumed that the production cost per unit was a quadratic function of the production rate. In addition, a numerical example and sensitivity analysis were carried out to characterize an iterative solution process.

A study was conducted to analyze a hybrid algorithm for the multi period multi product production planning problem. The algorithm supported mathematical programming and simulation frameworks of a manufacturing system. A production plan that is mathematically optimal and feasible was then developed. Results indicated that analytical models can be utilized with simulation frameworks to generate solutions for the problem.

The implementation of group technology as a way of factory organization is best carried out in conjunction with production flow analysis during the initial stage. Group technology involves the categorization of machine tools, human resources and other production resources. It is a newer organizational technique as compared to process organization, whose implementation is more widespread.

A simulated annealing algorithm is derived to deal with the problem of batching within the context of a flexible manufacturing system in production planning. The batching problem occurs because of the limited quantity of production resources. Computational results show that the derived algorithm performs quite well in terms of time and quality. Furthermore, the algorithm is considered applicable even for more difficult and bigger problems.

Several case studies are discussed, which show how the strategic use of advanced manufacturing technology can result in a superior marketing performance. Factors which impede the successful integration of manufacturing technology with marketing are identified. A number of recommendations to facilitating a greater linkage between technology and competitive strategy in the manufacturing environment are also prescribed.

The use of a time-based framework in corporate decision-making processes can lead to increased efficiency in the production capability of corporations. The importance of organizational quality and continuous development in the enhancement of corporate strategy can be shown in the successful workings of Japanese corporations. Two case studies involving the use of a time-based theoretical framework by an electronics components company and a gear manufacturer are presented.

We consider optimal (s, S) policies with delivery time guarantees for production planning in one-machine manufacturing systems with early set-up. The machine produces one type of product and delivery time guarantee is offered to the customers for each unit of ordered product. The inter-arrival time of the demand and the processing time for one unit of product are assumed to be exponentially distributed. In a (s, S) policy, the machine will shut down when an inventory level of S is attained and once the inventory level drops to s, the machine will re-start. A set-up time is required for the machine. We model the set-up by the exponential distribution. We obtained an analytical form of the steady state probability distribution for the inventory levels derived. The average profit of the system can be written in terms of this probability distribution. Hence the optimal (s, S) policy can be obtained by varying different possible values of s and S. [C] 2001 Elsevier Science Ltd. All rights reserved. Keywords: Manufacturing systems; (s, S) policies; Delivery time; Early set-up

The dynamic lot-sizing model (DLS) is one of the most frequently used models in production and inventory system because lot decisions can greatly affect the performance of the system. The practicality of DLS algorithms is hindered by the huge amount of computer resources required for solving these models, even for a modest problem. This study developed a parallel algorithm to solve the lot-sizing problem efficiently. Given that n is the size of the problem, the complexity of the proposed parallel algorithm is O([n.sup.2]p) with p processors. Numerical experiments are provided to verify the complexity of the proposed algorithm. The empirical results demonstrate that the speedup of this parallel algorithm approaches linearity, which means that the proposed algorithm can take full advantage of the distributed computing power as the size of the problem increases. Keywords: Materials requirements planning; Parallel algorithm; Lot sizing models

A study was conducted to extend the analysis of obtaining optimal safety stock levels in material requirements planning systems to a multi-level system supporting production that takes place based on a lot-for-lot policy. The production correlates with the application of the net present value as the objective criterion and a disregard of opportunities for joint set-up. Findings indicated the applicability of single-level results in multi-level cases during a lot-for-lot policy.