Most of the traditional models in production and inventory control ignore the financial states of an organization and can lead to infeasible practices in real systems. This paper is the first attempt to incorporate asset-based financing into production decisions. Instead of setting a known, exogenously determined budgetary constraint as most existing models suggest, we model the available cash in each period as a function of assets and liabilities that may be updated periodically according to the dynamics of the production activities. Furthermore, our models allow different interest rates on cash balance and outstanding loans, which is an enhancement over most traditional models in that inventory financed by a loan may be more expensive than that by out-of-pocket cash. We demonstrate the importance of joint consideration of production and financing decisions in a start-up setting in which the ability to grow the firm is mainly constrained by its limited capital and dependence on bank financing. We then explain the motivation for asset-based financing by examining the decision making at a bank and a set of retailers in a newsvendor setting.production/inventory management, asset-based financing, loan limits, supply chain management

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This paper reviews recent work on the development of analytical models of Flexible Manufacturing Systems (FMSs). The contributions of each of the groups concerned with model development are summarized and an assessment is made of the strengths and weaknesses of its modelling approach. A number of directions in which models require extension are outlined, in particular the representation of such aspects of FMS operation as the tool delivery systems, the blocking phenomenon, the transient behavior and the differences between flexible machining systems and flexible assembly systems. Further work is also required on the structure of FMS control and the integration with plant production planning and control.flexible manufacturing system, production planning/control, analytical models

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The theoretical approach of OR and AI to scheduling often is not applicable to the dynamic characteristics of the actual situation. A preliminary field study is used to illustrate that the basic theoretical approach does not represent the reality of open job-shop scheduling, and its applicability is limited to those situations that are fundamentally static and behave like the models. Better understanding and modeling of the scheduling situation is needed.

The two management set parameters which determine the performance of a material requirements planning (MRP) system are the lead time and the safety stock. The appropriate values of these parameters are influenced by the accuracy of forecasts over the lead time, the variability of processing time and the degree of congestion, together with the costs of inventory and shortages. These influences are explored using stochastic models of a single stage manufacturing system for which work release is controlled using MRP. The major conclusion is that safety time is usually only preferable to safety stock when it is possible to make accurate forecasts of future required shipments over the lead time, otherwise safety stock is more robust in coping with changes in customer requirements in the lead time or with fluctuations in forecasts of lead time demand.production management, inventory control, input control, stochastic models