Sankar Sengupta

Steady-state performance analysis of serial transfer lines subject to machine and buffer failure

In modern automated production lines, it is common to connect adjacent machines with buffers. Since these buffers are mechanical devices, they are prone to failure. Previous research concerning the steady-state analytical modeling of serial transfer lines assumed that buffers are completely reliable. The paper considers the unreliable buffer and presents a model of the serial transfer line incorporating this concept. A decomposition technique is developed for the general serial transfer line with unreliable buffers, and an algorithm for computing the solution of the model is presented.

A better approach to modeling emergency care service

The objective of this paper is to develop and analyze models used in emergency care system. A different modeling approach is presented based on the idea of using a priority measure defined as “operating priority” that changes with time as a patient waits for service and each resource pays due consideration to skill hierarchy and selects the next patient for treatment. The new modeling approach breaks away from the conventional approach in which entity drives the request for resources. The resource is the driver in the new approach. This paper presents a comparison of performance between the conventional and the new approach in modeling emergency care. The paper also discusses potential enhancements of the proposed approach.

An interdisciplinary laboratory for teaching manufacturing and artificial intelligence

Summary form only given. Global competition has played a major role in the awakening of American industry to the need to improve the understanding and control of their manufacturing processes. The manufacturing arena has traditionally been the domain of engineers. However, many manufacturing problems are ill-defined with solutions that are not adequate for todays manufacturing environment. One promising approach for developing new solutions to these problems, that comes from the discipline of computer science, is artificial intelligence (AI). Research concerning the application of AI concepts to problems in manufacturing systems resulted in the formation of the Artificial Intelligence and Manufacturing (AIM) project at Oakland University. The National Science Foundation, Carnegie Group Inc., Fanuc Robotics Inc. and Siemans Energy and Automation Inc. have provided funding and equipment for the AIM Laboratory. The AIM laboratory provides learning facilities for students to study manufacturing as well as AI concepts individually. In addition, the AIM laboratory allows students to integrate such knowledge and methodologies in order to improve manufacturing processes through the use of AI techniques.

Heuristic procedure for resolving a production planning model of an FMS

A production planning model for an FMS that integrates quality related decisions is presented. A heuristic procedure for resolving the model is presented and performance of the procedure is reported. Initial investigation indicates that the procedure is capable of identifying good solutions expediently. The performance of the procedure is discussed.

Derivation of repair and processing rates for decomposition of serial transfer lines with unreliable buffers

The analytic model of the K machine serial transfer line consisting of K unreliable machines and K-1 unreliable buffers is considered. An approximate solution of this model for certain performance measures has been accomplished by utilization of a decomposition technique. We give details of the derivation of the repair and processing rates for the virtual machines of this decomposition.