Yohanan Arzi

Learning and forgetting in mental and mechanical tasks: a comparative study

This study compares learning and forgetting of mental and mechanical tasks. Fifty-eight subjects performed a simple mechanical and complex mental task repetitively. After completing half the repetitions on each task type, each subject took a break ranging from 2 to 6 weeks before completing the remaining repetitions. The learning and forgetting processes of the participating subjects are analyzed by fitting appropriate models. The results of hypothesis testing regarding the relationship between the learning and forgetting models of mechanical and mental tasks are reported and discussed.

Neural network-based adaptive production control system for a flexible manufacturing cell under a random environment

A Neural Network (NN)-based Production Control System (PCS) for a Flexible Manufacturing Cell (FMC), operating in a highly random produce-to-order environment is presented. The proposed PCS chooses periodically, on the basis of the current state of the system, the most appropriate scheduling rule, out of several predetermined ones. The proposed PCS is based on multi-layer NNs, one for each competing scheduling rule, that predict the FMCs performance. The NNs are retrained periodically. The performance of the proposed NN-based PCS was tested by simulation of two different FMC configurations. The NN-based PCS has performed significantly better than a decision-tree-based PCS and a single-rule-based PCS.

Operating an FMC by a decision-tree-based adaptive production control system

In previous works decision tree mechanisms were suggested for real-time production control of flexible manufacturing systems operating in a constant mix environment. The current paper tests the performance of a decision-treebased adaptive production control system operating in a flexible manufacturing cell in more random environments. A decision-tree-based production control system, which periodically chooses, on the basis of the current state of the system, the most appropriate scheduling rule, out of several predetermined ones, is presented. The performance of the decision-tree-based production control system was tested by simulating a flexible manufacturing cell operating in two different operational environments, distinct by the variability of their demand. The decision tree-based-production control system has performed rather well in the produce-to-order environment. However, it does not outperform the alternative scheduling rules in a highly random produce-to-order environment.

Optimal design of flexible production lines with unreliable machines and infinite buffers

Despite the increasing use of automated manufacturing systems, combining flexible technology, only a few models for designing such systems are available. This paper presents a model for the determination of the profit-maximizing configuration of workstations (both machine types and number) along a flexible production line with unreliable machines and infinite buffers. A mixed integer programming formulation of the problem is introduced and an optimal solution algorithm is developed. For large scale problems a heuristic procedure is presented.

Real-time production control of an FMS in a produce-to-order environment

Abstract This paper deals with real-time control of an FMS, operating in a produce-to-order environment, with machines subject to failure. A two-level production control system (PCS) is developed and examined. The proposed PCS incorporates three principles: no need for pre-planning procedures; separation between due-date and operational considerations; and full exploitation of process flexibility. In an extensive series of simulation experiments it was demonstrated that the proposed PCS leads to good results in both criteria: maximum throughput and minimum tardiness of orders. A comparison study between this PCS and one which is not based on separation between due-date and operational considerations, indicated the advantage of the former.

Model for cost estimation in a finite-capacity stochastic environment based on shop floor optimization combined with simulation

In recent years several researchers suggested cost estimation models that consider limited capacity. These researchers ignored the stochastic nature of the shop floor. This paper presents a cost estimation model that takes into account the stochastic environment. It is based on marginal analysis - the difference between the total cost without the new order and the total cost with the new order. The proposed model is based on the integration of simulation and optimization. Data generated by the simulation is inserted into the optimization procedure that finds good feasible solutions quickly. A significant advantage of the proposed stochastic cost estimation over an existing deterministic approach is shown. A computational study is performed to test different factors affecting the proposed model.

On-line scheduling in a multi-cell flexible manufacturing system

This paper deals with on-line scheduling in a multi-cell flexible manufacturing system, operating in a produce-to-order environment. A two level distributed production control system (DPCS) is developed and tested through a simulation study. The DPCS allows autonomous and simultaneous operation of each cell-controller, utilizing only local and short term information as well as simple heuristic rules. Simulation experiments show that the proposed DPCS achieves good results in throughput, tardiness of orders and WIP inventory level and that it is robust to machine and handling device failures.

Measurement of processing flexibility in flexible manufacturing cells

Abstract This paper proposes an approach to a quantitative evaluation of processing flexibility in flexible manufacturing cells. Factors that may influence flexibility are surveyed and two numerical indices incorporating some of these factors are developed. A simple index is based on the existence of interrelations between operations and machines. A more complex index requires knowledge of processing times. Extensive experiments were carried out to test the correlation between these indices and the ratio of average achieved throughput at partial flexibility to that total flexibility (i.e., if all operations could be carried out on all machines). Results indicated that the proposed flexibility measures provide an excellent prediction of the influence of machine-operation possibilities on throughput performance.

Methods engineering: Using rapid prototype and virtual reality techniques

Methods engineering (ME) is the most traditional area of industrial engineering. In spite of its importance, the tools and techniques in use have hardly changed in the last 30 years. Lately, tools based on rapid prototyping (RP) and virtual reality (VR) techniques have been developed. This article presents the concept of incorporating these technologies with the ME process. A framework for an RP and VR-based ME system is introduced. Two preliminary attempts to implement RP technology in ME are reported.

Distributed dynamic production control in a multi-cell flexible manufacturing system

This paper deals with real-time control of a multi-cell flexible manufacturing system, operating in a produce-to-order environment. A two-level Distributed Production Control System (DPCS) is developed, the DPCS allowing autonomous operation of each cell-controller, utilizing only local and short term information as well as simple heuristic rules.