No abstract

No abstract

Complex systems in a work cell often consist of multiple units to process the manufacturing functions effectively for achieving the desired objectives. All manufacturing work cells are familiar with many unforeseeable events, for instance machine down time and scheduled maintenance. In fact, every configuration naturally exhibits some level of redundancy during those unpredictable events that may fail a small portion of units. In this work, using the remaining units and by raising the workloads on these units, up to the level of their capacities, we tried to fulfil the requirement of products. To procure the requirement, dynamic workload adjustment strategy has been suggested on two important configurations such as parallel and hybrid, by actively controlling its degradation path and failure times. During its operation, at each decision-making point, termed as decision epoch, the examination of the real-time condition monitoring data has been carried out for upgrading the posterior distribution. Using this updated distribution as the root of all operations, the residual life distribution of every concerned unit is calculated, for a particular workload. Subsequently, the establishment of an optimization scheme, i.e., an optimization framework, has been carried out with the help of the predicted residual life to eliminate the unit failures, for individual units, coinciding with each other. Eventually, with various scenarios, simulation has been carried out on the proposed methodology to assess the rate of degradation of various units. The validation of the approach's effectiveness has been shown by the simulation results on two different configurations having different scenarios.

No abstract

Social network analysis (SNA) is a widely studied research topic, which has been increasingly applied for solving different kinds of problems, including industrial manufacturing ones. This paper focuses on the application of SNA to an industrial plant layout problem. The study aims at analysing the importance of using SNA techniques to study the important relations between entities in a manufacturing environment, such as jobs and resources in the context of industrial plant layout analysis. Here, performance measures such as maximum completion time of jobs (makespan), resource utilisation, and throughput time have been considered to evaluate the system performance. Later, with the simulation analysis, the relationships between entities and their impact on the system performance are evaluated. The experimental results revealed that the proposed SNA approach supports to find the key machines of the systems that ultimately lead to the effective performance of the whole system. Finally, the identification of relations among these entities supported the establishment of an appropriate plant layout for producing the jobs in the context of industry 4.0.