Author:
Wa-Muzemba Anselm Tshibangu
Affiliation:
Morgan State University, United States
Keyword(s):
Little’s Law, Simulation, Lean Six Sigma, Throughput, Mean Flow Time, Work in Process, Reliability, MTBF, MTTR.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Engineering Applications
;
Formal Methods
;
Industrial Engineering
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Manufacturing Systems Engineering
;
Modeling, Simulation and Architectures
;
Planning and Scheduling
;
Production Planning, Scheduling and Control
;
Robotics and Automation
;
Signal Processing, Sensors, Systems Modeling and Control
;
Simulation and Modeling
;
Symbolic Systems
;
Systems Modeling and Simulation
Abstract:
Uncertainty in production systems may arise from different sources including machines, parts, tools or material handling failures. For this reason the need for the production system to be flexible enough to respond to unanticipated breakdowns or failures become highly recognized. This paper considers a flexible manufacturing system (FMS) and analyzes the effect of a combination of various design and operational parameters on the overall system performance under different machine failures/breakdowns patterns. Three performance criteria including throughput rate (TR), mean flow time (MFT), work-in-process (WIP), are analyzed for various machine and AGV scheduling rule combinations over a range of AGV fleet size. These key Lean indicators are selected because they are tenants of Little’s Law considered as the backbone equation in Lean Six Sigma methodologies as it advocates the reduction of waste, variability and work in process around the process in order to reduce the cycle time while
increasing quality. Comparison is made with the performance profile of a system operating in a failure-free mode. The results reveal that machine and material handling scheduling rule combinations together with the maintenance policy in use may affect significantly the performance of a production system. The results also show that there is an acceptable level of machine breakdown (reliability) for which the system performance is similar to a failure free system.
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