The Cycle Time Stochastic Distributions in Simulation of Manufacturing Systems

2015 ◽  
Vol 809-810 ◽  
pp. 1426-1431
Author(s):  
Elena Iuliana Gingu Boteanu ◽  
Miron Zapciu ◽  
Cristina Mohora
Keyword(s):  
Cycle Time ◽  
Flexible Manufacturing ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Flexible Manufacturing System ◽  
Probability Distributions ◽  
System Simulation ◽  
Modelling And Simulation ◽  
Discrete Events ◽  
Manufacturing Line

The paper presents a theme of research through the analysis of flows' modelling and simulation in a flexible manufacturing system. It is studied the simulation with discrete events of a real manufacturing line with the software Delmia Quest. The objectives of this paper are to modelling and simulate the manufacturing system and to choose the properly probability distributions of a cycle time of each machine from this layout. A comparison of three distributions is presented and SCL implemented program will automatically display the values resulting from the manufacturing system simulation.

Performance optimization of a flexible manufacturing system using simulation: the Taguchi method versus OptQuest

SIMULATION ◽  
2019 ◽  
Vol 95 (11) ◽  
pp. 1085-1096 ◽  
Author(s):  
Abdessalem Jerbi ◽  
Achraf Ammar ◽  
Mohamed Krid ◽  
Bashir Salah
Keyword(s):  
Taguchi Method ◽  
Performance Optimization ◽  
Flexible Manufacturing ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Flexible Manufacturing System ◽  
Flow Time ◽  
Mean Flow ◽  
Taguchi Optimization ◽  
Mean Flow Time

The Taguchi method is widely used in the field of manufacturing systems performance simulation and improvement. On the other hand, Arena/OptQuest is one of the most efficient contemporary simulation/optimization software tools. The objective of this paper is to evaluate and compare these two tools applied to a flexible manufacturing system performance optimization context, based on simulation. The principal purpose of this comparison is to determine their performances based on the quality of the obtained results and the gain in the simulation effort. The results of the comparison, applied to a flexible manufacturing system mean flow time optimization, show that the Arena/OptQuest optimization platform outperforms the Taguchi optimization method. Indeed, the Arena/OptQuest permits one, through the lowest experimental effort, to reliably minimize the mean flow time of the studied flexible manufacturing system more than the Taguchi method.

Mapping Structural Relationships Among the Critical Factors of FMS Flexibility

2019 ◽  
Vol 18 (03) ◽  
pp. 469-485
Author(s):  
Surinder Kumar ◽  
Tilak Raj ◽  
Rajesh Attri
Keyword(s):  
Flexible Manufacturing ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Flexible Manufacturing System ◽  
Critical Factors ◽  
Interpretive Structural Modeling ◽  
Excessive Competition ◽  
Structural Relationships ◽  
Manufacturing Organizations ◽  
Flexibility Options

The excessive competition in domestic as well as international market has forced the manufacturing organizations to adopt advance manufacturing systems such as flexible manufacturing system (FMS). Adoption of these systems has resulted into increased productivity and better quality products. In order to continue their presence in cut-throat competitive environment, the manufacturing organizations are exploring the flexibility options of FMS. In order to analyze the flexibility options of FMS, an endeavor has been performed to identify the critical factors (CFs) that are pertinent to the flexibility of FMS. These CFs have a reflective impact in designing of FMS. After ascertaining these CFs, interpretive structural modeling (ISM) and MICMAC approach have been used to establish the structural relationships among these CFs to develop a hierarchical model. The verdicts of this exploration may assist managers to analyze the flexibility options of FMS in their organizations.

Stochastic Design Exploration with Rework of Flexible Manufacturing System Under Copula-Coverage Approach

2018 ◽  
Vol 25 (02) ◽  
pp. 1850007 ◽  
Author(s):  
Mangey Ram ◽  
Nupur Goyal
Keyword(s):  
System Reliability ◽  
Flexible Manufacturing ◽  
Manufacturing Systems ◽  
Manufacturing Industry ◽  
Manufacturing System ◽  
Flexible Manufacturing System ◽  
Reliability Measures ◽  
High Productivity ◽  
Reliability Characteristics ◽  
Production Environments

Manufacturing systems are increasingly becoming automated and complex in nature. Highly reliable and flexible manufacturing systems (FMSs) are the necessity of manufacturing industries to fulfill the increasing customized demands. Worldwide, FMSs are used in industries to attain high productivity in production environments with rapidly and continuously changing manufactured goods structures and demands. Reliability prediction plays a very significant role in system design in the manufacturing industry, and two crucial issues in the prediction of system reliability are failures of equipment and system configuration. This novel work presents a stochastic model to analyze the performance of an FMS through its reliability characteristics, in the concern of its equipment. To improve the reliability of FMS, determine the sensitivity of the reliability measures of FMS. FMS consists of many components such as machine tools like CNC, automatic handling and material storage, controller and robot for serving load. The designed system is studied by using the Markov process, supplementary variable technique, Laplace transformation, coverage factor and Gumbel–Hougaard family copula to obtain various reliability measures. For some realistic approach, particular cases and graphical illustrations are also obtained.

Modelling and Design of Closed-Loop Manufacturing Systems

2013 ◽  
Vol 378 ◽  
pp. 367-374 ◽  
Author(s):  
Andrey A. Kutin ◽  
Mikhail Turkin
Keyword(s):  
Analytical Method ◽  
Flexible Manufacturing ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Flexible Manufacturing System ◽  
Closed Loop ◽  
Production Systems ◽  
Finite Buffers ◽  
Unreliable Machines

This paper introduces an analytical method for evaluating the performance of closed loop manufacturing systems with unreliable machines and finite buffers. The method involves transforming an arbitrary loop into one without thresholds and then evaluating the transformed loop using a new set of decomposition equations. It is more accurate than existing methods and is effective for a wider range of cases. The convergence reliability, and speed of the method are also discussed. In addition, observations are made on the behavior of closed loop production systems under various conditions. Finally, the method is used in a case study to design a flexible manufacturing system for production of aerospace parts.

Digital Factory: Simulation Enhancing Production and Engineering Process

2018 ◽  
Author(s):  
Angella Thomas ◽  
David A. Guerra-Zubiaga ◽  
John Cohran
Keyword(s):  
System Integration ◽  
Flexible Manufacturing ◽  
Manufacturing Systems ◽  
Manufacturing Industry ◽  
Manufacturing System ◽  
Flexible Manufacturing System ◽  
Engineering Process ◽  
Research Activity ◽  
Digital Twins ◽  
Enhancing Production

Manufacturing system integration is an important industrial and research activity to explore Next Generation Automated Systems (NGAS). Manufacturing systems has been incorporating flexible, reconfigurable, smart and intelligent features. Advances in technology and trends such Industry 4.0 will revolutionize the manufacturing industry tremendously. Important subjects in this direction are Digital Twins, Internet of Things, and Collaborative Robots among others, are integral to continue the progression to create smart and reliable manufacturing processes. This paper aims to implement a method applying these concepts in a Flexible Manufacturing System (FMS) by providing a broad view of NGAS.

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