scholarly journals Study of Grey Fuzzy Optimization Techniques for FMS Scheduling Problem

2020 ◽  
Vol 5 (1) ◽  
pp. 01-16
Author(s):  
Reetik Kaushik ◽  
◽  
Nikita Deswal ◽  
Anurag Dudpuri ◽  
Sumit Chawla ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Flexible Manufacturing ◽  
Manufacturing Systems ◽  
Job Shop ◽  
Water Quality Management ◽  
Fuzzy Optimization ◽  
Optimization Techniques ◽  
Scheduling Problem ◽  
Fms Scheduling

Deep The research study focuses on the concept of Fuzzy Logic and its applications in diverse sectors like Behavioural Science, Machining, Business Operations, Medicinal Science, Water Quality Management, Manufacturing, Anti-Braking systems, etc. Fuzzy Logic is regarded as the best option to deal with complex problems which arise due to uncertainty, incomplete information, and lack of preciseness. The major focus of this research is then divided into a case study on the application of Grey Fuzzy Optimization in the Manufacturing and Machining sectors, using the Fuzzy Logic Toolbox of MATLAB. The case study deals with a Job-Shop Scheduling Problem in a Flexible Manufacturing System (FMS). Scheduling of Jobs is a crucial task for meeting and exceeding the market demands. The decision of which part will be the next to be processed considers some criteria that influence the performance of a job shop system. The job shop system is taken from previous literature and the proposed approach is applied to get the optimal scheduling of products. Within the vast field of production and operation, its applicability was tested in scheduling conflicts in flexible manufacturing systems (FMS). All the output values were in the range of single-digit percentage error owing to different sets of rule formations but nonetheless, the proximity of the actual and calculated values reaffirmed the confidence that the verification was justified.

scholarly journals Human-Computer-Machine Interaction for the Supervision of Flexible Manufacturing Systems: A Case Study

2020 ◽  
Vol 53 (2) ◽  
pp. 10550-10555
Author(s):  
Jose Daniel Hernandez ◽  
Edgar Schneider Cespedes ◽  
David Andres Gutierrez ◽  
David Sanchez-Londoño ◽  
Giacomo Barbieri ◽  
...  
Keyword(s):  
Flexible Manufacturing ◽  
Flexible Manufacturing Systems ◽  
Manufacturing Systems ◽  
Machine Interaction

Research of Flexible Dynamic Scheduling Problem Based on Genetic Algorithm

2009 ◽  
Vol 16-19 ◽  
pp. 743-747
Author(s):  
Yu Wu ◽  
Xin Cun Zhuang ◽  
Cong Xin Li
Keyword(s):  
Genetic Algorithm ◽  
Flexible Manufacturing ◽  
Manufacturing Systems ◽  
Dynamic Scheduling ◽  
Scheduling Problem ◽  
Static Scheduling ◽  
Coding Method ◽  
Scheduling Method ◽  
Distribution Principle ◽  
Working Procedure

Solve the flexible dynamic scheduling problem by using “dynamic management & static scheduling” method. Aim at the property of flexible Manufacturing systems, the dynamic scheduling methods are analyzed and a coding method based on working procedure is improved in this paper. Thus it can be efficiently solve the problem of multiple working routes selection under the active distribution principle. On the other hand, the self-adaptive gene is provided and the parameters of the genetic algorithm are defined. In such a solution, the scheduling is confirmed to be simple and efficient.

Application of Fuzzy Logic and Fuzzy Optimization Techniques in Medical Image Processing

Biometrics ◽  
2017 ◽  
pp. 907-932 ◽  
Author(s):  
Niladri Sekhar Datta ◽  
Himadri Sekhar Dutta ◽  
Koushik Majumder
Keyword(s):  
Mathematical Model ◽  
Fuzzy Logic ◽  
Optimization Technique ◽  
Fuzzy Optimization ◽  
Fuzzy Model ◽  
Optimization Method ◽  
Fuzzy Modeling ◽  
Optimization Techniques ◽  
Fuzzy Variables ◽  
Truth Value

Fuzzy logic deals with approximate rather than fixed and exact reasoning. Fuzzy variables may have a truth value that ranges in degree between 0 and 1; extended to handle the concept of partial truth where the truth value may range between completely true or completely false. This computational logic uses truth degrees as a mathematical model of the vagueness phenomenon while probability is a mathematical model of ignorance. A huge number of complex problems may be solve using Fuzzy logic specifically Fuzzy modeling and optimization method. Fuzzy modeling is the understanding of the problem and analysis of the Fuzzy information where the Fuzzy optimization solves Fuzzy model optimally using optimization techniques via membership functions. In this research article authors describe the Fuzzy rules and its application and the different types of well known problems solved by the Fuzzy optimization technique.

scholarly journals Bi-local search based variable neighborhood search for job-shop scheduling problem with transport constraints

2020 ◽  
Author(s):  
Moussa Abderrahim ◽  
Abdelghani Bekrar ◽  
Damien Trentesaux ◽  
Nassima Aissani ◽  
Karim Bouamrane
Keyword(s):  
Manufacturing Systems ◽  
Variable Neighborhood Search ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Search Algorithm ◽  
Neighborhood Search ◽  
Efficient Production ◽  
Scheduling Problem ◽  
Job Shop Scheduling Problem ◽  
Shop Scheduling

AbstractIn job-shop manufacturing systems, an efficient production schedule acts to reduce unnecessary costs and better manage resources. For the same purposes, modern manufacturing cells, in compliance with industry 4.0 concepts, use material handling systems in order to allow more control on the transport tasks. In this paper, a job-shop scheduling problem in vehicle based manufacturing facility that is mainly related to job assignment to resources is addressed. The considered job-shop production cell has two types of resources: processing resources that accomplish fabrication tasks for specific products, and transporting resources that assure parts’ transport to the processing area. A Variable Neighborhood Search algorithm is used to schedule product manufacturing and handling tasks in the aim to minimize the maximum completion time of a job set and an improved lower bound with new calculation method is presented. Experimental tests are conducted to evaluate the efficiency of the proposed approach.

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