Integrating simulation with activity-based management to evaluate manufacturing cell part sequencing

1999 ◽  
Vol 37 (4) ◽  
pp. 757-768 ◽  
Author(s):  
Rodney R Rasmussen ◽  
Paul A Savory ◽  
Robert E Williams
Keyword(s):  
Manufacturing Cell ◽  
Part Sequencing

scholarly journals Fuzzy Gilmore and Gomory Algorithm: Application in Robotic Flow Shops with the Effects of Job-dependent Transportation and Set-ups

2020 ◽  
Author(s):  
Shahabeddin Sotudian ◽  
Ali Akbar Sadat Asl ◽  
Mohammad Hossein Fazel Zarandi
Keyword(s):  
Flexible Manufacturing ◽  
Fuzzy Numbers ◽  
Flow Shops ◽  
Flexible Manufacturing Cell ◽  
Fuzzy Method ◽  
Manufacturing Cell ◽  
Robotic Cells ◽  
Time Parameters ◽  
Part Sequencing ◽  
Set Up

This paper addresses the scheduling of robotic cells with job-dependent transportation and set-up effects with fuzzy methodology. Since transportation and set-up times are a large portion of the production time in a flexible manufacturing cell, ignoring these parameters may cause significant errors in determining the optimal makespan. Furthermore, determining the exact values of these time parameters is a challenging task. To overcome this problem, we represent these parameters using fuzzy L-R numbers. Using the capability of fuzzy numbers to model approximate values, we can represent these parameters without losing valuable information. For generating the optimal part sequencing in the cells, the Gilmore and Gomory algorithm is modified, and instead, a fuzzy Gilmore and Gomory algorithm is developed. We compare the results of the proposed fuzzy method with those of crisp ones. The results indicate the superiority of the proposed algorithm in terms of robustness, flexibility, and reduction of makespan.

Coordination of Operations by Relation Extraction for Manufacturing Cell Controllers

2010 ◽  
Vol 18 (2) ◽  
pp. 414-429 ◽  
Author(s):  
Kristin Andersson ◽  
Johan Richardsson ◽  
Bengt Lennartson ◽  
Martin Fabian
Keyword(s):  
Relation Extraction ◽  
Manufacturing Cell ◽  
Cell Controllers

scholarly journals Method engineering to increase labor productivity and eliminate downtime

2020 ◽  
Vol 13 (2) ◽  
pp. 321
Author(s):  
Mildrend Montoya-Reyes ◽  
Alvaro González-Angeles ◽  
Ismael Mendoza-Muñoz ◽  
Margarita Gil-Samaniego-Ramos ◽  
Juan Ling-López
Keyword(s):  
Human Factor ◽  
Dead Time ◽  
Research Strategy ◽  
Method Engineering ◽  
Human Machine Interaction ◽  
Manufacturing Cell ◽  
Future Harm ◽  
The Individual ◽  
Machine Interaction

Purpose: The purpose of this work is to present a method based on the application of method engineering, in order to eliminate downtime and improve the manufacturing cell.Design/methodology/approach: The research strategy employed was a case study applied to a manufacturing company to explore the causes of excessive dead time and low productivity. The methodology used was divided in five steps. The first corresponds to the analysis of the lathe and grinding process; the second is the elaboration of the man-machine diagram to identify dead times; the third is the application of the improvement proposal; the fourth is the redistribution of the cell to optimize the process; the fifth is to conclude from the results obtained.Findings: With the proposed method, the downtime was reduced by 41% and only 50% of the available labor is required, therefore, it is concluded that the method can be used to redesign manufacturing cells.Research limitations/implications: This research was limited to analyzing and improving human-machine interaction, since work is not just the machine, or the individual alone, or the individual manipulating the machine, therefore, no other tools were used to improve the time of machines operation.Practical implications: Designing a manufacturing cell that allows the operator to do his job with less fatigue and not adapt the operator to the job, as commonly happens.Social implications: Companies must show a greater interest in occupational health by including human capital in their optimization plans to avoid future harm to workers.Originality/value: The key contribution of this paper focused on developing a novel and practical methodology to design or re-design manufacturing cells to improve productivity considering the human factor, inspired by the main concepts of method engineering.

Neural networks in manufacturing cell design

1998 ◽  
Vol 36 (1-2) ◽  
pp. 133-138 ◽  
Author(s):  
Manolis Christodoulou ◽  
Vassilis Gaganis
Keyword(s):  
Neural Networks ◽  
Cell Design ◽  
Manufacturing Cell

Task recognition from joint tracking data in an operational manufacturing cell

2015 ◽  
Vol 29 (6) ◽  
pp. 1203-1217 ◽  
Author(s):  
Don J. Rude ◽  
Stephen Adams ◽  
Peter A. Beling
Keyword(s):  
Tracking Data ◽  
Manufacturing Cell ◽  
Task Recognition ◽  
Joint Tracking

Control of knowledgeable manufacturing cell with an unreliable agent

2008 ◽  
Vol 20 (6) ◽  
pp. 671-682 ◽  
Author(s):  
Hong-Sen Yan ◽  
Hong-Bing Yang ◽  
Hao Dong
Keyword(s):  
Manufacturing Cell ◽  
Knowledgeable Manufacturing
Sign in / Sign up

Export Citation Format

Share Document