scholarly journals CELLULAR MANUFACTURING LAYOUT DESIGN USING HEURISTIC CLUSTERING ALGORITHM AND LPP MODEL

2021 ◽  
Vol 32 (2) ◽  
Author(s):  
S. Ramesh ◽  
N. Arunkumar ◽  
R. Vijayaraj
Keyword(s):  
Clustering Algorithm ◽  
Cell Formation ◽  
Shop Floor ◽  
Benchmark Problems ◽  
Algorithm Performance ◽  
Batch Sizes ◽  
Optimisation Model ◽  
Exceptional Elements ◽  
Heuristic Clustering ◽  
Machine Cell

This mathematical model forms machine cells, optimises the costs of unassigned machines and components, and designs the shop floor cell layout to have minimal movement of materials. The complete similarity measure algorithm forms machine cells and part families in a refined form. Later, exceptional elements are eliminated in the optimisation model by using machine duplication and sub-contracting of parts. Then the shop floor layout is designed to have optimised material movements between and within cells. An evaluation of the cell formation algorithm’ performance is done on the benchmark problems of various batch sizes to reveal the process’s capability compared with other similar methods. The data of machining times are acquired and tabulated in a part incidence matrix, which is used as input for the algorithm. The results from the linear programming optimisation model are that costs are saved, machines are duplicated, parts are sub-contracted, and there are inter- and intra- cellular movements. Finally, the output of the inbound facility design is the floor layout, which has machine cell clusters within the optimised floor area.

DESIGN OF AN INTERACTIVE VIRTUAL FACTORY USING CELL FORMATION METHODOLOGIES

2003 ◽  
Vol 02 (02) ◽  
pp. 229-246 ◽  
Author(s):  
T. KESAVADAS ◽  
M. ERNZER
Keyword(s):  
Virtual Environment ◽  
Clustering Algorithm ◽  
Flow Analysis ◽  
Cell Formation ◽  
Open Architecture ◽  
Successful Implementation ◽  
Design Environment ◽  
Virtual Factory ◽  
Software Modules ◽  
And Performance

This paper describes an interactive virtual environment for modeling and designing factories and shop floors. The factory building tool is developed as an open architecture in which various modules can be utilized to quickly implement factory design algorithms ranging from plant layout to factory flow analysis. Software modules and utilities have been implemented to allow easy set-up of the visual interface. In this paper, this virtual factory is used to implement cellular manufacturing (CM) system. CM has traditionally been a very complicated system to implement in practice. However successful implementation of the system has improved productivity immersely. Several issues involved in implementing CM within our virtual factory machine modeling and interface designs for defining the cells, are discussed. The mathematical clustering algorithm called Modified Boolean Method was implemented to automatically generate complex virtual environments. The virtual factory makes the process of CM-based factory design a very easy and intuitive process. Though the cell formation problem is NP-complete in 2D space, issues related to human factors and ergonomics can be better perceived in a 3D virtual environment. It also leads to further optimization with respect to maintainability and performance, and thus help get better solutions, which are not visible unless the factory is built. Our virtual factory interface also allows easy reassignment of machines and parts, subcontracting of bottleneck parts and rearranging of machines within the same design environment, making this a productive industrial tool. 3D virtual factory can also be automatically generated from the Part Machine interface called the Virtual Matrix Interface.

Manufacturing and Fractional Cell Formation Using a New Binary Digit Grouping Algorithm with a Pwavroid Solution Explorer Toolkit

2014 ◽  
Vol 933 ◽  
pp. 97-105
Author(s):  
Hassan Mroue ◽  
Thien My Dao
Keyword(s):  
Group Technology ◽  
Cell Formation ◽  
Optimal Solution ◽  
Binary Digit ◽  
Final Solution ◽  
Manufacturing Cells ◽  
Additional Cell ◽  
Exceptional Elements ◽  
Grouping Algorithm ◽  
Fractional Cell

A new algorithm is presented in order to search for the optimal solution of the manufacturing and fractional cell formation problem. In addition, this paper introduces a new toolkit, which is used to search for the various candidate solutions in a periodic and a waving (diversified) manner. The toolkit consists of 15 tools that play a major role in speeding up the obtainment of the final solution as well as in increasing its efficiency. The application of the binary digit grouping algorithm leads to the creation of manufacturing cells according to the concept of group technology. The nonzero entries, which remain outside the manufacturing cells, are called exceptional elements. When a lot of such elements is obtained, an additional cell called fractional (or remainder) cell may be formed; the aim of which is to reduce their number. This algorithm was tested by using illustrative examples taken from the literature and succeeded to give better or at least similar results when compared to those of other well-known algorithms.

Design of an Interactive Virtual Factory Using Cell Formation Methodologies

1999 ◽  
Author(s):  
T. Kesavadas ◽  
M. Ernzer
Keyword(s):  
Clustering Algorithm ◽  
Flow Analysis ◽  
Cell Formation ◽  
Open Architecture ◽  
Successful Implementation ◽  
Design Environment ◽  
Virtual Factory ◽  
Machine Modeling ◽  
Software Modules ◽  
Set Up

Abstract This paper describes an interactive virtual environment for modeling and designing factories and shop floors. The factory building tool is developed as an open architecture in which various modules can be utilized to quickly implement factory design algorithms ranging from plant layout to factory flow analysis. Software modules and utilities have been implemented to allow easy set-up of the visual interface. In this paper this virtual factory is used to implement cellular manufacturing (CM) system. CM has traditionally been a very complicated system to implement in practice. However the productivity rise obtained by the successful implementation of the system has been proved to be immense. Several issues involved in implementing CM within our virtual factory machine modeling and interface designs for defining the cells, are discussed. The mathematical clustering algorithm called Modified Boolean Method was implemented to automatically generate complex virtual environments. The virtual factory makes the process of CM-based factory design a very easy and intuitive process. Virtual factory interface also allows easy reassignment of machines and parts, subcontracting of bottleneck parts and rearranging of machines within the same design environment, making this a productive industrial tool.

A Fuzzy Simulated Evolution Algorithm for Hard Problems

2014 ◽  
pp. 892-912
Author(s):  
Michael Mutingi
Keyword(s):  
Set Theory ◽  
Large Scale ◽  
Cell Formation ◽  
Computational Experiments ◽  
Benchmark Problems ◽  
Problem Complexity ◽  
Simulated Evolution ◽  
Solution Methods ◽  
Hard Problems ◽  
Evolution Algorithm

As problem complexity continues to increase in industry, developing efficient solution methods for solving hard problems, such as heterogeneous vehicle routing and integrated cell formation problems, is imperative. The focus of this chapter is to develop from the classical simulated evolution algorithm, a Fuzzy Simulated Evolution Algorithm (FSEA) that incorporates the concepts of fuzzy set theory, evolution, and constructive perturbation. The aim is to improve the search efficiency of the algorithm by enhancing the major phases of the algorithm through initialization, evaluation, selection, and reconstruction. Illustrative examples are provided to demonstrate the candidate application areas and to show the strength of the algorithm. Computational experiments are conducted based on benchmark problems in the literature. Results from the computational experiments demonstrate the strength of the algorithm. It is anticipated that the application of the FSEA metaheuristic can be extended to other hard large scale problems.

Genetic vs. Hybrid Algorithm in Process of Cell Formation

2013 ◽  
pp. 68-98 ◽  
Author(s):  
R. Sudhakra Pandian ◽  
Pavol Semanco ◽  
Peter Knuth
Keyword(s):  
Hybrid Algorithm ◽  
Flow Analysis ◽  
Cell Formation ◽  
Performance Measure ◽  
Cell Formation Problem ◽  
Production Flow ◽  
Linkage Algorithm ◽  
Formation Problem ◽  
Exceptional Elements ◽  
Performance Results

The cell formation problem has met with a significant amount of attention in recent years by demonstrating great potential for productivity improvements in production environment. Therefore, the researchers have been developing various methods based on similarity coefficient (SC), graph theory approaches, neural networks (NN), and others with aim to automate the whole cell formation process. This chapter focuses on presentation of hybrid algorithm (HA) and genetic algorithm that are helpful in production flow analysis to solve the cell formation problem. The evaluation of hybrid and genetic algorithms are carried out against the K-means algorithm and C-linkage algorithm that are well known from the literature. The comparison uses performance measure and the total number of exceptional elements (EEs) in the block-diagonal structure of machine-part incidence matrix using operational time as an input. The final performance results are presented in the form of graphs.

Sign in / Sign up

Export Citation Format

Share Document