Designing a new mathematical model for cellular manufacturing system based on cell utilization

2007 ◽  
Vol 190 (1) ◽  
pp. 662-670 ◽  
Author(s):  
Iraj Mahdavi ◽  
Babak Javadi ◽  
Kaveh Fallah-Alipour ◽  
Jannes Slomp
Keyword(s):  
Mathematical Model ◽  
Manufacturing System ◽  
Cellular Manufacturing ◽  
Cellular Manufacturing System

Proposed linear-mathematical model for configuring cell and designing unequal-area facility layout in dynamic cellular manufacturing system

2016 ◽  
Vol 22 (3) ◽  
pp. 332 ◽  
Author(s):  
Afsaneh Nouri Houshyar ◽  
Zulkiflle Bin Leman ◽  
Moh Khairol Anuar Mohd Ariffin ◽  
Napsiah Ismail ◽  
Hojat Pakzad Moghadam ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Manufacturing System ◽  
Cellular Manufacturing ◽  
Facility Layout ◽  
Cellular Manufacturing System

A mathematical model for assessing the effects of a lot splitting feature on a dynamic cellular manufacturing system

2017 ◽  
Vol 11 (4-5) ◽  
pp. 557-573 ◽  
Author(s):  
Mohammad Kazemi ◽  
Shima Shafiee Gol ◽  
Reza Tavakkoli-Moghaddam ◽  
Reza Kia ◽  
Javad Khorrami
Keyword(s):  
Mathematical Model ◽  
Manufacturing System ◽  
Cellular Manufacturing ◽  
Cellular Manufacturing System ◽  
Lot Splitting

scholarly journals Integration of parts scheduling, MRP, production planning and generalized fixed-charge transportation planning in the design of a dynamic cellular manufacturing system

2020 ◽  
Author(s):  
Shima Shafiee-Gol ◽  
reza kia ◽  
Reza Tavakkoli-Moghaddam ◽  
Mohammad Kazemi ◽  
Mehdi A. Kamran
Keyword(s):  
Mathematical Model ◽  
Supply Chain ◽  
Production Planning ◽  
Manufacturing System ◽  
Cellular Manufacturing ◽  
Raw Materials ◽  
Cell Formation ◽  
Time Cost ◽  
Cellular Manufacturing System ◽  
Dynamic Cell

In this paper, to integrate the decisions of parts scheduling, Material Requirement Planning (MRP), Production Planning (PP) and Transportation Planning (TP) for designing a Cellular Manufacturing System (CMS) under a dynamic environment, a Mixed-Integer Nonlinear Programming (MINLP) mathematical model is formulated. The proposed mathematical model integrates extensive coverage of significant manufacturing characteristics in designing a CMS to be implemented in a three-layer supply chain. The considered features include markets demands, heterogeneous vehicles, raw materials requirements planning, parts due dates, cell size limits, machines capacity, intra/inter cell material handling time/cost, transportation time/cost, operation time, alternative processing routes in addition to the main decisions of parts scheduling, PP, TP and dynamic cell formation. Also, some novel characteristics are incorporated based on a three-layer supply chain that make the presented model remarkable respect to the literature including 1) In the first layer, planning the orders of raw materials with different lead times and usage coefficients is performed, 2) In the second layer, decisions of dynamic cell formation and parts scheduling are made, and 3) In the third layer, optimal vehicles are selected as a generalized fixed-charge TP based on transportation time and cost to satisfy multi-markets with different demand volumes. The components in the objective function to be minimized include total costs of holding the parts inventories in the markets, backorders, tardiness, transportation of the parts from the plant to the markets, purchase of raw materials, keeping raw materials in the plant warehouse, intercellular/intracellular movements and machine relocation. An illustrative numerical example is solved by the CPLEX solver to illustrate the achievements obtained by the incorporated characteristics in the integrated model. Furthermore, a sensitivity analysis is performed to assess the effects of important parameters on the model performance. Since the proposed model is NP-hard, a Simulated Annealing (SA) algorithm is improved by an elaborately-designed matrix-based chromosome representation is applied to represent all decision variables, as well as a sequential procedure generating initial solutions. Several test problems either generated randomly or taken from the literature with various sizes are solved and the results are compared with the solutions gained using CPLEX solver. The comparisons results show that the designed SA is capable of evolving optimal or near-optimal solutions with reasonable relative gaps in a computationally satisfactory manner.

Integrated dynamic cell formation with operator assignment and inter-cell layout problems: A mathematical model

2015 ◽  
Vol 231 (9) ◽  
pp. 1658-1669 ◽  
Author(s):  
Saeed Sadeghi ◽  
Mohammad Ali Forghani ◽  
Masoud Seidi
Keyword(s):  
Mathematical Model ◽  
Sensitivity Analysis ◽  
Manufacturing System ◽  
Cellular Manufacturing ◽  
Cell Formation ◽  
Cellular Manufacturing System ◽  
Numerical Examples ◽  
Proposed Model ◽  
Dynamic Cell ◽  
Operator Assignment

Designing a cellular manufacturing system involves four major decisions: cell formation, cellular layout, operator assignment and cellular scheduling which should be considered, simultaneously. This article presents a new mathematical model to solve the cell formation, operator assignment and inter-cell layout problems, concurrently. The objectives of proposed model are minimization of inter–intra cell part movements, machine relocation cost and operator-related issues including hiring, firing, training and salary costs. Two numerical examples in both small and large sizes are optimally solved by the Lingo software to verify and validate the proposed mathematical model. Also, a sensitivity analysis is performed to analyze the behavior of operators in different production periods.

Multioptimization in a Cellular Manufacturing System Having Stochastic Parameters Considering Pricing

2015 ◽  
Vol 15 (3) ◽  
pp. 257-265
Author(s):  
Reza Salarian ◽  
Hamed Fazlollahtabar
Keyword(s):  
Mathematical Model ◽  
Manufacturing System ◽  
Cellular Manufacturing ◽  
Search Algorithm ◽  
Heuristic Method ◽  
The Novel ◽  
Cellular Manufacturing System ◽  
Solution Approach ◽  
Processing Times ◽  
Stochastic Parameters

AbstractA mathematical model is developed to formulate a cellular manufacturing system with uncertain parameters. In this work, the processing times and demands are stochastic and estimated via expected value and standard deviation after sampling process. The objectives of the proposed mathematical model are to configure machines’ layout in cells so that the inter-cell and intra-cell movements are minimized, the bottlenecks are breakthrough and the profit is increased. Finally, the profit is maximized due to decreasing production cost. The applicability of the proposed mathematical program is illustrated using numerical examples. With respect to the large amount of computational efforts in larger sized problem, a heuristic methodology is developed as solution approach. The properties of the proposed heuristic method are the novel search algorithm and the allocation methodology.

scholarly journals A mathematical model in cellular manufacturing system considering subcontracting approach under constraints

2012 ◽  
Vol 2 (7) ◽  
pp. 2393-2408 ◽  
Author(s):  
Kamran Forghani ◽  
M.A. Sobhanallahi ◽  
A. Mirzazadeh ◽  
Mohammad Mohammadi
Keyword(s):  
Mathematical Model ◽  
Manufacturing System ◽  
Cellular Manufacturing ◽  
Cellular Manufacturing System
Sign in / Sign up

Export Citation Format

Share Document