Integration of cell formation and job sequencing to minimize energy consumption with minimum make-span

Abstract

Cell formation is the fundamental step while designing a cellular manufacturing system. Integration of job sequencing with cell formation can attain lower make-spans. The traditional cell formation and scheduling problems consider performance indicators such as productivity, time and flexibility in cellular manufacturing system; however, energy consumption has not been given due attention. Therefore, this research addressed the minimization of total energy consumption by implementing an energy-efficient schedule at the cell formation stage of cellular manufacturing system. For this purpose, a two-phase approach is proposed; in phase I, formation of independent cells is being carried out by considering energy-efficient routings and genetic algorithm is used for improving search performance. In phase II, a formulation is being developed to compute the total energy of the system based on optimal job sequence with respect to minimum idle running of the machines in each independent cell. For the proposed approach, a code is being developed in MATLAB software. Different sample problems have been evaluated. The results showed that the proposed approach is effective in generating independent cells and sequences with minimum energy consumption and make-span.

A new model and metaheuristic approach for the energy-based resource-constrained scheduling problem

“…like milling, turning, and drilling), the theoretical efficiency of an electric motor is the conversion of electrical energy into mechanical energy. This is represented by expression (8), where h is the efficiency, P mechanical represents the energy output from the motor shaft, and P electrical is the energy absorbed 31 h = P mechanical P electrical = P mechanical P mechanical + P losses ð8Þ…”

“…These problems have great importance in industry due to their applications in different fields such as production, distribution, transportation, project management, and supply-chain optimization in general. Currently, the research effort is focused on analyzing and developing new methodologies for the optimal allocation of resources to minimize both makespan and energy consumption [7,8].…”

“…Currently, the research effort is focused on analyzing and developing new methodologies for the optimal allocation of resources to minimize both makespan and energy consumption. 7,8…”

“…Currently, the research effort is focused on analyzing and developing new methodologies for the optimal allocation of resources to minimize both makespan and energy consumption. 7,8 In general, scheduling problems are combinatorial optimization problems. Therefore, relatively small instances are highly complex, with most of them being categorized as NP-hard (non-deterministic polynomialtime hard), such as the job shop scheduling problem (JSP), the flow shop scheduling problem (FSP), and the multi-mode resource-constrained project scheduling problem (MRCPSP).…”

A two-stage novel approach using centre ordering of vectors on agglomerative hierarchical clustering for manufacturing cell formation

“…A two-phase GA approach is applied to generate CF solution to minimize energy consumption and makespan from the generated independent cells. 15 Coextending, CF, operator assignment and inter-cell layout problems have been solved using a mathematical model to achieve minimum inter-intra cell transfer, machine relocation cost and problems related to operator hiring, layoff, training and salary costs. 16 A visual hierarchical clustering (HC) approach using growing hierarchical self-organizing map has been applied to solve CF problems.…”