For flexible manufacturing systems, there are normally some durations in which a number of machines are idle and do not process any parts. Devising a control policy to turn off the idle machines and reduce their level of energy consumption is a significant contribution towards the green manufacturing paradigm. This paper addresses the design of such a control strategy for a closed-loop flow shop plant based on a one-loop pallet system. The main goal is to coordinate running of the machines and motion of pallets to gain the minimal energy consumption in idle machines, as well as to obtain the desired throughput for the plant. To fulfill this goal, first mathematical conditions, which economically characterize the on-off control for machines, are presented. Constrained to these conditions and the mathematical models describing the pallet system, a mixed integer nonlinear minimization problem with the energy monitor as the objective function is then developed. Provided that the problem computation time can be managed, the optimal control for the operation of the plant and the minimal energy consumption in the idle machines are computed. To deal with the time complexity, a linearized form of the model and a heuristic approach are introduced. These methods are applied to some examples of industrial size, and their impacts in practice are discussed and verified by using a discrete event simulation tool.Note to Practitioners-Control of a flexible manufacturing plant in order to produce a set of part types in a determined production cycle time is a challenging problem. In addition, the problem is more complicated if energy efficiency is considered as an important key in the plant control design. This study provides methods which tackles this complex problem for an industrial size of a pallet-constrained flow shop. The outcome is an optimal switching control strategy, which reduces energy consumption for idle processing machines and maintains a desired throughput for the flow shop plant.Index Terms-Energy model, flow shop plant, heuristic algorithm, optimization, pallet system.
Reduction of energy consumed by a manufacturing system to turn raw parts to finished products is a big step towards the green and lean production. In this study the energy efficiency of a one-loop pallet system, a main tool to handle and locate various part types in a cyclic production line, is investigated. The main goal is to obtain the minimal energy consumption in the pallet system drive unit through an optimally controlled and coordinated motion of pallets. To achieve the mentioned goal, first the mean value of the pallet system energy consumption is mathematically modeled. Later, this energy model is utilized as an objective function within an optimization model including constraints on system crucial properties such as cyclic and dynamic behavior, queueing policy, and buffer size. The solution of the optimization problem gives the optimal values of the system control variables, namely, number of pallets and conveyor velocity. To demonstrate the application of this optimization model in practice, three case studies are introduced. The results of these studies show that a significant amount of the energy consumption may be saved by applying the suggested green control.
A proper control of a system to get a desired function and increase the system lifetime is a crucial step towards the sustainable paradigm. In this paper, such a control is designed for a cyclic pallet system to achieve a minimal force on its drive unit, meet safety conditions on the system chain tension force and the momentum of pallets, and fulfill the desired production rate. The optimal values of the control parameters, namely number of pallets and conveyor velocity, are obtained through solving a linear optimization model. The objective function in the model defines the average force on the drive unit in a cycle production. In addition, the related constraints characterize the pallet system properties such as cyclic and dynamic behavior, buffer size, constant work in process, and safety specifications. The robustness of the optimal control is analyzed, using a worst but safe control strategy. The optimal control and the robustness analysis are applied to some case studies, and the results are evaluated and discussed.
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