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Master Production Scheduling
Published in Susmita Bandyopadhyay, Production and Operations Analysis, 2019
Master production scheduling (MPS) is a very critical and essential component of manufacturing planning and control. Master production schedule is a plan or schedule that is used to show when and how much of each product can be produced, based on the sales and inventory, in order to meet the customer demand. Some of the significant reasons for which MPS is required can be one or more of the following: High material handling costProduction disruptions due to delay in deliveries from suppliersDissatisfied customers due to delay in delivering finished productLarger-than-required work-in-progressIncreasing past duesIncreasing frequency of changing schedulesProblems faced in the shop floor because of material delays or other reasonsProblems arisen due to long queues in the manufacturing shop floor
A Case Study on the Theory of Constraints
Published in Bob Sproull, Theory of Constraints, Lean, and Six Sigma Improvement Methodology, 2019
This company was using a form of Enterprise Resource Planning (ERP) to schedule their production, but they weren’t very successful using it. ERP systems are supposed to help a business by providing a common set of tools that can be used across an enterprise to both plan for and control the execution of actions at each resource. Scheduling in an ERP system begins with an order due date and then attempts to start as late as possible while still meeting the date or it starts with today and tries to complete the work as soon as possible, which often times is well before the due date. Typically, scheduling through a manufacturing plant uses production rates and times or units of production capacities to schedule each resource. I mention this point early on because we modified this company’s ERP system to merge with another scheduling mechanism known as Drum-Buffer-Rope from the Theory of Constraints. We will cover this merger later in the chapter.
Introduction to Batch Processes
Published in Thokozani Majozi, Esmael R. Seid, Jui-Yuan Lee, Understanding Batch Chemical Processes, 2017
Thokozani Majozi, Esmael R. Seid, Jui-Yuan Lee
Batch processes differ from continuous processes in several ways. The main difference is that time is inherent in batch processes. In batch processes, every task has a definite duration with starting and finishing times, whereas in continuous processes, time is important during non-steady-state operation. As a result, scheduling of batch processes is vital to the operation of any batch facility. Furthermore, in batch plants, detailed requirements for the various products may be specified on a day-to-day basis. A production schedule must indicate the sequence and manner in which the products are to be produced and specify the times at which the process operations are to be carried out. It is clear that the overall productivity and economic effectiveness of batch plants depend critically on the production schedule as it harmonizes the entire plant operation to attain production goals. While flexibility of batch plants improves productivity, it also makes plant scheduling a challenging task. Much research has focused on developing optimization techniques for scheduling batch plants with the aim of reducing the CPU time required to attain the optimal objective value.
Effectiveness of nervousness reduction policies when capacity is constrained
Published in International Journal of Production Research, 2020
Sukran N. Atadeniz, Sri V. Sridharan
One known weakness of MRP systems is their tendency to produce nervous schedules, especially when faced with demand and/or supply uncertainties. Schedule changes are often initiated in response to uncertainties in demand such as when the actual demand deviates from the forecast. Likewise, uncertainty in supply due to scrap losses, production overruns, variations in vendor lead times, variations in shop flow times, machine breakdowns, and tooling problems may also necessitate schedule changes. Nervousness (i.e. excessive changes in production plans) impedes the successful execution of production schedules. Some of the undesirable effects of nervousness are increased global costs, reduced productivity, low morale, and lower customer service levels (Campbell 1971; Hayes and Clark 1985; Newman and Sridharan 1992; Law 2011; Pujawan and Smart 2012; Herrera et al. 2016).
Multi-product continuous plant scheduling: combination of decomposition, genetic algorithm, and constructive heuristic
Published in International Journal of Production Research, 2020
Pavel Borisovsky, Anton Eremeev, Josef Kallrath
Scheduling the processes of an industrial plant involves a large number of objects such as processing units, tasks, intermediate and final products (states) and a set of complex relations between them. The production scheduling problem basically consists in selection of a set of tasks to be performed and construction of a schedule complying with the technological requirements and satisfying as much as possible the given demands for a final production. The real-life production scheduling problems may encompass many specific technological and business requirements such as due dates, sequence dependent changeovers, unit blockages, etc. (Kallrath 2002). The great variety of problem formulations makes it hardly possible to use any unified method for their solution. The widely used mixed integer linear programming (MILP) approach provides a good tool for mathematical modelling, but NP-hardness of majority of these problems and the large scale that usually reaches dozens of units and hundreds of products gives very little chance to solve them optimally with the existing optimisation software. This fact confirms the interest in development of problem specific algorithms that allow to find at least feasible solutions with practically acceptable quality in reasonable time.
Production improvement with flow shop scheduling heuristics in Household utensils manufacturing company
Published in Cogent Engineering, 2018
Micheal G. Wolde, Eshetie Berhan, Kassu Jilcha
Manufacturing industries sustainability is determined by their competitiveness in the market. To maintain competitiveness their products should be delivered adequately, with best quality, minimum time and price to customers. In order to do so a manufacturing company needs optimized production line. Optimized production line will have a minimum manufacturing time. Minimum manufacturing time can be attained through an optimal production sequences (production sequences with minimum makespan value or completion time), that suits well with the production environment constraints. In this study, the objective is to improve the production capacity through flow shop scheduling heuristics. Scheduling determines the optimum sequence of n-jobs to be processed on m-machines. In scheduling, it is necessary to consider the production line constraints such as machines breakdown and processing time of specific jobs on machines. The case company has been functioning for several years without systematically scheduling the jobs based on the production environment constraints; as a result, they arbitrarily assigned the n-jobs to the m-machines. But, a good production schedule enhances production and machine utilization, improves production planning and control, reduces production cost, increases customer satisfaction, supports maintenance planning, and keeps a firm competitive advantage.