An integrated mathematical model for production scheduling and preventive maintenance planning (original) (raw)
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Integrating Production Scheduling and Maintenance : Practical Implications
2012
This work discusses the integration of the scheduling decisions regarding production and maintenance operations for minimizing total cost of production including product holding cost and maintenance costs. Delays in production occur whenever the machine goes through preventive maintenance or corrective maintenance activities which in effect increases the total production cost. Preventive maintenance may be done between job processing with the purpose of reducing the chance of unplanned machine failures while processing a job. In this paper we discuss the case involving a single machine processing a number of jobs differing in processing time requirements. In practice, decisions regarding job scheduling are usually dealt with disjointly from maintenance related decisions and models that optimize such decisions are scarce in the literature. In this paper we present a modified version of the integrated model developed by Hadidi, et al. (2011) and demonstrate its utilization under vario...
An integrated cost model for production scheduling and perfect maintenance
International Journal of Mathematics in Operational Research, 2011
Production scheduling deals with scheduling production jobs on a machine (single or multiple) in order to optimise a specific objective such as total weighted completion times or total weighted tardiness. The assumption that machines are always available for processing jobs is generally used in the production scheduling literature. In reality, machines often are unavailable due to preventive maintenance activities or machine failure. Production scheduling and preventive maintenance planning are interrelated, but are most often treated separately. This interdependency seems to be overlooked in the literature. This work integrates, simultaneously, the decisions of preventive maintenance and job order sequencing for a single machine. The objective is to find the job order sequence and maintenance decisions that would minimise the expected cost.
Practical implications of managerial decisions to integrate production scheduling and maintenance
International Journal of System Assurance Engineering and Management, 2014
This work discusses the practical implications of managerial decisions to integrate the scheduling of production and maintenance operations. Integrating both decisions will assure minimizing product holding costs and maintenance costs. In this paper we discuss the case involving a single machine processing a number of jobs differing in processing time requirements. The machine goes through preventive maintenance or corrective maintenance activities which in effect increases the total production cost. We present a modified version of the integrated model developed by Hadidi (Int J Math Oper Res 3: 395-413, 2011) and demonstrate its utilization under various conditions to emphasize the practical implications of the model. In practice, managerial decisions are highly affected by the cost parameters of maintenance, correction and holding costs.
SCHEDULING OF PRODUCTION AND MAINTENANCE ACTIVITIES UNDER RELIABILITY CONSTRAINT
This paper deals with a joint scheduling of production and preventive maintenance activities in the justin-time context. We propose two mathematical models and a simulation model which are able to consider the maintenance and production views of a production system. The proposed models coordinate the two views so that the sum of maximum weighted earliness and tardiness cost is minimized. The mathematical models are evaluated on one machine/component subject to preventive maintenance without considering breakdowns. The simulation model is evaluated in the same context but is also able to take breakdowns into consideration. Thanks to its modular conception it is also able to easily consider several machines/components with no modification of its internal functioning. The dynamic aspects are modelled by a combination of timed petri-nets and PDEVS models and implemented in the VLE simulator.
International Journal of Production Research, 2018
The scheduling literature is extensive, but much of this work is theoretical and does not capture the complexity of real world systems. Capital goods companies produce products with deep and complex product structures, each of which requires the coordination of jobbing, batch, flow and assembly processes. Many components require numerous operations on multiple machines. Integrated scheduling problems simultaneously consider two or more simultaneous decisions. Previous production scheduling research in the capital goods industry has neglected maintenance scheduling and used metaheuristics with stochastic search that cannot guarantee an optimal solution. This paper presents a novel mixed integer linear programming (MILP) model for simultaneously solving the integrated production and preventive maintenance scheduling problem in the capital goods industry, which was tested using data from a collaborating company. The objective was to minimise total costs including: tardiness and earliness penalty costs; component and assembly holding costs; preventive maintenance costs; and setup, production, transfer and production idle time costs. Thus, the objective function and problem formulation were more extensive than previous research. The tool was successfully tested using data obtained from a collaborating company. It was found that the company's total cost could be reduced by up to 63.5%.
Since jobs scheduling becomes subject to both renewable and non-renewable resources at the same time and the production systems are characterised by random machine failures, multiple production criteria and the presence of uncertain events, selecting the most appropriate jobs to be executed and the optimal intervention date of maintenance actions becomes a critical issue and has a high impact on the system performance. In this context, this paper deals with the joint consideration of production scheduling and maintenance planning, in parallel machine environment under the resources constraints. We propose a new resolution strategy which allows the decision maker to find compromise solutions between the two services. The integrated strategy consists to establish an optimal number of preventive maintenance interventions in order to maximize the productivity of the system and to minimize the system unavailability. The simulation results show that the proposed integrated strategy improve the profitability and the performances of the system.
Proceedings of the 19th IFAC World Congress, 2014
In this paper, we deal with the problem of maintenance planning and production planning for a multiple-product manufacturing system. The manufacturing system under consideration consists of one machine which is subject to random failures and produces several products in order to satisfy some random demands. At any given time, the machine can only produce one type of product. The purpose of this study is to establish an economical production planning followed by an optimal maintenance strategy, taking into account the influence of production rate on the system degradation. Analytical models are developed in order to minimize sequentially the production/storage costs and the total maintenance cost. Finally, a numerical example is presented to illustrate the usefulness of the proposed approach.
Heuristic for production scheduling on job-shop plants considering preventive maintenance tasks
The simultaneous analysis of production scheduling and preventive maintenance task attracts special attention of researchers due to its complexity and therefore the necessity to seek efficient methods for solving this kind of combinatorial problems. This paper presents a heuristic approach to solve this issue on job shop plants. The solution method includes a linear programming model, based on the Traveling Salesman Problem, where the setup time is considered as distance measure. The method´s aim is to obtain a sequence of production orders and preventive maintenance tasks that reduce the idle time and the backlogs simultaneously, accomplishing the maintenance program. After finding an optimal solution for each machine a Correction Factor (CF) is determined as new distance measure. The CF considers the structure of the initial solution, the machine utilization and the product priorities. Then, the final solution is reached running the linear programming model using the distance updated values. Finally, the proposed heuristic is applied to real case study of the Cuban industry. The experimental results indicated a significant idle time reduction for the company under examination.
Integrated production planning and preventive maintenance in deteriorating production systems
Information Sciences an International Journal, 2008
This paper discusses the issue of integrating production planning and preventive maintenance in manufacturing production systems. In particular, it tackles the problem of integrating production and preventive maintenance in a system composed of parallel failure-prone production lines. It is assumed that when a production line fails, a minimal repair is carried out to restore it to an 'as-bad-as-old' status. Preventive maintenance is carried out, periodically at the discretion of the decision maker, to restore the production line to an 'as-good-as-new' status. It is also assumed that any maintenance action, performed on a production line in a given period, reduces the available production capacity on the line during that period. The resulting integrated production and maintenance planning problem is modeled as a nonlinear mixed-integer program when each production line implements a cyclic preventive maintenance policy. When noncyclical preventive maintenance policies are allowed, the problem is modeled as a linear mixed-integer program. A Lagrangian-based heuristic procedure for the solution of the first planning model is proposed and discussed. Computational experiments are carried out to analyze the performance of the method for different failure rate distributions, and the obtained results are discussed in detail.
A production and maintenance planning model for the process industry
International Journal of Production Research, 1996
In this paper a model is developed to simultaneously plan preventive maintenance and production in a process industry environment, where maintenance planning is extremely important. The model schedules production jobs and preventive maintenance jobs, while minimizing costs associated with production, backorders, corrective maintenance and preventive maintenance. The formulation of the model is flexible, so that it can be adapted to several production situations. The performance of the model is discussed and alternate solution procedures are suggested. − New production systems, like JIT, with minimum stocks of finished products and work-inprocess, have made interruptions to production costly. − Failure to deliver on time, with the possible loss of future business, may result from interruptions to operations. − Preventive maintenance or correction of defective conditions, not only decreases the cost of repairs but also maintains the quality and capacity of machinery. − Utility and service expenses for steam, electricity, gas, water, and the like are reduced by a continuous maintenance program. − Adequate planning of maintenance operations will insure that needed spare parts and materials are on hand.