Single machine scheduling problem with two synergetic agents and piece-rate maintenance

This paper attempts to study on the single machine scheduling problems with two synergetic agents, each has a set of nonpreemptive jobs and a regular objective function depending on the completion times of its jobs only. It is not only necessary to satisfy the constraints of each agents objective function, it is necessary to minimize an aggregate increasing objective function of two agents’ objective function. Furthermore, this paper proposes a new kind of machine maintenance: piece-rate maintenance, which depicts the scenario that machine maintenance is implemented once every a fixed number of jobs is completed. Hence, it explores into the single machine scheduling problems with two synergetic agents and piece-rate maintenance. If the regular objective function of each job is polynomial, it can be observed that these problems are all polynomially solvable.     

Optimal replacement policies for two-unit machines with increasing running costs 1

A machine consists of two stochastically failing units. Failure of either of the units causes a failure of the machine and the failed unit has to be replaced immediately. Associated with the units are running costs which increase with the age of the unit because of increasing maintenance costs, decreasing output, etc.A preventive replacement policy is proposed under which, at failure points, we also replace the second unit if its age exceeds a predetermined control limit. It is proved that, for two identical units with exponential life-time distributions and linear running costs, this policy is optimal and the optimal control limit is calculated. In an additional model we take into consideration the length of time it takes to replace one unit or both units.The method of solution is a variation of dynamic semi-Markov programming. Analytical results are obtained and the influence of the various parameters on them is investigated. Finally, we study the saving due to our policy in comparison with a policy in which only failed units are replaced.     

COLLECTIVE DECISION MAKING IN AN INTERNATIONAL RIVER POLLUTION MODEL

In this paper, we study international river pollution problems. We introduce a model in which countries located along a river from upstream to downstream derive benefits from causing pollution, but also incur environmental costs from experiencing its own pollution and the pollution of all its upstream countries. The total welfare, being the sum of all benefits minus the sum of all costs, is maximized when all countries cooperate. Several principles from international water law are applied to find reasonable and fair distributions of the total welfare that can be obtained under full cooperation. Such a distribution of the welfare at efficient pollution levels can be implemented by monetary compensations.     

Contribution of simulation to the optimization of maintenance strategies for a randomly failing production system

This paper compares two strategies for operating a production system composed of two machines working in parallel and a downstream inventory supplying an assembly line. The two machines, which are prone to random failures, undergo preventive and corrective maintenance operations. These operations with a random duration make the machines unavailable. Moreover, during regular subcontracting operations, one of these machines becomes unavailable to supply the downstream inventory. In the first strategy it is assumed that the periodicity of preventive maintenance operations and the production rate of each machine are independent. The second strategy suggests an interaction between the periods of unavailability and the production rates of the two machines in order to minimize production losses during these periods. A simulation model for each strategy is developed so as to be able to compare them and to simultaneously determine the timing of preventive maintenance on each machine considering the total average cost per time unit as the performance criterion. The second strategy is then considered, and a multi-criteria analysis is adopted to reach the best cost-availability compromise.     

Age-dependent production planning and maintenance strategies in unreliable manufacturing systems with lost sale

In this paper, we formulate an analytical model for the joint determination of an optimal age-dependent buffer inventory and preventive maintenance policy in a production environment that is subject to random machine breakdowns. Traditional preventive maintenance policies, such as age and periodic replacements, are usually studied based on simplified and non-realistic assumptions, as well as on the expected costs criterion. Finished goods inventories and the age-dependent likelihood of machine breakdowns are usually not considered. As a result, these policies could significantly extend beyond the anticipated financial incomes of the system, and lead to crises. In order to solve this problem, a more realistic analysis model is proposed in this paper to consider the effects of both preventive maintenance policies and machine age on optimal safety stock levels. Hence, a unified framework is developed, allowing production and preventive maintenance to be jointly considered. We use an age-dependent optimization model based on the minimization of an overall cost function, including inventory holdings, lost sales, preventive and corrective maintenance costs. We provide optimality conditions for the manufacturing systems considered, and use numerical methods to obtain an optimal preventive maintenance policy and the relevant age-dependent threshold level production policy. In this work, this policy is called the multiple threshold levels hedging point policy. We include numerical examples and sensitivity analyses to illustrate the importance and the effectiveness of the proposed methodology. Compared with other available optimal production and maintenance policies, the numerical solution obtained shows that the proposed age-dependent optimal production and maintenance policies significantly reduce the overall cost incurred.     

Evaluation of Transport Costs for Alternative Factory Sites — A Case Study

The problem of siting one or more factories so as to minimize transport costs is considered in the context of other factors of interest to management. The method of solution is described. This involved the solution of simple transportation problems, the determination of rules by which costs could be computed, the construction of an analogue machine to assist with the problem of site selection and the writing of a programme for a digital computer to cope with the heavy load of calculation. The way in which the work of the operational research team was organized to meet a deadline is described and a number of technical difficulties are discussed. The solution consisted of the presentation of minimum transport costs for each of a large number of possible combinations of factories so that management could assess the relative importance of transport costs together with other factors when deciding where to build factories for the manufacture of a new product.     

Cooperation in assembly systems: The role of knowledge sharing networks

Process improvement plays a significant role in reducing production costs over the life cycle of a product. We consider the role of process improvement in a decentralized assembly system in which a buyer purchases components from several first-tier suppliers. These components are assembled into a finished product, which is sold to the downstream market. The assembler faces a deterministic demand/production rate and the suppliers incur variable inventory costs and fixed setup production costs. In the first stage of the game, which is modeled as a non-cooperative game among suppliers, suppliers make investments in process improvement activities to reduce the fixed production costs. Upon establishing a relationship with the suppliers, the assembler establishes a knowledge sharing network – this network is implemented as a series of meetings among suppliers and also mutual visits to their factories. These meetings facilitate the exchange of best practices among suppliers with the expectation that suppliers will achieve reductions in their production costs from the experiences learned through knowledge sharing. We model this knowledge exchange as a cooperative game among suppliers in which, as a result of cooperation, all suppliers achieve reductions in their fixed costs. In the non-cooperative game, the suppliers anticipate the cost allocation that results from the cooperative game in the second stage by incorporating the effect of knowledge sharing in their cost functions. Based on this model, we investigate the benefits and challenges associated with establishing a knowledge sharing network. We identify and compare various cost allocation mechanisms that are feasible in the cooperative game and show that the system optimal investment levels can be achieved only when the most efficient supplier receives the incremental benefits of the cost reduction achieved by other suppliers due to the knowledge transfer.     

Fuzzy extensions to Integer Programming models of cell-formation problems in machine scheduling

Cell formation has received much attention from academicians and practitioners because of its strategic importance to modern manufacturing practices. Existing research on cell formation problems using integer programming (IP) has achieved the target of solving problems that simultaneously optimise: (a) cell formation, (b) machine-cell allocation, and (c) part-machine allocation. This paper will present extensions of the IP model where part-machine assignment and cell formation are addressed simultaneously, and also a significant number of constraints together with an enhanced objective function are considered. The main study examines the integration of inter-cell movements of parts and machine set-up costs within the objective function, and also the combination of machine set-up costs associated with parts revisiting a cell when part machine operation sequence is taken into account. The latter feature incorporates a key set of constraints which identify the number of times a part travels back to a cell for a later machine operation. Due to two main drawbacks of IP modelling for cell formation, i.e. (a) only one objective function can be involved and (b) the decision maker is required to specify precisely goals and constraints, fuzzy elements like fuzzy constraints and fuzzy goals will be considered in the proposed model. Overall the paper will not only include an extended and enhanced integer programming model for assessing the performance of cell formation, but also perform a rigorous study of fuzzy integer programming and demonstrate the feasibility of achieving better and faster clustering results using fuzzy theory.     

Decision Techniques for Town Development

Town development is a complex process which has wide physical, social and economic consequences. Its impact varies as between private and public developers and the community at large, and it is a potent source of conflict. Techniques are needed to evaluate the consequences of decisions in this field from the various points of view. There is a need both for evaluating alternative solutions to the same problem and for evaluating alternative ways of investing the same resources. Decisions about town development involve the trinity of appearance, amenity and costs. It is easier to reach rational decisions when the consequences of alternative choices have been quantified than when they consist of a large number of factors relating to separate attributes, some of which are qualitative. It is necessary to understand the conflicts of interest, to evaluate the social and economic benefits and to provide indicators which measure the balances of advantage between alternative policies.Town development is a long-term and enduring process. Both its costs and benefits are spread over long periods of time and evaluation of its consequences can only be based on predictions. Many of the costs and benefits are indirect and frequently suitable cost data are not available; special cost studies are often necessary to enable the consequences to be evaluated. Many of the benefits are, of course, a matter of opinion, but some benefits can be evaluated by experienced observers, although even then there are still problems of weighting; in some other cases the benefits can be quantified by using indirect measures. Because costs and benefits are spread over time, values must be discounted, the possible effects on the decision of the rate chosen must be studied.Broadly, there are two methods of summarizing the results of the analysis, “costs in use” based on balance sheets for comparing alternative means to the same end and “cost-benefit ratio” for investment type problems. The latter technique is related in some forms to business investment choice techniques. These techniques have a value in many fields in addition to their use in town development.     

Data-driven preventive maintenance for a heterogeneous machine portfolio

We describe a data-driven approach to optimize periodic maintenance policies for a heterogeneous portfolio with different machine profiles. When insufficient data are available per profile to assess failure intensities and costs accurately, we pool the data of all machine profiles and evaluate the effect of (observable) machine characteristics by calibrating appropriate statistical models. This reduces maintenance costs compared to a stratified approach that splits the data into subsets per profile and a uniform approach that treats all profiles the same.     

带有机器维修和两车辆派送的单机排序问题

研究了带有机器维修和工件派送的单机排序问题,该问题可以被视为一个集成生产和出站配送的排序模型。不同体积的工件需要在带有一个维修区间的机器上加工,且加工不可中断,然后由固定容量的两辆同类车批次交付给单客户,目标函数是极小化最大完工时间,本文提出了2-近似算法,并证明了2是紧界。     

基于成本优先级的部件维修策略分析

现实中,系统由于任务、环境等因素,无法实时对故障部件进行维修。因此需要在任务间隔期间或对故障部件进行维修的同时对系统各部件进行预防性机会维修。本文考虑系统期望维修成本,提出了基于部件维修优先级的预防性维修策略。首先把系统期望维修成本分为失效部件维修成本、失效部件导致系统故障的成本和预防性维修其他部件的成本,提出了基于成本的二态和多态系统部件维修优先级度量方法,并在两种场景下分析了如何选择预防性维修部件。其次针对多态系统,研究了基于成本重要度的部件最佳维修水平,并讨论了成本约束下的部件预防性维修策略。最后以某型预警机系统为例进行验证,结果表明,基于成本的预防性维修策略不仅与故障部件位置和相关成本有关,而且还与可用于预防性维修的其他部件重要性有关。     

CFD modelling of thickeners at Worsley Alumina Pty Ltd

Computational fluid dynamics (CFD) modelling of process unit operations is a tool that is being used increasingly by mineral processing industries to reduce operating and capital costs and increase throughputs.Worsley Alumina first became involved with CFD modelling through support of the AMIRA Thickener Technology Project 266A in 1994, and subsequent extension projects in which CSIRO has been developing validated CFD models of thickener operation. The CSIRO Division of Minerals has been involved with CFD modelling since 1984 mainly on high temperature furnace applications and has been developing multi-phase thickener models since 1992. The benefits of obtaining a better understanding of flow patterns in thickeners using this modelling method became obvious and projects commenced in the third quarter of 1995 to utilise the CSIRO expertise. Projects have been ongoing almost continuously since that time. The CFD modelling was verified using tracers to measure actual flow patterns in a settler. Once verification had been achieved the CFD model was used to test innovative changes in design aimed at achieving higher throughputs and improved operation. These innovative changes when implemented on the full plant gave results similar to the CFD model predictions and resulted in improved process stabilisation, reduced chemical costs and very large savings in capital requirements for our major expansion that has just been completed. There are a number of assumptions made in the CFD model and these are discussed in detail in the paper together with details of individual CFD modelling projects and cost benefits achieved from completed projects.     

Discrete time model for two-machine one-buffer transfer lines with restart policy

The paper deals with analytical modeling of transfer lines consisting of two machines decoupled by one finite buffer. In particular, the case in which a control policy (referred as “restart policy”) aiming to reduce the blocking frequency of the first machine is addressed. Such a policy consists of forcing the first machine to remain idle (it cannot process parts) each time the buffer gets full until it empties again. This specific behavior can be found in a number of industrial production systems, especially when some machines are affected by outage costs when stops occur. The two-machine one-buffer line is here modeled as a discrete time Markov process and the two machines are characterized by the same operation time. The analytical solution of the model is obtained and mathematical expressions of the most important performance measures are provided. Some significant remarks about the effect of the proposed restart policy on the behavior of the system are also pointed out.     

Metaheuristic algorithms for balancing robotic assembly lines with sequence-dependent robot setup times

Industries are incorporating robots into assembly lines due to their greater flexibility and reduced costs. Most of the reported studies did not consider scheduling of tasks or the sequence-dependent setup times in an assembly line, which cannot be neglected in a real-world scenario. This paper presents a study on robotic assembly line balancing, with the aim of minimizing cycle time by considering sequence-dependent setup times. A mathematical model for the problem is formulated and CPLEX solver is utilized to solve small-sized problems. A recently developed metaheuristic Migrating Birds Optimization (MBO) algorithm and set of metaheuristics have been implemented to solve the problem. Three different scenarios are tested (with no setup time, and low and high setup times). The comparative experimental study demonstrates that the performance of the MBO algorithm is superior for the tested datasets. The outcomes of this study can help production managers improve their production system in order to perform the assembly tasks with high levels of efficiency and quality.     

Balancing Workloads and Minimizing Set-up Costs in the Parallel Processing Shop

This paper presents an optimal scheduling algorithm for minimizing set-up costs in the parallel processing shop while meeting workload balancing restrictions.There are M independent batch type jobs which have sequence dependent set-up costs and N parallel processing machines. Each of the M jobs must be processed on exactly one of the N available machines. It is desirable to minimize total changeover costs with the restriction that each machine workload assignment T _n be within P units of the average machine assignment. The paper describes a static problem in which all jobs are available at time zero. The sequence dependent change over costs are identical for each machine. An extension of the algorithm handles nonidentical processor problems.A combinatorial programming approach to the problem is used. For the special case of identical processors, the problem can be treated as a multi-salesman travelling salesman problem. A general branch and bound algorithm and numerical results are given.     

An integrated production and preventive maintenance planning model

We are given a set of items that must be produced in lots on a capacitated production system throughout a specified finite planning horizon. We assume that the production system is subject to random failures, and that any maintenance action carried out on the system, in a period, reduces the system’s available production capacity during that period. The objective is to find an integrated lot-sizing and preventive maintenance strategy of the system that satisfies the demand for all items over the entire horizon without backlogging, and which minimizes the expected sum of production and maintenance costs. We show how this problem can be formulated and solved as a multi-item capacitated lot-sizing problem on a system that is periodically renewed and minimally repaired at failure. We also provide an illustrative example that shows the steps to obtain an optimal integrated production and maintenance strategy.     

Pooling of spare parts between multiple users: How to share the benefits?

Companies that maintain capital goods (e.g., airplanes or power plants) often face high costs, both for holding spare parts and due to downtime of their technical systems. These costs can be reduced by pooling common spare parts between multiple companies in the same region, but managers may be unsure about how to share the resulting costs or benefits in a fair way that avoids free riders. To tackle this problem, we study several players, each facing a Poisson demand process for an expensive, low-usage item. They share a stock point that is controlled by a continuous-review base stock policy with full backordering under an optimal base stock level. Costs consist of penalty costs for backorders and holding costs for on-hand stock. We propose to allocate the total costs proportional to players’ demand rates. Our key result is that this cost allocation rule satisfies many appealing properties: it makes all separate participants and subgroups of participants better off, it stimulates growth of the pool, it can be easily implemented in practice, and it induces players to reveal their private information truthfully. To obtain these game theoretical results, we exploit novel structural properties of the cost function in our (S − 1, S) inventory model.     

Optimal design of unreliable production–inventory systems with variable production rate

In this article, we study an economic manufacturing quantity (EMQ) problem for an unreliable production facility where the production rate is treated as a decision variable. As the stress condition of the machine changes with the production rate, the failure rate of the machine is assumed to be dependent on the production rate. The unit production cost is also taken as a function of the production rate, as the machine can be operated at different production rates resulting in different unit production costs. The basic EMQ model is formulated under general failure and general repair time distributions and the optimal production policy is derived for specific failure and repair time distributions viz., exponential failure and exponential repair time distributions. Considering randomness of the time to machine failure and corrective repair time, the model is extended to the case where certain safety stocks in inventory may be useful to improve service level to customers. Optimal production policies of the proposed models are derived numerically and the sensitivity of the optimal results with respect to those parameters which directly influence the machine failure and repair rates is also examined.     

On a periodic maintenance problem

In this paper, a machine maintenance problem, in which n machines are to be served on a regular, periodic basis, is studied. In particular, we are interested in how the maintenance cycles of the machines can be initiated so that all service requirements can be fulfilled by k servers.