Production planning and inventory allocation of a single-product assemble-to-order system with failure-prone machines

We consider the optimal production and inventory allocation of a single-product assemble-to-order system with multiple demand classes and lost sales. Each component is replenished by a dedicated machine that is subjected to unpredictable breakdowns. We find that the machine state not only influences the production and allocation decisions on its own component but also influences the decisions on the other components. Specifically, the optimal component production policy is a base-stock policy with the base-stock level non-decreasing in the inventory levels of the other components and the states of the other machines. The optimal component allocation policy is a rationing policy with the rationing level non-increasing in the inventory levels of the other components, the states of the other machines, and its own machine state. We use an exponential distribution to approximate the distribution of the total processing times and propose two heuristic policies to address the production and allocation decisions. The importance of taking machine failures into consideration is revealed through computational experiments.     

Fuzzy multi-criteria decision model for evaluating reconfigurable machines

The design and configuration of manufacturing equipment require crucial decision considering optimum capacity and functionality. The equipment selection problem might be involved with choosing between large-capacity machines versus a greater number of machines with smaller capacities, and/or dedicated facilities versus multi-product facilities. This paper investigates reconfigurable machining system characteristics in order to identify the crucial factors influencing the machine selection and the machine (re)configuration. Furthermore, changeover cost and changeover time while switching from one product to the other are taken into account. In particular, a fuzzy analytical hierarchical process (FAHP) model is proposed to integrate the decisive factors for the equipment selection process under uncertainty. The expected values of the normalised fuzzy sets are determined to identify the preference values of the alternative machines. The fuzzy multi-criteria model is analysed within the fuzzy domains of the operational characteristics along with economic, quality and performance criteria. The proposed model is examined using monitoring sensitivity analysis through a case study. As a result, the alternative machines are prioritised with consideration of the inconsistency ratios. The relative performances of the alternative equipment in view of interactions of process reconfigurability and cost, and capacity and functionality are graphically illustrated.     

Machine repairing models for production systems

In this paper we consider manufacturing systems of m identical unreliable machines producing one type of product. The operating time of each machine is exponentially distributed. The repairing process of a machine requires more than one phase. In each phase, the repair time is exponentially distributed and more than one operator may be required for fixing a broken machine. Here we consider two models of manufacturing systems. In the first model, there are r operators assigned in one server to repair a broken machine. The repairing rate in each phase depends on the number of operators there. This is a generalized model discussed in Buzacott and Shanthikumar [11]. We then consider a two-phase repairing model. Two groups of operators are assigned in the two phases. Each operator can handle one broken machine in each phase individually. This model is a generalization of Eben–Chaime's model [8]. Average profits are derived for both models and can be optimized by suitable allocation of the number of machines and operators in the systems.     

A mathematical programming approach to evaluating alternative machine clusters in cellular manufacturing

Cellular manufacturing systems achieve the economies of scope and scale approaching that of flexible and high-volume production when the machine/part clusters are totally independent of each other. However, most real systems contain bottleneck machines and exceptional parts (exceptional elements) that reduce these economies. Many grouping methods have been proposed for creating the initial machine/part cells where the presence of exceptional elements may greatly affect their performance. Furthermore, multiple alternative solutions are often possible for a given grouping algorithm. In this paper, the previous work dealing with exceptional elements is reviewed. A mathematical programming model used for comprehensively dealing with exceptional elements is investigated. The effect of alternative initial machine/part clusters on the total cost is evaluated. It is demonstrated that the mathematical programming model can provide useful information in making trade-off decisions when exceptional elements are present.     

A hybrid approach based on the variable neighborhood search and particle swarm optimization for parallel machine scheduling problems—A case study for solar cell industry

This paper studies a solar cell industry scheduling problem which is similar to the traditional hybrid flow shop scheduling (HFS). In a typical HFS with parallel machines problem, the allocation of machine resources for each order should be scheduled in advance and then the optimal multiprocessor task scheduling in each stage could be determined. However, the challenge in solar cell manufacturing is the number of machines can be dynamically adjusted to complete the job within the shortest possible time. Therefore, the paper addresses a multi-stage HFS scheduling problem with characteristics of parallel processing, dedicated machines, sequence-independent setup time, and sequence-dependent setup time. The objective is to schedule the job production sequence, number of sublots, and dynamically allocate sublots to parallel machines such that the makespan time is minimized. The problem is formulated as a mixed integer linear programming (MILP) model. A hybrid approach based on the variable neighborhood search and particle swarm optimization (VNPSO) is developed to obtain the near-optimal solution. Preliminary computational study indicates that the developed VNPSO not only provides good quality solutions within a reasonable amount of time but also outperforms the classic branch and bound method and the current industry heuristic practiced by the case company.     

Digital Machines,Space, and Time: Towards a Behavioral Perspective of Flexible Manufacturing

Recently, the diffusion of digital machines has further enhanced firms’ manufacturing flexibility, but also opened questions on potential challenges and implications in the production process. To respond to these timely issues, this study adopts a behavioral perspective and comparatively explores how four different types of digital machines—characterized by increasing degrees of manufacturing flexibility—affect the perception and use of space and time for routines within the production plant. To this end, 45 digital manufacturing machines, sampled across 14 firms in the British and Italian motorsport industry, were qualitatively observed and compared. A model emerges where four key mechanisms reshape (1) the interactive space around the machine, (2) the innovation activities performed in the machine space, (3) the time within activities involving the machine, and (4) the time perception. Such mechanisms mediate the relationship between manufacturing flexibility and firm performance. Further, data show how increasing digitalization in the manufacturing process enhances the establishment of new routines as flexible machines get introduced in the production. Finally, theoretical and practical implications related to fostering a behavioral perspective in innovation and operations management studies are discussed.     

Integrating noncyclical preventive maintenance scheduling and production planning for a single machine

This paper deals with the problem of integrating noncyclical preventive maintenance and tactical production planning for a single machine. We are given a set of products that must be produced in lots during a specified finite planning horizon. The maintenance policy suggests possible preventive replacements at the beginning of each production planning period, and minimal repair at machine failure. The proposed model determines simultaneously the optimal production plan and the instants of preventive maintenance actions. The objective is to minimize the sum of preventive and corrective maintenance costs, setup costs, holding costs, backorder costs and production costs, while satisfying the demand for all products over the entire horizon. The problem is solved by comparing the results of several multi-product capacitated lot-sizing problems. The value of the integration and that of using noncyclical preventive maintenance when the demand varies from one period to another are illustrated through a numerical example and validated by a design of experiment. The later has shown that the integration of maintenance and production planning can reduce the total maintenance and production cost and the removal of periodicity constraint is directly affected by the demand fluctuation and can also reduce the total maintenance and production cost.     

U-shaped production lines: A review of theory and practice

Most writers describe the U-shaped production line as the special type of cellular manufacturing used in just-in-time (JIT) production systems. JIT is defined to be an umbrella term for a number of techniques whose purpose is to improve product quality and cost by eliminating all waste in the production system. The U-line arranges machines around a U-shaped line in the order in which production operations are performed. Operators work inside the U-line. One operator supervises both the entrance and the exit of the line. Machine-work is separated from operator-work so that machines work independently as much as possible. Standard operation charts specify exactly how all work is done. U-lines may be simple or complex. U-lines are rebalanced periodically when production requirements change. The U-line satisfies the flow manufacturing principle. This requires operators to be multi-skilled to operate several different machines or processes. It also requires operators to work standing up and walking. When setup times are negligible, U-lines are operated as mixed-model lines where each station is able to produce any product in any cycle. When setup times are larger, multiple U-lines are formed and dedicated to different products. 114 US and Japanese U-lines are examined in this study. The average U-line has 10.2 machines and 3.4 operators. About one-quarter of all U-lines are manned by one operator and so run in chase mode. The reported benefits are impressive. Productivity improved by an average of 76%. WIP dropped by 86%. Leadtime shrunk by 75%. Defective rates dropped by 83%.     

PVC手套生产线手模温度在线测量的研究与应用

为了解决PVC手套生产过程中手模温度在线测量难题,开发出一套移动物体在线测温装置。该装置安装红外测温传感器,采用PLC控制的同步跟踪技术对生产线手模进行跟踪,保证红外测温传感器和手模同步并正确测量其温度。用组态软件kingview开发出手模温度在线测量的监控界面,对手模温度进行实时监控。实验结果显示该装置运行稳定,采集的温度可靠。     

A Solution Methodology for Probabilistic Capital Budgeting Problems Using Complex Utility Functions

Historically, the study of economic equipment replacement is primarily limited to that of a single machine or a single machining system. The replacement situation whereby machines under consideration are part of a large integrated system has received little attention. This paper proposes a framework, for the analysis of multiple-machine replacement within an integrated system context. The major difficulty of analyzing such a problem lies in the interactive nature of an integrated system; that is, how should the effects to the entire system be assessed as a result of alterations to one or more of its components. The emphasis of this work is on the issues regarding multiple machine replacement. A single-period model is utilized in order to simplify the presentation. A comprehensive example is also provided for illustration.     

Scheduling a single batch processing machine with arbitrary job sizes and incompatible job families

Motivated by a bottleneck operation in a multi-layer ceramic capacitor production line, we study a scheduling problem of batch processing machine in which a number of jobs are processed simultaneously as a batch. The performance measures considered include makespan, total completion time, and total weighted completion time. We first present a new simple integer programming formulation for the problem, and using this formulation, one can easily find optimal solutions for small problems. However, since the problem is NP-hard and the size of a real problem is very large, we propose a number of heuristic algorithms and design a hybrid genetic algorithm to solve practical big-size problems in a reasonable computational time. To verify performance of the algorithms, we compare them with lower bounds for the problems. From the results of these computational experiments the heuristic algorithms including the genetic algorithm show different performances for the three problems.     

Using a mathematical programming model to examine the marginal price of capacitated resources

Accurate information on dual prices of capacitated resources is of interest in a number of applications, such as cost allocation and pricing. To gain insight we focus on the dual prices of capacity and demand in a single-stage single-product production-inventory system, and discuss their interpretation. In particular, we examine the behavior of two different production planning models: a conventional linear programming model and a nonlinear model that captures queuing behavior at resources in an aggregate manner using nonlinear clearing functions. The classical linear programming formulation consistently underestimates the dual price of capacity due to its failure to capture the effects of queuing. The clearing function formulation, in contrast, produces positive dual prices even when utilization is below one and exhibits more realistic behavior, such as holding finished inventory at utilization levels below one.     

Rising real wages,mechanization and growing advantage of large farms: Evidence from Indonesia

This paper examines dynamic patterns of land use, capital investments and wages in agriculture using farm panel data from Indonesia. The empirical analysis shows that with an increase in real wages that prevailed in both agricultural and non-agricultural sectors in rural areas, relatively larger farmers increased the size of operational farm land by renting in land as well as used more hired-in machines through machine rental and/or service providers, which induces the substitution of labor by machines. Machines and land are complementary and, consistently, the inverse farm size-productivity relationship tends to be reversed among relatively large holders. The results support growing (diminishing) advantage of large (small) farms in the presence of rapidly rising real wages and have food security policy implications to many Asian countries where real wages are rapidly rising and small farms are predominant.     

A production rate control policy for stochastic repair and remanufacturing systems

We consider the control of a manufacturing system responding to planned demand at the end of the expected life of each individual piece of equipment and unplanned demand triggered by a major equipment failure. The difficulty of controlling this type of production system resides in the variable nature of the remanufacturing process. In practice, remanufacturing operations for planned demand can be executed at different rates, referring to different component replacement and repair strategies. We formulate this problem as a multi-level control problem and propose a suboptimal control policy. The proposed control policy is described by inventory thresholds triggering the use of different execution modes. Determination of the control policy parameters is based on parameter optimization of analytical cost expressions. A numerical example based on a real case is presented. Our analysis demonstrates that the use of the proposed control approach can lead to a significant reduction in the total average cost, as compared to current practices.     

Stock rationing under service level constraints in a vertically integrated distribution system

This paper addresses a rationing problem in a two-level, vertically integrated distribution system composed of one manufacturer and several retail points. The motivating case, developed in the vending machine sector and modeled as a newsvendor-like problem, is representative of many real settings where short-term changes in demand can be substantial while capacity modification is not a viable option. The paper provides an analytical discussion of the problem from two different standpoints: a pure profit-maximization perspective and a minimum service-level perspective, both subject to a product availability constraint that affects the service level the company can provide, and the related expected profit. By analyzing the Lagrangean formulation of the problem, we devise efficient computational procedures based on dichotomy search to find the optimal allotments to retailers, maximizing the expected profit and ensuring a minimum service level. Then, we extend the analysis to the evaluation of the highest service level that can be provided, under a product availability constraint. We identify conditions such that the proposed search procedures succeed in finding the optimal solutions, as well as bounds for the search domains. The proposed approach is legitimated under several demand distribution functions subject to a few commonly adopted restrictions that encompass many of the usually adopted continuous distributions. Finally, the paper presents a three-step decision-making framework using the proposed procedures, summarizing the decision paths the manufacturer might follow in order to optimize the allocation decision.     

Determination of an order-up-to policy in the stochastic economic lot scheduling model

We consider a production–inventory problem with compound renewal item demand. The model consists of stockpoints, one for each item, controlled according to (R,S)-policies and one machine which replenishes them. The replenishment orders are produced with a fixed rate on the machine with significant setup times and costs, which are stochastic and sequence dependent. The time between the release and the production of the replenishment order is called the waiting time. We develop analytical approximations for the first two moments of this waiting time, the order-up-to levels and the average physical inventory levels for all stockpoints, given the target fill rates. These analytical approximations allows for a quick evaluation of the waiting time which is important when optimization of the system is considered.     

Lockout/tagout and operational risks in the production control of manufacturing systems with passive redundancy

This paper addresses problems associated with production control and occupational safety in a manufacturing system prone to failure involving two machines working in passive redundancy. Machines turning out one part experience two modes of failure and repair: firstly, where failure occurs when a machine remains in fair condition; and, secondly, where such failure results in outright breakdown. Accordingly, we examine both modes of failure for their impact on a flexible manufacturing system (FMS) with respect to production control in terms of costs associated with lockout/tagout procedures and corrective maintenance. This study seeks to identify optimal costs related to backlogs, inventories and maintenance over an infinite planning horizon, along with levels of occupational risk where production control includes efficient planning of lockouts/tagouts. Our study offers numerical methods which may be employed to achieve optimal conditions in setting control policies. A numerical example and sensitivity analysis support this approach.     

Remanufacturing decision and sustainability under product life cycle uncertainty

Abstract

For a single type of product, we study a firm's remanufacturing decisions for the product under demand uncertainty from a real options approach. Specifically, we assume that the product life cycle consists of a growth regime with the expected product demand and volatility increasing with respect to time and a decay regime with the expected product demand and volatility decreasing with respect to time while the timing of regime change itself is uncertain as well. Under this framework, this study aims to derive and analyze the demand threshold above which the firm establishes a remanufacturing process in its production system. Moreover, the number of products being remanufactured throughout the life cycle is numerically studied to assess the degree of sustainability due to remanufacturing.     

机用锯条端头双孔冲模设计

介绍了机用锯条的加工工艺、锯条端头以及双孔模具的结构及设计要点,该模具结构简单合理,能在1台压力机上同时完成端头以及双孔加工,效率较高。该模具左右2个冲模之间的距离可调,可以加工双孔中心距为300~600mm的多规格锯条。     

A simulation-based evaluation of the cost of cycle time reduction in Agere Systems wafer fabrication facility—a case study

With the vast amount of capital invested in the semiconductor industry and the high level of competitiveness, semiconductor manufacturers are continuously searching for new methods to gain more market share and increase their profits. New technologies are continuously in demand, and are pushing the semiconductor manufacturers to seek better market position through constant improvement in their processes and products.Agere Systems is one of the leading companies in the microelectronics industry. This paper presents a comprehensive framework for strategic capacity expansion of production equipment at Agere Systems wafer fabrication facility (fab). We integrate simulation modeling, design of experiments, statistical analysis, and economic justification tools to aid in this highly complex decision-making process. We compliment the framework with a particular implementation. The procedure involved studying the factors in the fab that significantly impact the cycle times of the four main technologies that are currently in process and will stay in demand for at least the next few years. Moreover, the goal was to quantify the economic impact of reducing cycle times.To accomplish the objectives of this research, a valid simulation model of the production line of the fab was built. The production equipment (tool sets) that significantly influence production cycle time were identified through factor screening experiments. Based on these factors, several scenarios involving the acquisition of additional tools, aimed at cutting down cycle times, were identified and the operating characteristics curves were constructed. These characteristics curves were used to relate cycle time to production volume capabilities. Finally, an economic analysis was conducted to evaluate the return on investment in additional tools.The outcome of the case study was the identification of bottleneck facilities in the fab that have a significant impact on the cycle time of the four technologies. In the economic analysis, the cost of adding machines to these facilities was compared with the benefits resulting from the increase in production capacities.