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%.     

Scheduling with processing set restrictions: PTAS results for several variants

We consider multiprocessor scheduling to minimize makespan. Each job has a given processing time and in addition, a subset of machines associated with it, also called its processing set. Each job has to be assigned to one machine in its set, thus contributing to the load of this machine. We study two variants of this problem on identical machines, the case of nested processing sets, and the case of tree-hierarchical processing sets. In addition, we consider uniformly related machines with a special case of inclusive processing sets, which has a clear motivation. We design polynomial time approximation schemes for these three variants. The first case resolves one of the open problems stated in the survey by Leung and Li (2008).     

A mathematical model for a buffered two-stage manufacturing cell with an unreliable transfer device

In this paper, a mathematical model is developed for a manufacturing cell of two manufacturing stages with a single-storage buffer and a transfer robot for loading, unloading and moving parts into and out of the buffer. Both stages and the transfer robot are subject to failure. The cell is modeled as a random Markov process on the assumption that time to failure and time to repair are exponentially distributed. The output of such manufacturing cell is established, and as expected, it is less than that where the transfer means are continuously available.     

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.     

On how buyback and remanufacturing strategies affect the profitability of spare parts supply chains

The purpose of this paper is to provide a case-based framework to offer insights on the opportunity of recovering parts. We consider a two-stage spare parts supply chain, where independent repair shops are responsible for handling the repair process. There are two options to meet spare parts demand: repair shops may replace the part with a new one (ordered from the OEM) or they may use a part that they themselves repaired before. While repair shops achieve a larger profit by repairing parts, the OEM would prefer the use of new parts. However, he has no control over demand which might be obtained by offering buyback of broken parts. Furthermore, the OEM could recover these parts on a higher level, thus reducing production/procurement of new parts. The main contribution of this paper is the provision of a simple deterministic framework for answering the question whether a buyback option should be offered by the OEM to the repair shops, and which buyback price should be paid for each returned core. We further highlight the impact of remanufacturing performed at the OEM on the profitability of buyback.     

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.     

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.     

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.     

A new approach to job shop scheduling problems with due date constraints considering operation subcontracts

We consider a kind of job shop scheduling problems with due-date constraints, where temporal relaxation of machine capacity constraint is possible through subcontracts. In practice, this kind of problem is frequently found in manufacturing industries where outsourcing of manufacturing operation is possible through subcontract. We present a heuristic algorithm that addresses the problem by solving a series of smaller subproblems to optimality. For the sake of efficiency, the algorithm repeatedly executes in two steps—(1) improving the sequence of operations and (2) picking out the operations to be subcontracted—on bottleneck machines. Experiments are conducted for example problems, and the result of the experiment confirms the viability of the suggested algorithm.     

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.     

Heuristics for operational fixed job scheduling problems with working and spread time constraints

Operational fixed job scheduling problems select a set of jobs having fixed ready and processing times and schedule the selected jobs on parallel machines so as to maximize the total weight. In this study, we consider working time and spread time constrained versions of the operational fixed job scheduling problems. The working time constraints limit the total processing load on each machine. The spread time constraints limit the time between the start of the first job and the finish of the last job on each machine. For the working time constrained problem, we present a filtered beam search algorithm that evaluates the promising nodes of the branch and bound tree. For the spread time constrained problem we propose a two phase algorithm that defines the promising sets for the first jobs and finds a solution for each promising set. The results of our computational tests reveal that our heuristic algorithms perform very well in terms of both solution quality and time.     

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.     

Simultaneous control of production, repair/replacement and preventive maintenance of deteriorating manufacturing systems

This paper presents a method to find the optimal production, repair/replacement and preventive maintenance policies for a degraded manufacturing system. The system is subject to random machine failures and repairs. The status of the system is deemed to degrade with repair activities. When a failure occurs, the machine is either repaired or replaced, and a replacement action renews the machine, while a repair action brings it to a degraded operational state, with the next repair time increasing as the number of repairs increases as well. A preventive maintenance action is considered in order to improve the reliability of the machine, thereby reducing the amount of disruptions caused by machine failures. The decision variables are the production rate, the preventive maintenance rate and the repair/replacement switching policy upon machine failure. The objective of the study is to find the decision variables that minimize the overall cost, including repair, replacement, preventive maintenance, inventory holding and backlog costs over an infinite planning horizon. The proposed model is based on a semi-Markov decision process, and the stochastic dynamic programming method is used to obtain the optimality conditions. A numerical example is given to illustrate the proposed model, and a sensitivity analysis is considered in order to confirm the structure of the control policy and to illustrate the usefulness of the proposed approach.     

Technology‐push,market‐demand and the missing safety‐pull: a case study of American Airlines Flight 587

Through a critical case study of the crash of American Airlines Flight 587, this paper draws upon ‘the Social Shaping of Technology’ (SST) approach to offer a reconceptualisation of the technology‐push and market‐demand model for High‐Reliably Organisations (HROs), providing support for a third factor, called here a ‘safety‐pull’. A safety‐pull is defined as organisationally supported reflexivity in which technology innovators and frontline operators collaborate to consider the potential implications of adopting new technologies in HROs and the complex ways this change may impact human operators' work performance, often in risky and unanticipated ways. In contrast to accidents occurring solely as the result of individual operator error, analysing the safety‐pull provides a way to tease out the wide range of factors that can contribute to HRO failures and offers a new SST perspective through which to examine high‐risk operations.     

Multiple part-type scheduling in flexible robotic cells

This paper considers the scheduling problem arising in two-machine manufacturing cells which repeatedly produce a set of multiple part-types, and where transportation of the parts between the machines is performed by a robot. The cycle time of the cell depends on the robot move sequence as well as the processing times of the parts on the machines. For highly flexible CNC machines, the processing times can be adjusted. To this end, this study tries to find the robot move sequence as well as the processing times of the parts on each machine that jointly minimize the cycle time. The problem of determining the best cycle in a 2-machine cell is first modeled as a traveling salesman problem. Then, an efficient 2-stage heuristic algorithm is constructed and compared with the most common heuristic approach of longest processing time (LPT).     

石油钻机状态模糊综合评价

运用模糊数学的方法,根据石油钻机各个组成系统在整套钻机中所起的作用大小,确定各个系统的权重,并再进一步细化,确定各个组成系统的关键部件和零件的权重。依据检测数据分析和专家经验,对钻机等级进行综合评判和分级。     

油气管道环焊缝新型修复技术研究

为了寻求适应高钢级油气管道环焊缝缺陷的新型修复方法,克服传统修复技术的局限性,提出了电弧增材制造技术用于油气管道环焊缝修复的可行性。首先,对激光熔覆、冷喷涂、电弧增材制造3种新型修复技术进行对比分析后,采用电弧增材制造技术进行实验研究;其次,在X80管道环焊缝处沿轴线截取22 mm厚的试样,并在环焊缝处设计坡口角度为60°,坡口深度为11 mm的缺陷,采用电弧增材制造冷金属过渡工艺、ER50-6焊丝进行修复实验;最后,对修复试样进行力学实验测试,并对实验数据和断口形貌进行分析。实验结果表明,电弧增材制造修复后试件抗拉强度最高达639 MPa,强度与管体基材匹配。研究结果表明,电弧增材制造技术用于X80油气管道环焊缝缺陷的修复是可行的,具有沉积效率高、成本低、力学性能能满足修复要求的特点,对于高钢油气管道环焊缝缺陷修复的可行性和经济性具有重要的现实意义。     

Economic implications of a co-investment scheme for FTTH/PON architectures

Due to the high costs associated with the deployment of the passive infrastructure of FTTH networks, a few alternative operators have pondered the possibility of making co-investments based on a network sharing model. The purpose of this article is to explore economic aspects of a co-investment scheme for present and future FTTH/PON architectures. The article describes the cost reductions that can be achieved when a co-investment scheme is used, as well as the relationship between market shares and the cost per home connected. A cost model was employed to calculate the investment per home passed and the investment per home connected. The investment per home passed for an alternative operator indicates significant cost reductions when a co-investment scheme is used. On the other hand, the results show that when the incumbent's market share is equal or higher than the total market share of all the alternative operators that share the network infrastructure, the investment per home connected for an alternative operator is higher than that for the incumbent operator. Moreover, to be cost competitive with the incumbent operator, the necessary market share that each alternative operator should achieve is much lower than that of the incumbent operator.     

Two-machine flow shop scheduling with deteriorating jobs and chain precedence constraints

In this paper we investigate two-machine flow shop scheduling problems with deteriorating jobs and chain precedence constraints. We consider two types of precedence constraints. Under the first type constraints, a successor cannot start on any machine before its predecessor has been completed on the same machine. Under the second one, a successor cannot start on any machine before its predecessor has been completed on all machines. We show that the problem with the first type precedence constraints is polynomially solvable, and the problem with the second type precedence constraints is NP-hard in the strong sense.