Equipment selection and task assignment for multiproduct assembly system design

A multiproduct assembly system produces a family of similar products, where the assembly of each product entails an ordered set of tasks. An assembly system consists of a sequence of workstations. For each workstation, we assign a subset of the assembly tasks to be performed at the workstation and select the type of assembly equipment or resource to be used by the workstation. The assembly of each product requires a visit to each workstation in the fixed sequence. The problem of system design is to find the system that is capable of producing all the products in the desired volumes at minimum cost. The system cost includes the fixed capital costs for the assembly equipment and tools and the variable operating costs for the various workstations. We present and illustrate an optimization procedure that assigns tasks to workstations and selects assembly equipment for each workstation.     

Literature review of assembly line balancing problems

Mass production system design is a key for the productivity of an organization. Mass production system can be classified into production line machining a component and production line assembling a product. In this paper, the production line assembling a product, which is alternatively called as assembly line system, is considered. In this system, balancing the assembly line as per a desired volume of production per shift is a challenging task. The main objectives of the assembly line design are to minimize the number of workstations for a given cycle time (type 1), to minimize the maximum of the times of workstations for a given number of workstations (type 2), and so forth. Because this problem comes under combinatorial category, the use of heuristics is inevitable. Development of a mathematical model may also be attempted, which will help researchers to compare the solutions of the heuristics with that of the model. In this paper, an attempt is made to present a comprehensive review of literature on the assembly line balancing. The assembly line balancing problems are classified into eight types based on three parameters, viz. the number of models (single-model and multi-model), the nature of task times (deterministic and probabilistic), and the type of assembly line (straight-type and U-type). The review of literature is organized as per the above classification. Further, directions for future research are also presented.     

On-Line Production Control of Tandem Systems with Finite Inter-Stage Storage, Using a Dynamic Maximum Cycle Time Algorithm

For a tandem manufacturing system with finite interstage storage and asynchronous operations, stage cycle times are allowed to vary from cycle to cycle and from stage to stage. Owing to the nature of the operation and the occurrences of blocking and starvation, the relationship between the time each stage spends on each job and the output rate of the system is not directly observable. In order to operate the system so that it meets the demand without over-producing or under-producing, it would be helpful to know the time limit available for each stage to operate on each job. This paper describes a method for calculating such cycle time limits for each stage at each cycle on a real-time basis. The calculated cycle time limits are always bounded below, approximately by the expected time between outputs of the system. The value of a cycle time limit is a function of the current system state, performance history of the stages and the interrelationship among the stages. Emulation examples (with 3-stage and 10- stage systems) will show that while cycle times are allowed to vary, as long as they do not exceed their calculated limits throughout the production, system output will be very close to a predefined expected amount.     

基于HRP视角下医院固定资产全生命周期管理系统研究

为了帮助医院更好地规划固定资产,搞好固定资产全生命周期全面管理,减少资源浪费,节约医疗资本,以此促进医院可持续化发展,本文提出构建固定资产全生命周期管理系统.该系统立足于HRP(Hospital Resource Planning医院资源规划)基础上,运用预算等专门管理系统,采用集成平台接口进行对接,然后与EAS(El...     

A mathematical model and ant colony algorithm for multi-manned assembly line balancing problem

In real-world assembly lines, that the size of the product is large (e.g., automotive industry), usually there are multi-manned workstations where a group of workers simultaneously perform different operations on the same individual product. This paper presents a mixed integer programming model to solve the balancing problem of the multi-manned assembly lines optimally. This model minimizes the total number of workers on the line as the first objective and the number of opened multi-manned workstations as the second one. Since this problem is well known as NP (nondeterministic polynomial-time)-hard, a heuristic approach based on the ant colony optimization approach is developed to solve the medium- and large-size scales of this problem. In the proposed algorithm, each ant tries to allocate given tasks to multi-manned workstations in order to build a balancing solution for the assembly line balancing problems by considering the precedence relations, multi-manned assembly line configuration, task times, and cycle time constraints. Through computational experiments, the performance of the proposed ACO is compared with some existing heuristic on various problem instances. The experimental results validate the effectiveness and efficiency of the proposed algorithm.     

A bidirectional heuristic for stochastic assembly line balancing Type II problem

In this paper, a heuristic algorithm is proposed to solve the single-model stochastic assembly line balancing Type II problem. For a given number of workstations and a pre-specified assembly line reliability, which is the probability of the workload not exceeding the cycle time for the whole assembly line, the proposed algorithm tries to obtain a solution with the smallest cycle time. In the first stage, the tasks are assigned to workstations from the forward and backward directions alternatively. In the second stage, the workload is smoothed by swapping tasks among workstations. At last, the upper bound of the cycle time obtained in the second stage is reduced step by step until the smallest cycle time satisfies the pre-specified assembly line reliability. The performance of the proposed algorithm is compared with a modified version of Moodie and Youngs algorithm by applying them to some literature problems. The computational results show that the proposed algorithm is efficient in minimizing the cycle time for the single-model stochastic assembly line balancing problem.     

Balancing–sequencing procedure for a mixed model assembly system in case of finite buffer capacity

In the last decades, the necessity to make production more versatile and flexible has forced assembly line production systems to change from fixed assembly lines to mixed model assembly lines, where the output products are variations of the same base product and only differ in specific customizable attributes. Such assembly lines allow reduced setup time, since products can be jointly manufactured in intermixed sequences (Boysen, Flieder, Scholl. Jena Research Papers in Business and Economics, Friedrich-Schiller-Universitat Jena, 1;1–11, 2007a; Boysen, Flieder, Scholl. Jena Research Papers in Business and Economics, Friedrich-Schiller-Universitat Jena, 2;1–33, 2007b). Unfortunately, the installation of customization options typically leads to variations in process times, and when the cycle is exceeded within a certain station, an overload is created, forcing other stations to wait and idle. Normally, process time variation in an un-paced line are absorbed by buffers, but in some industrial application the buffer dimensions are critical not only for the reduction of work in progress but also in reducing other constrains (space, technology, model dimensions, etc.). The problem of balancing mixed model assembly lines (MALBP), in the long term, and that of sequencing mixed model assembly lines (MMS), in the short term (Merengo, Nava, Pozetti. Int J Prod Res 37:2835–2860, 1999), are the two major problems to solve. The object of this paper is to illustrate an innovative balancing–sequencing step-by-step procedure that aims to optimize the assembly line performance and at the same time contain the buffer dimensions in function of different market demand and production mix. The model is validated using a simulation software and an industrial application is presented.     

Design configuration for a mixed-model assembly system in case of low product demand

In order to accompany the increasing variety of costumers’ demands, manufacturers tend to produce different models of the same product on an assembly line by introducing group assembly (GA) design concepts that improve the flexibility of assembly systems. Generally, when the demand for a set of similar products is relatively low and the set-up time is significant, the beneficial effects of the task repeatability of the straight line configuration are difficult to achieve. As a consequence, the fixed-point assembly philosophy is often preferred. This paper addresses the application of a mixed-model assembly balancing problem to an assembly-to-order environment in the case of low production rates and large number of tasks. The aim of this work is to propose an alternative design procedure for the balancing of semi-automated and mixed-model assembly systems under low product demand effects by the application of multi-turn circular transfers, such as a multi-stations rotating table. This layout configuration permits a job enlargement for human operators and, at the same time, provides an increment in task repeatability through the work-pieces assembling by increasing the number of the turns of the transfer. Finally, the developed heuristic procedure is tested on a simple rotating table assembly cell, a partial representation of a complete assembly system of domestic air compressors.     

预防维护下装配线平衡的多目标重启变邻域搜索算法

针对预防维护下的装配线平衡问题,提出了一种带有重启策略的多目标变邻域搜索算法,以优化正常工作、设备维护情形下的节拍与工序调整。算法结合启发式与随机方法得到较优初始解;设计并筛选出寻优能力较强且具有互补性的四类邻域算子及其搜索策略,以更好地进行全局探索与局部开发。为促进Pareto前沿推进,提出了一种具有自适应能力的重启算子,以便根据问题规模调整重启代数阈值、参考寻优进程扩大搜索空间。该算法机制简单且无固定参数,实验结果表明该算法能够获得具有竞争性的非支配解集。     

Design of a flexible assembly line to control the bottleneck

In this paper, a methodology for the design of a flexible assembly line system (e.g. a flow shop consisting of a set of tandem flexible workstations, a set of automated inspection stations, a loading station, and an unloading station, linked by a material handling system) is presented, while controlling the bottleneck problem. This paper is a generalization of earlier work, where a design strategy for a simplified version of a similar manufacturing system was proposed. In this paper, the loading process is stationary with identically distributed interarrival times, and defective work-pieces are reprocessed at the corresponding workstations. Here, the performance of the assembly line is modelled by a non-Markovian queueing network with finite capacity queueing nodes. Based on this queueing network, a stochastic optimization model is then presented to select the minimum required local storage sizes of the workstations and the transporter stations such that the resulting probabilities of finding each workstation and each transporter station blocked (e.g. full) are sufficiently close to zero. To solve the proposed optimization model, a heuristic algorithm is then developed. Finally, an example is presented, and the relative accuracy of the proposed algorithm is investigated by a simulation study.     

A Petri net-based heuristic for simple assembly line balancing problem of type 2

In this paper, a Petri net-based heuristic is presented to solve simple assembly line balancing problem type-II (SALBP-2). Petri net is a mathematical and graphical tool to model and analyze for discrete event systems. SALBP-2 minimizes cycle time for given number of workstations. The presented heuristic determines available tasks and assign task to current workstation by using reachability analysis, one of the main properties of Petri nets, and token movement. Solution of SALBP-2 is implemented by iteratively solving the problem for several trial cycle time. If the cycle time is infeasible for given number of workstations, the heuristic increases the cycle time by a value until finding a feasible solution. To improve the solution, a binary search procedure is implemented between the first feasible solution and the last infeasible solution. Three versions of the heuristic are developed by integrating with forward, backward, and bidirectional procedures. All of them are coded in MATLAB, and their efficiencies are tested on benchmark datasets with 302 instances. Also a comparison study is made with a direct procedure and five heuristics based on differential evolution algorithm. Test and comparison results show that the proposed heuristic obtains good results for SALBP-2. Its performance is superior especially in large assembly lines.     

An agent-based collaborative assembly process planning system

In recent years, the competition among manufacturers to reduce the development time of new products has been quite fierce. At the same time, customers’ needs have become relatively diverse. Considering these facts, it is essential for manufacturers to build an assembly line in the shortest time possible. Because an assembly line for varied and complex products involves numerous workstations, assembly operations and resources, it is extremely difficult for assembly process planners to develop an efficient assembly sequence and position. Thus, in order to overcome such complications, the best alternative is for a number of process planners to develop a process plan synchronously . This paper introduces a new process planning method for assembly lines based on a collaborative system. In it we propose an agent-based collaborative process planning system, and to verify it, we implement the system in an Internet environment and apply it to some practical case studies.     

A new algorithm and multi-response Taguchi method to solve line balancing problem in an automotive industry

One of the most important issues in an assembly line balancing problem is to control a flow of production and manufacturing to provide continuous flow to balance the production line. For this purpose, a line balancing problem was considered for a special assembly line in an automotive factory. A new algorithm was required to deal with balancing an assembly line which consisted of the same job which must be performed by more than one worker at the same time. In this way, the new algorithm was expected to be effective in such a case that jobs were simultaneously completed in a parallel way. In order to measure effectiveness of the proposed algorithm, performance criteria were identified as total number of assembly station, total number of workers, and line productivity. As a result of the application of the proposed algorithm with taking into consideration factors such as cycle time, an allowable number of workers in an assembly station, and an allowable idle time of a worker, alternative solutions were determined in order to measure these criteria. However, these alternative solutions do not give any information about which of the solutions provide not only minimization of the number of assembly station and number of workers on the line but also maximize the line productivity at the same time. Hereby, a multi-response Taguchi method was applied in order to investigate levels of factors which directly affected system performance criteria.     

Heuristic scheduling policies for a semiconductor wafer fabrication facility: minimizing variation of cycle times

This paper presents heuristic scheduling policies for semiconductor wafer fabrication facilities. The proposed heuristic scheduling policies include the advanced operation due date (OPNDD) for a sequence control policy and the adaptive constant work-in-process (CONWIP) for an input release control policy. The objective of the proposed scheduling policies is to reduce the variation of cycle times in the wafer fab. The advanced OPNDD sets the higher priority to the front opening unified pod (FOUP) with the smallest operation due date that is computed using a generalized stochastic Petri net model, and at the same time regulates the queue lengths of the FOUPs in each stoker by preventing excessive queue lengths in bottleneck workstations. The adaptive CONWIP controls dynamically the input release time of FOUPs using the adaptive WIP level according to the current status of the wafer fab. The simulation experiments show that the proposed scheduling method is efficient in reducing the variation of cycle times.     

Evaluation of drilled hole quality in Al 2024 alloy

We propose an optimal worker flexibility policy for a CONWIP (constant work-in-process) controlled dual resource constrained (DRC) system. A critical issue in DRC systems is the dynamic assignment of workers to the workstations. The proposed worker flexibility policy is designed to evaluate the state of the system at periodic time intervals so that the dynamic assignment of workers to the workstations can be made in an efficient manner. By integrating the response surface methodology (RSM) with simulation, this study provides an approach for optimizing worker transfer decisions. The RSM-based simulation optimization approach adopted in this study provides an effective and robust procedure to determine the optimum level of this decision variable under the given operating conditions.     

Error detection and recovery in flexible assembly systems

This study investigates error detection and recovery for flexible assembly systems. A method for error recovery based upon an expert system is presented. An expert system is used to control the assembly cell, but the robot controller controls the assembly operation. This ensures adequate speed of the assembly cycle. The robot signals the expert system when an error occurs. It determines the cause of the error and recommends a preprogrammed recovery procedure to correct the error automatically. The system is flexible and new error recovery routines are easily added to the system. The proposed method was implemented in the Mark II assembly cell at 1VF-KTH in Stockholm. The reliability of the assembly cell increased considerably after installation of the error detection and recovery system. The error detection did not affect the cycle time and error recovery took less than 10 seconds on average.     

Cycle time variance minimization in dynamic scheduling of single machine systems

In this paper, we study the minimization of variance of cycle times in a dynamic single machine system where jobs arrive continuously over time. Numerous production systems give rise to single machine models, and a multiple-machine environment where the performance of a bottleneck machine determines the performance of the entire system reduces to a single machine problem [16]. Minimizing cycle time variance helps in safe predictions of the completion of job production and thus in providing the same quality of service to the customers. This allows an improved ability to meet the due dates reliably, and thus the greater coordination with further downstream operations on the jobs, as highly preferred in semiconductor manufacturing. Scheduling the bottleneck process to minimize the time of presence of the jobs in process minimizes the deterioration of cycle time-related performance measures. Low values of cycle time-related measures are also preferred for low risk of wafer contamination associated with it during processing. New scheduling rules are developed to minimize both the cycle time variance and the maximum cycle time for single machine system, wherein the machine/process is always utilized to the maximum extent and in the extreme case is heavily loaded with jobs for processing. The performance of the proposed rules is compared with the rules available in the literature and the results are presented for the objectives of minimizing cycle time variance and maximum cycle time at higher levels of machine utilization.     

A P-invariant-based algorithm for simple assembly line balancing problem of type-1

A simple assembly line balancing problem of type-1 (SALBP-1) concerns minimizing the number of workstations on an assembly line for a given cycle time. In this problem only a single product with deterministic task times is considered. Since the SALBP-1 is known as an NP-hard, considerable research effort has been spent to develop heuristic approaches. In this study we develop a different heuristic approach based on the P-invariants of Petri nets. The algorithm is coded in MATLAB, and its efficiency is tested on Talbot’s and Hoffmann’s benchmark datasets according to some performance measures and classifications. A computational study validates its effectiveness on Tonge’s 70-task problem by comparison with solutions of traditional heuristics and a genetic algorithm reported to perform well.     

Modeling and design optimization of asynchronous flexible assembly systems with statistical process control and repair

This article presents the implementation of hybrid procedures involving the use of analytical performance evaluation techniques, discrete event simulation, and Monte Carlo optimization methods for the stochastic design optimization of asynchronous flexible assembly systems (AFASs) with statistical process control (SPC) and repair loops. AFASs are extremely complex and difficult to analyze in that such systems are subject to starvation and blocking effects, random jam occurrences at workstations, and splitting and merging of the assembly flow due to repair loops. Hence, an integrated approach simultaneously analyzing the interactions between product quality and optimal/near optimal system design is pursued. In the analytical analysis stage, a model based on GI/G/1 queueing network theory is used. In the Monte Carlo optimization stage, two alternative stochastic optimization approaches, namely, heuristic versions of stochastic quasigradient and simulated annealing algorithms, are implemented and compared in terms of their capabilities of solving complex AFAS design problems. The hybrid procedures presented appear to perform reasonably well in designing AFASs to reach a target production rate.