An Evolutionary Algorithm for Sequencing Production on a Paced Assembly Line

A new sequencing method for mixed‐model assembly lines is developed and tested. This method, called the Evolutionary Production Sequencer (EPS) is designed to maximize production on an assembly line. The performance of EPS is evaluated using three measures: minimum cycle time necessary to achieve 100% completion without rework, percent of items completed without rework for a given cycle time, and sequence “smoothness.” The first two of these measures are based on a simulated production system. Characteristics of the system, such as assembly line station length, assembly time and cycle time, are varied to better gauge the performance of EPS. More fundamental variation is studied by modeling two production systems. In one set of tests, the system consists of an assembly line in isolation (i.e., a single‐level system). In another set of tests, the production system consists of the assembly line and the fabrication system supplying components to the line (i.e., a two‐level system). Sequence smoothness is measured by the mean absolute deviation (MAD) between actual component usage and the ideal usage at each point in the production sequence. The performance of EPS is compared to those of well‐known assembly line sequencing techniques developed by Miltenburg (1989), Okamura and Yamashina (1979), and Yano and Rachamadugu (1991). EPS performed very well under all test conditions when the criterion of success was either minimum cycle time necessary to achieve 100% production without rework or percent of items completed without rework for a given cycle time. When MAD was the criterion of success, EPS was found inferior to the Miltenburg heuristic but better than the other two production‐oriented techniques.     

A mathematical model and genetic algorithm-based approach for parallel two-sided assembly line balancing problem

Assembly lines are usually constructed as the last stage of the entire production system and efficiency of an assembly line is one of the most important factors which affect the performance of a complex production system. The main purpose of this paper is to mathematically formulate and to provide an insight for modelling the parallel two-sided assembly line balancing problem, where two or more two-sided assembly lines are constructed in parallel to each other. We also propose a new genetic algorithm (GA)-based approach in alternatively to the existing only solution approach in the literature, which is a tabu search algorithm. To the best of our knowledge, this is the first formal presentation of the problem as well as the proposed algorithm is the first attempt to solve the problem with a GA-based approach in the literature. The proposed approach is illustrated with an example to explain the procedures of the algorithm. Test problems are solved and promising results are obtained. Statistical tests are designed to analyse the advantage of line parallelisation in two-sided assembly lines through obtained test results. The response of the overall system to the changes in the cycle times of the parallel lines is also analysed through test problems for the first time in the literature.     

Line balance analyses for system assembly lines in an electronic plant

This research analysed and optimised the assembly line balance of notebook computer system production lines in a major computer plant. The research developed a mathematical model for balancing assembly lines of a specific notebook computer system. Precedence relationship charts were created to enforce the required sequences and ILOG CPLEX software was used to obtain the optimal solution of the task assignments to the workstations. The new task assignments were simulated to verify the improvement recommendations and predict the potential benefits.The estimated improvements include: (1) 5.9% increase in average daily production; (2) 29% decrease in average daily WIP; (3) 67.9% reduction in cycle time; (4) 16.7% reduction in operator headcount over the whole system assembly area. The contributions of this research include: (1) Establishing line balancing mathematical model suitable for notebook computer factories; (2) Optimising the system assembly lines for the subject company; (3) Transferring the line balance modelling and optimisation techniques for company use.     

Flexible multi-manned assembly line balancing problem: Model,heuristic procedure,and lower bounds for line length minimization

Assembly lines dedicated to the production of large products often allow multiple workers to perform tasks simultaneously on the product. Previous works on such multi-manned lines define workstations with fixed, discrete, and restrictive frontiers, despite commonly considering continuous paced line control. This paper proposes flexible station frontiers for multi-manned lines and shows that such innovation allows significantly shorter line lengths. A new Mixed Integer Linear Programming model and a novel model-based heuristic procedure are presented to describe and optimize lines. Algorithmic lower bounds are also introduced for the problem. The formulation was compared to a literature benchmark of regular multi-manned solutions. These experiments showed that flexible multi-manned formulations can lead to line length reductions of up to 42%. Such reductions were obtained for most instances (81 out of 88), with an average value of 18%. The relationship between cycle time and minimal line length is also analyzed, demonstrating that efficient solution sets can be continuous or discrete, depending on the instance.     

PERFORMANCE ANALYSIS OF AN ASSEMBLY STATION WITH INPUT FROM MULTIPLE FABRICATION LINES

We develop analytical models for performance evaluation of Fabrication/Assembly (F/A) systems. We consider an F/A system that consists of an assembly station with input from K fabrication lines. Each fabrication line consists of one or more fabrication stations. The system is closed with a fixed number of items circulating between each fabrication line and the assembly station. We present algorithms to estimate the throughput and mean queue lengths of such systems with exponential processing times. We then extend our approach to analyze F/A systems with general processing time distributions. Numerical comparisons with simulations demonstrate the accuracy of our approach.     

Experimental push/pull production planning and control system

We introduce an experimental push/ pull production planning and control software system which is designed as an alternative to a MRP-II system for mass manufacturing enterprises in China. It has the following distinguishing features: (1) putting the philosophy of JIT into the master production scheduling of MRP-II via the earliness/ tardiness production planning method; (2) controlling material input by push and processing/ assembly by pull; and (3) adjusting the parameters of the production line by the‘ suggestion for improvement of production line’ module. Simulation results have shown that the proposed system can achieve better planning and control performance than existing systems.     

Efficient flow control of jobs in assembly lines

This paper addresses the issues of efficient flow control techniques for jobs in assembly lines. We propose a queuing theoretic approach for efficient flow control of jobs. An assembly line performance measure (ALPM) is used as the measure of performance for each assembly line and is denned as the ratio of throughput to total average delay of an assembly line (AL). A performance product criterion (PPC) is used as the performance measure of a cluster of ALs. It is shown that the performance product criterion has a unique maximum in throughput space. Two algorithms are presented to find the maximum of the performance product criterion in two different cases of assembly line environment. In the first algorithm, we attempt to maximize the performance product criterion with respect to the throughputs of the assembly lines in the entire throughput space. The second algorithm maximizes the performance product criterion when the sum of the throughputs of the ALs is fixed. Numerical examples are given as illustrations of the algorithms.     

Towards optimised robotic assembly

Assembly by robot is destined to have a major international impact over the next few years, yet the optimal design, analysis and economic evaluation of a potential robotic assembly application is currently extremely difficult. On looking at the current state-of-the-art in each stage of the hierarchy which a prospective robotic assembly project must pass through, it becomes clear that the whole procedure is closely analogous to attempting to paint an ‘ideal’ picture—both from the point of view of tasks which must be performed and also the level of complexity involved. Unfortunately, unlike with painting, there is not yet any wealth of experience on which roboticists can draw in their quest for ‘ideal’ assembly. Nevertheless, work at Imperial College aims at systematically uncovering some of the underlying principles of robotic assembly which if left to discovery through trial and error might take years—years which industry simply does not have.     

经济批量排产问题的一种排产方法

针对经济批量排产问题假定生产可以在库存降为0之前开始,并且提出新的算法求产品的生产顺序。结果表明,该排产方法成本要低于其他2种常用的经济批量排产问题的方法,并且给出了算法的时间复杂性。     

Two-sided assembly line balancing: A genetic algorithm approach

A two-sided assembly line balancing problem is typically found in plants producing large-sized high-volume products, e.g. buses and trucks. The features specific to the assembly line are described in this paper, which are associated with those of: (i) two-sided assembly lines; (ii) positional constraints; and (iii) balancing at the operational time. There exists a large amount of literature in the area of line balancing, whereby it has mostly dealt with one-sided assembly lines. A new genetic algorithm is developed to solve the problem, and its applicability and extensibility are discussed. A genetic encoding and decoding scheme, and genetic operators suitable for the problem are devised. This is particularly emphasized using problem-specific information to enhance the performance of the genetic algorithm (GA). The proposed GA has a strength that it is flexible in solving various types of assembly line balancing problems. An experiment is carried out to verify the performance of the GA, and the results are reported.     

A structured methodology to implement judiciously the right JIT tactics

In order to enhance the competitiveness and efficiency of manufacturing operations, many companies arc looking at implementing key strategic technologies. Two of the most predominant programs are ‘just-in-time’ and ‘synchronous organizations’. However, their impacts on improving quality and reducing time-to-market have been mixed. It is not very clear why, in some cases, results are poor, when in a similar situation, programmes have proved to work well. There are conflicting reasons reported for such a discrepancy. Some have argued that during J IT implementation either a right mix of tactics was not selected at the outset or the process was not carefully monitored to see whether a mid-course correction or change in tactics was necessary. In order to (a) protect the manufacturing and strategic teams from making the same/similar mistakes and (b) sustain a series of successful activity throughout during the strategic implementation cycle, this paper outlines a structured methodology. The method utilizes a matrix-based procedure to dynamically (over time) measure the effectiveness of a line of JIT tactics against the organization's principles and objectives. The operating procedure suggests first (a) using a method for monitoring the changing conditions of market and business and then (b) using the metrics to guide the management with a new line of tactics that might have better impact on the newly aligned company goals. In an effort to help managers and engineers decide on a proper line of tactics to implement JIT, a line of JIT quality matrices (JQM) is developed. JQM provides a framework to guide group managers to ‘plan, pick and choose’ a set of effective JIT techniques. An approach similar to quality function deployment (QFD) is used to generate the JIT house and their corresponding JQM matrices. With the JQM-based structured methodology, managers can design the best line of JIT strategy blended with JIT theory and adapted to the manufacturing environments in which it is expected to operate.     

Multi-neighborhood based path relinking for two-sided assembly line balancing problem

This paper presents a multi-neighborhood based path relinking algorithm (MN-PR) for solving the two-sided assembly line balancing problem. By incorporating an effective local search into a path relinking framework, the proposed MN-PR algorithm integrates a number of distinguishing features, such as a multi-neighborhood based local search procedure, a dedicated path relinking operator to generate new solutions and a strategy to fix an infeasible solution generated by the path relinking procedure to a feasible one. Our proposed MN-PR algorithm is tested on a set of totally 45 public instances widely used in the literature. Comparisons with other reference algorithms show the efficacy of the proposed algorithm in terms of the solution quality. Particularly, the proposed MN-PR algorithm is able to improve the best upper bounds for one instance with 65 tasks and 326 cycle time. This paper also presents an analysis to show the significance of the main components of the proposed algorithm.     

Time-based goal chasing method for mixed-model assembly line problem with multiple work stations

In sequencing problems for mixed-model assembly line in JIT production system, the Goal Chasing method (GC) is widely used for parts used leveling goal. The difference in assembly time of each product is not taken into consideration in the Goal Chasing method. Assembly time usually varies with product types. In recent years, the Time-Based Goal Chasing method (TBGC) has been proposed. The advantage of TBGC is to consider the influence of different assembly time of each product and idle time in production period. TBGC, however, has been only applied to single work station problems. In this paper, TBGC is applied to an assembly line problem with multiple work stations. Furthermore, the sequencing method and use of Simulated Annealing (SA) or Local Search (LS) for this problem are proposed.     

Multi-objective multi-verse optimiser for integrated two-sided assembly sequence planning and line balancing

Research in assembly optimisation is presently inclined towards integrative measures. Several benefits of simultaneously optimised Assembly Sequence Planning (ASP) and Assembly Line Balancing (ALB) have been highlighted by researchers to have better solution quality, shorter time-to-market, and minimalised error during planning. Recently, several efforts have been made to realise integrated assembly optimisation. However, none of the published research considered the two-sided assembly line problem. This paper presents an integrated ASP and ALB optimisation in a two-sided assembly environment (2S-ASPLB), which is mainly adopted in automotive assembly process. In this study, the 2S-ASPLB problem was formulated and optimised using Multi-Objective Multi-Verse Optimiser (MOMVO) by considering line efficiency, reorientation penalty, and tool change as the optimisation objectives. The computational experiments were conducted in a few stages, beginning with the identification of the best decoding approach for 2S-ASPLB. Next, the best MOMVO coefficient was studied, followed by comparing MOMVO performance with well-established multi-objective optimisation algorithms. Finally, a case study problem was presented to demonstrate applicability of the proposed model and algorithm in real-life problem. The results indicated that the priority factor (PF) decoding approach had better performance compared with others. Meanwhile, in comparison with well-established algorithms, MOMVO performed better in convergence and solution distribution. The case study results indicated the applicability of proposed 2S-ASPLB model and algorithm to improve line efficiency in assembly line. The main contribution of the research is a new 2S-ASPLB model and optimisation scheme, which can assist manufacturer in designing better assembly layout.

     

OPTIMAL BUFFER ALLOCATION IN ASYNCHRONOUS CYCLIC MIXED-MODEL ASSEMBLY LINES

This paper considers a problem of optimal buffer allocation in cyclic asynchronous mixedmodel assembly lines with deterministic processing times. An analytical model is used to provide new insights into properties of optimal buffer allocation, that is, a buffer configuration that guarantees the highest possible throughput rate on the assembly line with a minimum number of buffers. Optimal buffer configuration is characterized, and an efficient algorithm to find such a configuration is developed. The approach proposed in this paper also provides insights on how to allocate a given number of buffers to workstations on the assembly line to maximize the throughput rate.     

MIXED ASSEMBLY AND DISASSEMBLY OPERATIONS FOR REMANUFACTURING

In this paper we consider the problem of designing a mixed assembly‐disassembly line for remanufacturing. That is, parts from the disassembly and repair of used products can be used to build “new” products. This is a problem common to many OEM remanufacturers, such as Xerox or Kodak. We study two main configurations, under the assumption that the disassembly sequence is exactly the reverse of the assembly sequence. Under a parallel configuration, there exist two separate dedicated lines, one for assembly and one for disassembly, which are decoupled by buffers—from both disassembly operations, which have preference, as well as parts from an outside, perfectly reliable supplier. Under a mixed configuration, the same station is used for both disassembly and assembly of a specific part. The problem is studied using GI/G/c networks, as well as simulation. Due to a loss of pooling, we conclude that the parallel configuration outperforms the mixed line only when the variability of both arrivals and processing time are significantly higher for disassembly and remanufacturing than for assembly. Via a simulation, we explore the impact of having advanced yield information for the remanufacturing parts. We find that advanced yield information generally improves flow times; however, there are some instances where it lengthens flow times.     

Performance analysis of a multi-agent scheduling and control system under manufacturing disturbances

This paper is concerned with evaluating the performance of alternative multi-agent approaches to manufacturing planning and control. In order to separate the influence of ‘control algorithm’ from that of ‘control architecture’, a simple local control algorithm is chosen as a common starting point for developing the agent-based system. Two sets of experiments are then reported to evaluate how changes in individual agent characteristics can affect the control system's flexibility and adaptability against disturbances. These experiments show that the manufacturing and control system performance is not affected by architecture if the control algorithm remains fixed, however, altering the characteristics of the control system decision-makers influences both systems’ performance.     

A multiobjective model and evolutionary algorithms for robust time and space assembly line balancing under uncertain demand

Changes in demand when manufacturing different products require an optimization model that includes robustness in its definition and methods to deal with it. In this work we propose the r-TSALBP, a multiobjective model for assembly line balancing to search for the most robust line configurations when demand changes. The robust model definition considers a set of demand scenarios and presents temporal and spatial overloads of the stations in the assembly line of the products to be assembled. We present two multiobjective evolutionary algorithms to deal with one of the r-TSALBP variants. The first algorithm uses an additional objective to evaluate the robustness of the solutions. The second algorithm employs a novel adaptive method to evolve separate populations of robust and non-robust solutions during the search. Results show the improvements of using robustness information during the search and the outstanding behavior of the adaptive evolutionary algorithm for solving the problem. Finally, we analyze the managerial impacts of considering the r-TSALBP model for the different organization departments by exploiting the values of the robustness metrics.     

Optimizing the number of stations in assembly lines under learning for limited production

This paper considers finding the optimal number of stations for an assembly line producing a limited quantity of a new product under learning conditions. This type of production characterizes heavy products (such as airplanes and communication systems) and science-based industries (e.g. laser cutting devices and special equipment for hospitals). These products are manufactured in assembly line fashion in small batches of a few hundred. Since the products are assumed to be totally new to the workers, the learning phenomenon is significant (i.e. task times decrease from cycle to cycle as experience is gained). Therefore, standard balancing methods are no longer applicable. Determining the number of stations has a large effect on the production rate while the actual assignment of tasks to stations helps to fine tune the cycle time. Thus, the number of stations can be regarded as a strategic decision variable . This paper discusses two ways for determining the optimal number of stations, namely as a cost minimization problem and as a profit maximization problem.     

Union–Firm Bargaining as a Repeated Game and the Behaviour of Wages over the Business Cycle

This paper studies a repeated game between a union and a firm in the presence of revenue fluctuations. The simple setup, mainly based on Schultz’s (1995) model, gives support to the idea that the existence of a long-term relationship may change the predictions of the static one-shot model of wage and employment determination in unionized labour markets. In particular, when revenue is fluctuating and the discount factor is moderate the players can commit themselves to some ‘second best’ strategies, rather than playing non-cooperative strategies. As a consequence of the enforcement problems a flat wage over the business cycle may arise. This analysis suggests that ‘second best’ strategies allowing for a pro-cyclical wage as well as for a counter-cyclical wage are feasible. However, when the discount factor decreases and approaches a certain threshold value the parties cannot do better than play a wage constant over the cycle. Moreover, the resulting wage varies less than the employment level, in accordance with the empirical evidence.