Robotic assembly of printed circuit boards with component feeder location consideration

The use of industrial robots for the assembly of printed circuit boards (PCB) is fast gaining popularity. Minimization of the time required for board assembly while maintaining production quality is the process planner's main task. This task involves the specification of the insertion sequence of components in their respective locations and the assignment of component types to feeders or dispensing magazine slots. The time taken by a robot to fetch a component for insertion is dependent on the location of the feeder that holds the component type. Similarly, board assembly lime is dependent on the order of component insertion on the board and the fetch time of components between insertions. In this paper, models to minimize the total assembly time for a board are developed and studied. Factors considered in the analysis of the assembly time are the component assignment to magazine     

Job sequencing and component set-up on a surface mount placement machine

In this paper, the problem of sequencing PCB assembly jobs on an automatic SMD placement machine is addressed. The objective is to minimize the makespan. Moreover, both the job arrival times and the precedence constraints for those jobs requiring component placement on the primary and secondary side of the same board must be taken into account. A considerable set-up time occurs when switching from one board type to another, which depends on the number of component feeders to be replaced in the magazine of the assembly machine. The exchange of component feeders is complicated by the fact that each feeder occupies a different number of magazine positions. Theoretically, the minimum makespan required for a given batch of jobs could be derived by solving the order sequencing and the component set-up problems simultaneously. However, optimal solutions are practically unattainable for problems of realistic size. Therefore, efficient heuristic solution procedures are developed which exploit component commonality between PCB types. The numerical results obtained indicate the practicality of the proposed heuristics in an industrial application.     

Production scheduling in SMT electronic boards assembly

This paper tackles the problem of scheduling in the assembly of SMT electronic boards. In particular, it focuses on a new scheduling method developed within the framework of an industry-university joint research project. The scheduling system aims at minimizing the makespan; this goal is achieved by reducing setup times and idle times of the machines. As an example, the outcome of a test carried out on a production mix made up of 10 board types is presented and analyzed in a summarized form.     

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 heuristic approach for component scheduling on a high-speed PCB assembly machine

The collect-and-place machine is one of the most widely used placement machines for assembling electronic components on the printed circuit boards (PCBs). Nevertheless, the number of researches concerning the optimisation of the machine performance is very few. This motivates us to study the component scheduling problem for this type of machine with the objective of minimising the total assembly time. The component scheduling problem is an integration of the component sequencing problem, that is, the sequencing of component placements; and the feeder arrangement problem, that is, the assignment of component types to feeders. To solve the component scheduling problem efficiently, a hybrid genetic algorithm is developed in this paper. A numerical example is used to compare the performance of the algorithm with different component grouping approaches and different population sizes.     

On vendor part delivery dates in a stochastic assembly system

This paper describes the development of a model for the determination of optimal mean part delivery dates in a stochastic assembly system for the objective of minimizing the expected cost of subassembly and part inventory. Parts are assembled at each station to a subassembly. The part delivery and processing times at assembly stations follow known probability distributions. An approximate solution technique based on the optimization of individual stations in isolation is developed. The approximation applies a correction factor, as a function of the variability in part delivery and processing time, cost parameters and number of stations, to the decisions from the single station solutions to compensate for interdependence between stations. Results indicate that this is an effective approach and yields good near-optimal solutions with very little computational effort. Insights regarding the effect of the type of distribution used, random processing times, variance of the distribution used and cost parameter values on part delivery dates are also reported.     

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.     

Mixed-model assembly line sequencing problems

The paper develops a comprehensive classification of mixed-model assembly lines from which four categories of model sequencing are derived. Each category aims at satisfying one or both of two objective criteria, the one minimizing the overall line length, and the other minimizing the thruput time. Approaches for solving the sequencing problem in each category are presented. The paper suggests a design strategy that can be followed by designers of mixed-model assembly lines. Specific topics requiring further research are also defined.     

Improving throughput for an electronic assembly line using a constraint analysis methodology

Electronic assembly operations are vital to industries such as telecommunications, computers and consumer electronics. This paper presents a constraint analysis methodology for planning and improving electronic assembly operations that draws on concepts from queueing theory, simulation and production planning. The proposed methodology identifies the operational bottleneck and predicts the utilization, throughput and lead time of the assembly line. It also quantifies the relationship between yields and utilization for the assembly operations. A case study is presented that applies the methodology at an Ericsson, Inc., telecommunications equipment assembly facility. The constraint analysis methodology provided valuable decision support as the managers of Ericsson evaluated the costs and benefits of additional production capacity. Although the focus of this paper is electronic assembly operations, the methodology can be applied to general flow line assembly systems with feedback loops for test and rework under dedicated high-volume production.     

PCB assembly scheduling through kit concept

This paper presents the design and test of a new scheduling environment dedicated to the off-line scheduling of PCB assembly shops. The main idea introduced is the employment of the 'kit concept' as a scheduling tool, as opposed to the traditional batch scheduling. In the kit approach, the basic PCB aggregations are kits composed of different PCBs matching finished products requirements, instead of homogeneous batches of identical boards. By introducing the kit approach, PCB assembly schedule is intended to be focused more towards the assembly of final products than towards the internal PCB assembly shop constraints and requirements. A simulation model and data from a real assembly system are used to compare the kit approach with traditional batch processing. Experimental results show that the proposed kit approach jointly achieves remarkable improvements in the effectiveness and efficiency performances of the assembly system, as compared to the batch approach. However, it is determined also that these advantages can only be achieved if a sufficiently advanced scheduling system is used.     

自动化立体仓库中出入库任务顺序与出库位置选择集成优化研究

具有多个出口的自动化立体仓库系统是一种将存储和分拣相结合的新型仓储技术,其最典型的特征是在货架底层有很多个出库位置以供取货人员分拣。研究此系统中出入库任务排序与出口选择的集成优化问题,以最小化堆垛机完成所有任务的移动距离为目标,将此问题转化为一个混合整数规划模型。根据问题的特点设计了两阶段启发式算法求解此问题,数值结果表明设计的算法能在较短时间内给出近似最优解,同时与企业常用的先到先服务方法相比,该算法可以缩短超过20%的移动距离。     

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.     

A simulation-based dynamic operator assignment strategy considering machine interference - a case study on integrated circuit chip moulding operations

A simulation-based dynamic operator assignment strategy is proposed considering machine interference in solving an integrated circuit moulding operation problem. The strategy iteratively solves a floating manpower operator-assignment problem between simulation-based diagnostic study and operator assignment decision. Given current-state information, it provides a means for system performance evaluation. It searches a satisfactory solution for both cycle time and service level performances by using floating manpower method. A structured experimental design is used to illustrate the effectiveness of the proposed methodology. Empirical results show promise for the proposed methodology in solving a practical application. Finally, the system implementation constraints from both hardware and management problems are addressed.     

Scheduling algorithms for computer-aided line balancing in printed circuit board assembly

Generalized flexible flow line (GFFL) is a scheduling environment comprising several machine banks which the products visit in the same order but can skip some machine banks. The type of machines in a bank can differ but they are suitable for performing the same manufacturing tasks. To change one product to another demands a set-up operation of the machine. This paper describes several scheduling algorithms for the GFFL problem. The overall structure of these algorithms is similar, consisting of machine allocation and sequencing phases. The algorithms have been integrated into an interactive production scheduling system for electronics assembly. Sample cases are used to illustrate the operation of the system in practice.     

Optimal mixed-model sequencing for balanced assembly lines

This paper describes an algorithm for solving optimally, the mixed-model sequencing problem when assembly line stations are balanced for each model. An optimal sequence is obtained with the minimization of the overall assembly line length for zero station idle time.The algorithm incorporates two basic steps. The first involves a search procedure that generates all cycle sequences; i.e. sequences having identical ‘start’ and ‘finish’ positions and whose work content can be executed within a defined station length. The second step uses integer programming (IP) to determine the number and combination of the various cycle sequences, such that the production demand is satisfied.     

自动化立体仓库中的储位分配及存取路径优化

储位分配和存取作业路径优化是仓储管理中的两个重要决策问题。本文研究如何在自动化立体仓库中对这两个问题进行同时决策。提出了一个混合整数规划模型对该问题进行优化建模,设计开发了一个基于有向连接图的两阶段优化算法对问题求初始解,并利用禁忌搜索算法对所求得的解进行改进。算法第一阶段解决储位分配问题,在此基础上第二阶段利用Hungarian算法对堆垛机的存取作业路径优化问题进行求解。最后利用实例对算法效率和精度进行分析评价,计算结果验证了算法的有效性。     

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.

     

Network Reconfiguration for Increasing Transportation System Resilience Under Extreme Events

Evacuating residents out of affected areas is an important strategy for mitigating the impact of natural disasters. However, the resulting abrupt increase in the travel demand during evacuation causes severe congestions across the transportation system, which thereby interrupts other commuters' regular activities. In this article, a bilevel mathematical optimization model is formulated to address this issue, and our research objective is to maximize the transportation system resilience and restore its performance through two network reconfiguration schemes: contraflow (also referred to as lane reversal) and crossing elimination at intersections. Mathematical models are developed to represent the two reconfiguration schemes and characterize the interactions between traffic operators and passengers. Specifically, traffic operators act as leaders to determine the optimal system reconfiguration to minimize the total travel time for all the users (both evacuees and regular commuters), while passengers act as followers by freely choosing the path with the minimum travel time, which eventually converges to a user equilibrium state. For each given network reconfiguration, the lower‐level problem is formulated as a traffic assignment problem (TAP) where each user tries to minimize his/her own travel time. To tackle the lower‐level optimization problem, a gradient projection method is leveraged to shift the flow from other nonshortest paths to the shortest path between each origin–destination pair, eventually converging to the user equilibrium traffic assignment. The upper‐level problem is formulated as a constrained discrete optimization problem, and a probabilistic solution discovery algorithm is used to obtain the near‐optimal solution. Two numerical examples are used to demonstrate the effectiveness of the proposed method in restoring the traffic system performance.     

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.     

Online tree node assignment with resource augmentation

Given a complete binary tree of height h, the online tree node assignment problem is to serve a sequence of assignment/release requests, where an assignment request, with an integer parameter 0≤i≤h, is served by assigning a (tree) node of level (or height) i and a release request is served by releasing a specified assigned node. The node assignments have to guarantee that no node is assigned to two assignment requests unreleased, and every leaf-to-root path of the tree contains at most one assigned node. With assigned node reassignments allowed, the target of the problem is to minimize the number of assignments/reassignments, i.e., the cost, to serve the whole sequence of requests. This online tree node assignment problem is fundamental to many applications, including OVSF code assignment in WCDMA networks, buddy memory allocation and hypercube subcube allocation.