Real-time information driven intelligent navigation method of assembly station in unpaced lines

This paper considers the assembly station as a breakthrough to improve the real-time information driven control and optimization of assembly process in unpaced asynchronous line. By adopting automatic identification technologies, the overall architecture of the real-time intelligent navigation of assembly station (INoAS) is put forward. Under this architecture, three core services, namely the real-time assembly operating guidance service (OGS), collaborative production service (CPS) among assembly stations and real-time queuing service (RQS) of the jobs at each station, are designed to provide optimal and dynamical navigation for assembly activities for each station. Then, the disturbances and exceptions could be timely captured by installing the INoAS at each station, and the operating guidance, collaborative production information sharing and real-time queuing could be easily achieved. The presented architecture and services of INoAS will facilitate the real-time information driven process monitor and control between the line and stations.     

Algorithms for scheduling jobs on two serial duplicate stations

In automated assembly or production lines, some stations are duplicated due to their long cycle times. Material handling considerations may require these stations to be arranged in series rather than in parallel. Each job needs to be processed on any one of the duplicate stations. This study deals with scheduling of n available jobs on two serial duplicate stations in an automated production line. The performance measures considered are mean flowtime, makespan, and station idle time. After the problem is formulated, two algorithms are developed to determine the optimal schedules with respect to the performance measures.     

Minimizing makespan on a single burn-in oven with job families and dynamic job arrivals

This paper considers a scheduling problem for a single burn-in oven in the semiconductor manufacturing industry where the oven is a batch processing machine and each batch processing time is represented by the largest processing time among those of all the jobs contained in the batch. Each job belongs to one of the given number of families. Moreover, the release times of the jobs are different from one another. The objective measure of the problem is the maximum completion time (makespan) of all jobs. A dynamic programming algorithm is proposed in the order of polynomial time complexity for a situation where the number of job families is given (fixed). A computational experiment is performed to compare the time complexity of the proposed algorithm with that of another exact algorithm evaluating all possible job sequences based on batching-dynamic programming (BDP). The results of the experiment show that the proposed algorithm is superior to the other.Scope and purposeThis paper considers a scheduling problem on the burn-in operation in a semiconductor manufacturing process. The burn-in operation is a bottleneck process in the final testing process which is one of four major steps including wafer fabrication, wafer probe, assembly, and final testing steps. Thus, its scheduling is very important to improve the productivity of the whole manufacturing line. The objective of this paper is to find a solution technique that will find the optimal schedule that minimizes makespan for problems which are found in the semiconductor manufacturing industry.     

Mean value analysis of re-entrant line with batch machines and multi-class jobs

We propose an approximate approach for estimating the performance measures of the re-entrant line with single-job machines and batch machines based on the mean value analysis (MVA) technique. Multi-class jobs are assumed to be processed in predetermined routings, in which some processes may utilize the same machines in the re-entrant fashion. The performance measures of interest are the steady-state averages of the cycle time of each job class, the queue length of each buffer, and the throughput of the system. The system may not be modeled by a product form queueing network due to the inclusion of the batch machines and the multi-class jobs with different processing times. Thus, we present a methodology for approximately analyzing such a re-entrant line using the iterative procedures based upon the MVA and some heuristic adjustments. Numerical experiments show that the relative errors of the proposed method are within 5% as compared against the simulation results.Scope and purposeWe consider a re-entrant shop with multi-class jobs, in which jobs may visit some machines more than once at different stages of processing, as observed in the wafer fabrication process of semiconductor manufacturing. The re-entrant line also consists of both the single-job machine and the batch machine. The former refers to the ordinary machine processing one job at a time, and the latter means the machine processing several jobs together as a batch at a time. In this paper, we propose an approximation method based on the mean value analysis for estimating the mean cycle time of each class of jobs, the mean queue length of each buffer, and the throughput of the system.     

Mixed-model assembly line balancing using a multi-objective ant colony optimization approach

Mixed-model assembly lines are production systems at which two or more models are assembled sequentially at the same line. For optimal productivity and efficiency, during the design of these lines, the work to be done at stations must be well balanced satisfying the constraints such as time, space and location. This paper deals with the mixed-model assembly line balancing problem (MALBP). The most common objective for this problem is to minimize the number of stations for a given cycle time. However, the problem of capacity utilization and the discrepancies among station times due to operation time variations are of design concerns together with the number of stations, the line efficiency and the smooth production. A multi-objective ant colony optimization (MOACO) algorithm is proposed here to solve this problem. To prove the efficiency of the proposed algorithm, a number of test problems are solved. The results show that the MOACO algorithm is an efficient and effective algorithm which gives better results than other methods compared.     

基于遗传算法的焊接生产线工位平衡规划方法

在现代化大规模大批量的流水装配制造业中,数量众多的作用分配和多工位的合理安排使工位平衡问题显得更为突出。针对第一类工位平衡问题,即在给定的生产节拍下最小化工位数,首先分析了该问题并建立了数学模型,进而提出了一种基于改进遗传算法求解工位平衡问题的方法。该算法以焊接任务的操作顺序优先关系为约束前提,在初始种群的生产以及交叉和变异过程中保证了染色体解的可行性,同时在遗传算法的选择过程中考虑了具有相同工位数的最优作业方案的工时标准差,从而提高了算法的搜索效率和解的可靠性。最后通过实例求解验证了该算法的有效性。     

Evolutionary algorithms for flowshop sequencing with non-unique jobs

Sequencing problems are difficult combinatorial problems because of the extremely large search space of possible solutions and the large number of "local" optima that arise. Unlike other NP-hard combinatorial problems, the search space, in general, for sequencing problems (under the makespan objective) consists of sequences with objective function values that lie within only a relatively small amount of each other. This means that when a change is made to the sequence, an improvement or non-improvement is not easily recognised. This makes the problem much more difficult to solve. A number of constructive heuristics exist that obtain good solutions in a short period of time, however, the output of such algorithms is generally a single sequence which may not be feasible or preferred with respect to industry constraints. Other heuristic algorithms such as Simulated Annealing (SA) and Tabu Search (TS) have also been applied and successes have been reported. However, the performance is dependent upon a number of finely tuned parameters and the output is again only a single solution. For these reasons, Evolutionary Algorithms (EAs) may be suitable solution strategy, for which limited research has been performed. In this research, a number of new EAs have been proposed and a number of modifications have been made to several constructive algorithms to cope with non-unique jobs or jobs with multiple demands. A numerical comparison of a number of benchmark problems and real data of a truck assembly line has also been presented.     

面向虚拟环境的装配体模型研究

人机交互是虚拟装配的本质特性和技术瓶颈，能反映交互过程的装配体模型构造，是虚拟装配领域的一个关键问题，给出一种时序的装配体模型，对时序的聚合关系、时序的约束关系以及时序的行为结构给出定义和分析，为实现该模型，还给出了零件的中间模型和对象复杂行为构造，同时对虚拟装配直接操作的交互过程、交互模式及装配工艺知识给出了时序的形式描述，这是连接人机交互与装配体模型以及模型与工艺生成的桥梁．一致的表示模型减少了交互装配信息的冗余性，有利于提高交互信息的复用，为交互生成工艺提出了新方法。     

Minimizing the number of stations and station activation costs for a production line

In the problem under study, a paced unidirectional machining line, consisting of a number of stations, has to be configured to produce parts of several types. A given set of operations is required for each part type and the same operation can be required for different part types. Re-assignment of operations, when switching from one part type to another, is not allowed. All operations assigned to the same station are performed simultaneously. The objective is to assign operations to stations in order to minimize the number of stations and the station activation costs, with respect to precedence and zoning constraints. The two objectives are considered in a lexicographic order, the former being the primary objective. Activation costs refer to the costs induced by the energy consumption, equipment maintenance, setup activities or labor requirement which occur whenever a station is used. Computational complexity for various special cases is established. Heuristic algorithms, integer linear programming formulations, and computer experiments are presented. Instances of practical dimension, with 40–80 operations, are solved in an hour on a conventional computer.     

时间偏移下的多源目标精确定位方法

采用到达时间( TOA)测距实现源目标定位的方法比较简单,因此在无线传感器网络定位领域得到了广泛的应用。将TOA定位模型转化为线性优化问题,提出了一种存在时间偏移下的多源目标精确定位方法。该方法将定位计算过程分成两步,包括多源目标位置初始值估计和优化计算过程。两步计算方法将定位结果用代数解表示,避免了数值计算过程中的局部最优问题。仿真分析了时间偏移量及噪声大小对定位误差的影响。结果表明即使存在较大的时间偏移量,优化计算后的定位误差也能非常接近于克拉美罗( CRLB)下界值。     

The type E simple assembly line balancing problem: A mixed integer linear programming formulation

Although the simple assembly line balancing problem (SALBP) is the topic of many studies, typically they either consider minimizing the number of stations for a given cycle time (called type one), or minimizing the cycle time for a given number of stations (called type two). Rarely, type E of the problem has been considered. In the type E, cycle time and number of stations are both decision variables, and the objective is to maximize the line efficiency. This paper presents a mixed integer linear programming formulation for the type E simple assembly line balancing problem. Moreover, to further strengthen the presented formulation, two enhancement techniques in the form of valid inequalities and auxiliary variables are proposed. As the secondary objectives of the problem, minimization of the number of stations, the cycle time, and the smoothness index are studied as well. In the case of workload smoothing, three different linearization methods are employed and compared for minimizing the smoothness index. The results of computational study on the benchmark data set demonstrate the efficacy of the improved formulation     

新一代天气雷达开关及触发器组件快速检修系统设计

针对新一代天气雷达发射机开关和触发器组件故障频发,维修时效长,难度大等特点,提出了一种能够快速、便捷、高效、安全的新一代天气雷达开关和触发器组件关键芯片自动快速检测系统设计方案。该自动检测系统采用了机外脱机测试方法从而保证了雷达设备和人身的安全。该自动检测系统采用了发光二极管指示灯输出测试结果的自动快速测试方式,保证了雷达修复的较短时效。该自动检测系统直接测试雷达开关和触发器组件内部电路板常用关键芯片,而不是更换整个笨重的分机组件备件,从而使得维修新一代天气雷达故障变得便捷高效。新一代天气雷达开关和触发器快速检修系统研制完成后在多个台站得到了试用,试用实例结果表明其效果良好,可以给全国其他新一代天气雷达站快速维修新一代天气雷达提供借鉴和参考。     

Automated generation of assembly system-design solutions

Any assembly system-design problem which consists of generating system configurations and assignment of tasks to the stations has a set of solutions. The number of feasible solutions may be staggering, even for products consisting of a relatively small number of parts assembled on a small number of stations. As the size of the product and the assembly system grow, it may become difficult to develop a complete set of design solutions for in-depth analysis. Here an automated method is described by which the complete sets of system configurations and assembly sequences may be generated, and feasible solutions, consisting of a matched element from each set, can be rapidly derived. These solutions may then be tested for various performance metrics, some of which may not be expressed mathematically. In designing assembly systems, the layout of stations and the assignment of assembly tasks to these stations are important design problems. This paper proposes a set of algorithms to quickly generate the configurations of the assembly system and assign tasks to the configurations. Once the matching of tasks to the configurations is complete, the performance of these various design alternatives, such as productivity, can be evaluated to allow selection of configurations with the best performance.     

Assembly line balancing and group working: A heuristic procedure for workers’ groups operating on the same product and workstation

In this paper, we examine an assembly line balancing problem that differs from the conventional one in the sense that there are multi-manned workstations, where workers’ groups simultaneously perform different assembly works on the same product and workstation. This situation requires that the product is of sufficient size, as for example in the automotive industry, so that the workers do not block each other during the assembly work. The proposed approach here results in shorter physical line length and production space utilization improvement, because the same number of workers can be allocated to fewer workstations. Moreover, the total effectiveness of the assembly line, in terms of idle time and production output rate, remains the same. A heuristic assembly line balancing procedure is thus developed and illustrated. Finally, experimental results of a real-life automobile assembly plant case and well-known problems from the literature indicate the effectiveness and applicability of the proposed approach in practice.     

Two-sided assembly line balancing considering the relationships between tasks

Previous studies of the two-sided assembly line balancing problem assumed equal relationships between each two tasks assignable to a side of the line. In practice, however, this relationship may be related to such factors as the distance between the implementation place and the tools required for implementation. We know that the more relationships exist between the tasks assigned to each station, the more efficient will be the assembly line. In this paper, we suggest an index for calculating the value of the relationship between each two tasks, and define a performance criterion called ‘assembly line tasks consistency’ for calculating the average relationship between the tasks assigned to the stations of each solution. We propose a simulated annealing algorithm for solving the two-sided assembly line balancing problem considering the three performance criteria of number of stations, number of mated-stations, and assembly line tasks consistency. Also, the simulated annealing algorithm is modified for solving the two-sided assembly line balancing problem without considering the relationships between tasks. This modification finds five new best solutions for the number of stations performance criterion and ten new best solutions for the number of mated-stations performance criterion for benchmark instances.     

Queueing-model based analysis of assembly lines with finite buffers and general service times

In this paper, we study the production process on multi-stage assembly lines. These production systems comprise simple processing as well as assembly stations. At the latter, workpieces from two or more input stations have to be merged to form a new one for further processing. As the flow of material is asynchronous with stochastic processing times at each station, queueing effects arise as long as buffers provide waiting room. We consider finite buffer capacities and generally distributed processing times. Processing is a service operation to customer items in the sense of a queueing system. The arrival stream of customer items is generated by processing parts at a predecessor station. This paper describes an approximation procedure for determining the throughput of such an assembly line. Exact solutions are not available in this case. For performance evaluation, a decomposition approach is used. The two-station subsystems are analyzed by G/G/1/N$G/G/1/N$ stopped-arrival queueing models. In this heuristic approach, the virtual arrival and service rates, and the squared coefficients of variation of these subsystems are determined. A system of decomposition equations which are solved iteratively is presented. Any solution to this system of equations indicates estimated values for the subsystems’ unknown parameters. The quality of the presented approximation procedure is tested against the results of various simulation experiments.     

An efficient branch and bound algorithm for assembly line balancing problems with parallel multi-manned workstations

In the event that big-sized complex products (containing a large number of assembly tasks most of which have long task times) are produced in simple or two-sided assembly lines, hundreds of stations are essentially required. Long product flow time, a large area for establishment of the line, a high budget for the investment of equipment, and tools in stations and several work-in-process are also required for these kinds of products. In order to avoid these disadvantages, assembly lines with parallel multi-manned workstations can be utilized. In this paper, these lines and one of their balancing problems are addressed, and a branch and bound algorithm is proposed. The algorithm is composed of a branching scheme, some efficient dominance and feasibility criteria based on a problem-specific knowledge. A heuristic-based guidance for enumeration process is included as an efficient component of the algorithm as well. VWSolver algorithm proposed for a special version of the problem in the literature has been modified and compared with the proposed algorithm. Results show that proposed algorithm outperforms VWSolver in terms of both CPU times and quality of feasible solutions found.     

Fuzzy logic control of automated screw fastening

In this paper, we present an intelligent control strategy for automated screw fastening. In automated assembly processes, there are often found dedicated stations for various types/sizes of screw fastening. Problems found in current processes include cross-threading, screw jamming, slippage and the need to apply precise torque. The intelligent controller developed here supervises the integrated process of an electric driver mounted on a robotic positioning system to fasten screws. The new scheme controls continuously the motion and driving stages to avoid process-caused failures, to achieve a desired precise torque and to detect bad parts at early stages of the assembly. Initial simulation results are encouraging.     

不确定环境下的航空发动机装配线适应性调度方法

航空发动机装配是航空发动机制造过程的关键环节,其工序多,流程复杂,生产过程中扰动频发,如装配时间波动、不合格返工等.针对不确定环境下的航空发动机装配线的调度问题,提出一种基于门控循环神经网络(GRU)的适应性调度方法.该调度方法包含扰动识别和调度规则调整两个部分:扰动识别模块以滑动时间窗口为周期,利用GRU神经网络进行渐近型扰动的识别;调度规则调整模块以扰动识别的结果为触发,通过构建基于GRU神经网络的调度规则决策模型,输出适配当前生产状态的新的调度规则,用以指导生成更新的调度方案.最后,以某航空发动机装配线为研究案例,对所提出适应性调度方法进行验证分析.对比实验结果表明,所提出方法能够有效提升装配线的设备利用率、日均生产率等性能.     

融合规则的HEDA求解带工件批量运输的三阶段装配集成调度问题

针对现有三阶段装配集成调度问题模型将各工件在运输阶段的运输时间简化设定为相同常量,未考虑运输车辆数量和车载重量有限会导致工件需按批量分别运输的实际情况,研究以最小化总完工时间为目标的带工件批量运输的加工、运输、装配三阶段装配集成调度问题(three-stage assembly integrated scheduling problem with job batch transportation,3sAISP_JBT)和求解算法.首先,分阶段建立3sAISP_JBT的数学模型;其次,分别提出求解运输、装配阶段对应子问题的先完工先运输(first completed first transported,FCFT)规则和先到先装配(first come first assembly,FCFA)规则,以降低求解3sAISP_JBT的整体计算复杂度;再次,提出一种融合多种规则的混合分布估计算法(hybrid estimation of distribution algorithm with rules,HEDA_R)求解3sAISP_JBT;最后,通过仿真实验和算法比较验证了所提出算法的有效性.