Assembly line design in final assembly excavator at XYZ Corp using genetic algorithm

Purpose – This study seeks to present a simple assembly line design and its balance for a low‐volume manufacturing company.Design/methodology/approach – The study presents experiences with the design and implementation of a simple assembly line. The implementation concerns three aspects; design and construction of the assembly line, the assembly analysis of the product, and then balancing of the line. It also discusses construction and implementation difficulties of this tactical tool in the case company.Findings – The study presents some outcomes from the design, implementation, and balancing of an assembly line for SMEs.Research limitations/implications – The study is limited by the case company and its experience.Practical implications – This study is not pure theoretical study, it has application stages for industry, and it provides some real interface for the people from SMEs.Originality/value – The approach has an original value in respect of implementation of assembly line for a small manufacturing...

In Line Balancing principles, the total workload in the assembly process is divided as evenly as possible among the workstations, without violating the sequences and relations in the assembly operations. Line balancing is important in an assembly system as it balances the line and increases the efficiency, as well as the productivity of a system. A case study was conducted in the assembly line of an electrical accessories manufacturer in Malaysia. The cycle time for each station was recorded, and the standard cycle time was estimated. The productivity, as well as the efficiency of the current assembly line, were studied. In terms of the productivity, the performance of the current systems was 500 units/worker/day, while the expected productivity was 600 units/worker/day. An assembly line setting was proposed based on the Line Balancing Method; the productivity for the proposed line increased to 671 units/worker/day, or in rough additional increase around 34%.

PurposeCycle time fluctuations in assembly lines are one of the important reasons of re‐balancing. As a result of re‐balancing of assembly lines, it will be necessary to change task sequences or equipment locations. The purpose of this paper is to find the task sequence which enables assembly line balancing (ALB) with minimum number of stations (NS) for different cycle times such that tasks and equipment or fixture locations remain unchanged.Design/methodology/approachIn this paper a heuristic which consist of two stages is proposed to find a common task sequence for different cycle times in assembly lines.FindingsIt is shown that optimal NS for different cycle times can be achieved with a fixed task sequence.Research limitations/implicationsThe approach is limited to a single model case. Model variety together with cycle time variety can be investigated in further studies.Practical implicationsAssembly lines which require less time and cost for re‐balancing can be easily designed by the proposed approach.Originality/valueALB problem is handled with a new viewpoint. Also, it is observed that the proposed approach serves as a bridge between assembly line design and balancing. In this regard, it is thought to have an important place in the ALB literature.

A Simulation Study on the Layout Design of Micro Assembly Line for Lens Module

Traditionally assembly line balancing problems have been examined under the assumption of serial work station design. Thus no pair of work stations could be simultaneously working on the same copy of a product. This paper presents two models for which this assumption is dropped. The algorithms developed for operational design of such assembly lines are presented along with sample problems to demonstrate the computational procedures and advantages of these models.

Configuration changes of customizable products during assembly are disruptive for the assembly line and are therefore often avoided. Nevertheless, allowing changes to customer-specific product configurations until late steps into the final assembly can be a competitive advantage as long as the negative effects on the assembly line can be mitigated. This paper proposes a method to efficiently handle such configuration changes while keeping the disruption of the assembly line as minimal as possible. The method assesses the criticality of change requests based on their severity and the assembly progress of the product. Based on this categorization an optimal time slot during the assembly process is identified to perform any additional work associated with a change request. These additional work contents can occur from necessary disassembly and different or additional assembly processes. The validation of the method for a final assembly line of large and complex products showed that it can reduce the additional workload by 26 % and the prolongation of the throughput time by 78 % on average.

Printed Circuit Boards (PCBs) are widely used in most electronic devices. Typically, a PCB design has a set of components that needs to be assembled. In a broad sense, this assembly task involves placing PCB components at designated location on a PCB board; fixing PCB components; and testing the PCB after assembly operation to ensure that it is in proper working order. The stringent requirements of having a higher component density on PCBs, a shorter assembly time, and a more reliable product prompt manufacturers to automate the process of PCB assembly. Frequently, a few placement machines may work together to form an assembly line. Thus, the application of more than one machine for component placement on a PCB presents a line-balancing problem, which is basically concerned with balancing the workload of all the machines in an assembly line. This paper describes the application of a new artificial intelligence technique known as the immune algorithm to PCB component placement as well as the line balancing of PCB assembly line. It also includes an overview of PCB assembly and an outline of the assembly line balancing problem. Two case studies are used to validate the IA engine developed in this work. The details of IA, the IA engine and the case studies are presented.

Enumerations and stability analysis of feasible and optimal line balances for simple assembly lines

This paper presents a heuristic procedure for balancing production assembly lines and a computer program for carrying out that procedure. This research was undertaken to investigate the application of complex information processing techniques (as used in producing the Chess Machine and Logic Theorist) to a typical industrial problem. The assembly line balancing problem is stated as: Given an assembly process made up of elemental tasks, each with a time required per unit of product and an ordering with other tasks, what is the least number of work stations needed to attain a desired production rate? The heuristic procedure for assembly line balancing consists of three phases: repeated simplification of the initial problem by grouping adjacent elemental tasks into compound tasks; solution of the simpler problems thus created by assigning tasks to work stations at the least complex level possible, breaking up the compound tasks into their elements only when necessary for a solution; smoothing the resulting balance by transferring tasks among work stations until the distribution of assigned time is as even as possible. The heuristics used in each phase are considered in some detail. Appropriate means for mechanizing such a procedure are discussed, and operating results of the program on actual problems are presented.

The most important factor affecting efficiency and ergonomic risk levels in an assembly line design is the problem of assigning certain tasks to certain stations, namely the assembly line balancing problem. In the literature, assembly line balancing problem has often been studied, but studies that consider ergonomic risks are deficient. Recently, it has been one of the issues that have started to attract great attention with the realization of health problems caused by assembly lines. To this end, in this study, a bi‐objective mathematical model is developed that considers balancing assembly line station time and ergonomic risk levels, simultaneously. It is aimed to minimize both station time and the total deviations of ergonomic risk scores for the stations. Weighted sum and conic scalarization methods are applied to solve the bi‐objective model. To analyze the outcomes of the developed model, an application is proposed and tested on a real industrial case, at a home appliance assembly line. The deployment of the OMAX method is a contribution to the literature since it shows an analysis tool which evaluates the results of assembly line balancing. This method evaluates the performance of the stations based on different criteria such as station time and ergonomic risk. The number of high‐risk stations is obtained as 13 in the single‐objective model aiming to minimize the station time, while it is found to be nine in the bi‐objective model solved with CSM, without an increase in the total number of stations.

Assembly lines with fractional tasks increase the throughput with a better workload balancing among the stations. The possibility to share tasks between two consecutive stations can also support the design of assembly lines with redundancies of the tasks. The redundancy of the tasks allows reacting to short failures or variations in processing time. This paper proposes a framework to support the design and control of redundancy assembly lines. The first problem concerns a modified mixed-integer linear programming model used for the fractional allocation assembly line problem to design redundancy assembly lines. Then, this research proposes control policies to manage the allocation of the tasks shared between two consecutive stations. Finally, the simulation evaluates the performance of the proposed methods to handle short failures and uncertain processing times. The numerical results show the potential improvements of the proposed methods with a limited number of redundancies. The main improvements concern the reduction of throughput time and work in process.

The right amount of labor on work station is important to avoid uneven workload, that might reduce efficiency on production line, and cause bottleneck. Therefore, this research focus at searching the optimal amount of labor using line balancing and bottleneck that occurs on XYZ Fish Crackers Factory. Theory of constraints method is used to identify bottleneck, and line balancing method that will be used is Kilbridge-Wester, Moodie Young, Helgeson-Birnie, and J-Wagon. Fish cracker drying is the process that encounter bottleneck. The beginning line efficiency is 50.09%, with Kilbridge-Wester, Helgeson Birnie, and J- Wagon method, the line efficiency is 89.22%, and with Moodie Young method, the line efficieny is 89.45%. Therefore, Moodie Young method is the best method to apply, because it has the best result, with 89.45% line efficiency, 10.55% balance delay, 13.96% smoothness index, 20.3 minutes of idle time, 5 work station, and amount of labor needed is 10 person.

PT. DEF is a manufacturing company that produces lighting fixture. Light Emitting Diode (LED) down-light is one of the company flagship products. With the new type (LGB72316 LE1 and LGB72317 LE1) and the company's policy not to add man-power in production units lead automatically in addition of work hours on the production schedule that’s resulting in increased overtime. After a series of data collection and testing, as well as the determination of standard time on the assembly line work related, research shows that low line efficiency (66.55%) and the balance delay is high (33.45%). This is an indication of poor performance related on the assembly line. Line balancing would be an alternative problem solving tools to overcome these problems. This study tried to draft a new balancing method Helgeson-Birnei, Moodie Young and Kilbridge-Wester Heuristics. Of a series of procedures that have been performed, the method Kilbridge-Wester Heuristics showed the best results. The method is able to improve performance by reducing cycle time, product of 35.17 seconds / products became 32.88 seconds / products and generate 6 work stations with 6 operators, line efficiency 94.91%, balance delay 5.09%, smoothness index of 6,224 and labor cost saving of Rp 7,215,011.27 per month.

RNA-Seq dataset of thoracic ganglia transcriptome across four ovarian development stages in Fenneropenaeus merguiensis

In this chapter, a system to support the design of assembly and production lines used in the make-to-order production phase is presented. The relevance of the system is supported by the fact that current market dynamics often leads to frequent modifications in the allocation of manufacturing resources, and, as a result, decisions related to manufacturing systems design that used to belong to the strategic level are now taken at the tactical level, and thus require new tools to support them.The decision support system addresses two different categories of problems: (i) assembly line balancing and (ii) production line balancing. Due to the high complexity of these problems, it uses heuristic methods based on evolutionary computation approaches to tackle them. The system aggregates several modules to address the different problems, a database to handle both input and output data and an interface that enables a user-friendly interaction with the decision maker.