ASSEMBLY LINE BALANCING IMPLEMENTATION IN MINOR AND SUB ASSEMBLY WORK SHOP AT SHIPYARDS

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.

This article presents a novel approach for the automated design of assembly lines that combines the assembly line balancing problem with resource selection and the positioning of the chosen resources into one single optimisation problem. Existing approaches for the automated planning of assembly plants either focus on one planning step or work through different planning steps sequentially. So far, no method exists that sufficiently takes into account the interdependency between the selection and positioning of resources. This article addresses this problem by presenting a bi-level optimisation approach for the automated design of assembly lines. A nested genetic algorithm is used to solve an assembly line balancing problem that includes the selection of production resources while simultaneously considering the layouting options for the chosen resources. Three examples for the evaluation and validation of the algorithm are presented. The presented approach is economically promising as the design of assembly lines requires a lot of expert knowledge and is still mostly done manually.

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...

Multi-objective Early-stage Design of Automotive Hybrid Assembly Lines

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.

AutomationML as Seamless Data Exchange Format for Integration of Automated Planning Tools for Assembly Line Design

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.

Automated design of multi-station assembly lines

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

Design of assembly lines is a knowledge intensive process relying significantly on experience and associated with high costs, long lead times and high probability of risks and reworks. This paper presents a methodology to support the early stage design of assembly lines through Knowledge Based Engineering (KBE). In this introductory paper the authors discuss the methodology to implement the KBE approach. A set of system engineering rules is extracted from direct interviews and domain best practices and knowledge about product and process is formalized. These rules will be implemented in a user-friendly platform allowing the design of first phase line layout by taking the defined system requirements (e.g. cycle time) as input. Then, the KBE approach is extended to a specific case study taken from the powertrain sector.

Large scale manufacturing companies are growing along with ever-increasing demand from consumers, one of which is the heavy equipment industry. Excavators are the products of the heavy equipment division at XYZ Corp, where the Excavator assembly lines are single-model. Based on observations of existing conditions that occur at XYZ Corp, the production still cannot meet the demands of consumers. In the assembly process, the Excavator has a significant time difference from each work station, the distribution of work elements in the assembly process is uneven. In the Final assembly section (Zone C) there is a discrepancy between the takt time of Excavator products which is one reason for not achieving the demand. In resolving these problems, a line balancing process is needed, namely balancing workloads on each workstation. This study applies the Heuristic Priority Rules method as an initial solution and allocation constraint should be added as input from the Genetic Algorithms method to complete line balancing with a single-model system. Problems can be solved by increasing line efficiency from existing conditions by 60.4% to 91.74% and Smoothness index which decreases from 955.54 to 158.3977. The proposed result of balancing the final assembly of the excavator results in a better balance of assembly lines.

Purpose This paper aims to propose an improved Moth Flame Optimization (I-MFO) algorithm to optimize the cost-oriented two-sided assembly line balancing (2S-ALB). Prior to the decision to assemble a new product, the manufacturer will carefully study and optimize the related cost to set up and run the assembly line. For the first time in ALB, the power cost is modeled together with the equipment, set up and labor costs. Design/methodology/approach I-MFO was proposed by introducing a global reference flame mechanism to guide the global search direction. A set of benchmark problems was used to test the I-MFO performance. Apart from the benchmark problems, a case study from a body shop assembly was also presented. Findings The computational experiment indicated that the I-MFO obtained promising results compared to comparison algorithms, which included the particle swarm optimization, Cuckoo Search and ant colony optimization. Meanwhile, the results from the case study showed that the proposed cost-oriented 2S-ALB model was able to assist the manufacturer in making better decisions for different planning periods. Originality/value The main contribution of this work is the global reference flame mechanism for MFO algorithm. Furthermore, this research introduced a new cost-oriented model that considered power consumption in the assembly line design.

The Samota Road access development project continued in Sumbawa Regency is one part of the Samota area development project which acts as access to mobilization and supports the acceleration of development, economy, social and culture. In large-scale road works, heavy equipment is needed to facilitate work in a relatively shorter time. Errors in the operating time of heavy equipment and differences in the work field will affect cycle time and have an impact on productivity. This study aims to determine the amount of heavy equipment cycle time, heavy equipment productivity, and the effect of cycle time on heavy equipment productivity. The methods used in this research are time study and correlation methods. The time study method is a measurement of work by collecting data based on the time needed to complete a job so that productivity can be calculated, while the correlation method is an analysis to determine the level of relationship between the independent variable (X) and the dependent variable (Y).Based on data analysis, the value of cycle time, productivity and the effect of cycle time on heavy equipment productivity were obtained. In segment 1, the cycle time of the motor grader is 303,247 seconds with a productivity of 916,037 m2/hour and the cycle time of the vibratory roller is 612,345 seconds with a productivity of 1061,400 m3/hour. For the effect of cycle time on the productivity of the motor grader, the correlation test result is 0,986 and the vibratory roller is 0,999. In segment 4, the motor grader cycle time is 316,107 seconds with a productivity of 831,112 m2/ hour and the vibratory roller cycle time is 655,370 seconds with a productivity of 988,200 m3/hour. For the effect of cycle time on motor grader productivity, the correlation test results were obtained at 0,975 and vibratory roller at 0,999. In both segments, there is a very strong influence and relationship between variable X (cycle time) and variable Y (productivity).

Clustering of geometric objects is a very familiar and important problem in many different areas of applications as well as in the theoretical foundation of some modern fields of computer science. This paper describes how design problems, especially the design of an assembly line, can be transformed into a clustering problem. In order to solve the problem for large sizes of input data we introduce a structure, called Voronoi Tree, which applied to our real world data (assembly line design) did not only reduce the time to get a feasible design of an assembly line dramatically, but additionally increased the value of the design by more than 30% (in comparison with standard design methods). In addition to this we introduce a clustering method which is of interest for those applications which can be transformed to planar clustering problems. In this particular case it is possible to compute an (hierarchically) optimized clustering with resp. to a large class of clustering measures in timeO(nn1/2log3n+UF(n)nn1/2+PF(n)) [n: number of points;UF(n), PF(n) dependent on the chosen clustering measure].

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.