A multi-decision genetic approach for workload balancing of mixed-model U-shaped assembly line systems

A mixed-model assembly line is a type of production line where a variety of product models similar in product characteristics are produced. As a consequence of introducing the just-in-time (JIT) production principle, it has been recognised that a U-shaped assembly line system offers several benefits over the traditional straight line system. This paper proposes a new evolutionary approach to deal with workload balancing problems in mixed-model U-shaped lines. The proposed method is based on the multi-decision of an amelioration structure to improve a variation of the workload. This paper considers both the traditional straight line system and the U-shaped assembly line, and is thus an unbiased examination of line efficiency. The performance criteria considered are the number of workstations (the line efficiency) and the variation of workload, simultaneously. The results of experiments enhanced the decision process during multi-model assembly line system production; thus, it is therefore suitable for the augmentation of line efficiency in workstation integration and simultaneously enhancement of the variation of the workload. A case study is examined as a validity check in collaboration with a manufacturing company.     

Integrated procedure of balancing and sequencing for mixed-model assembly lines: a multi-objective evolutionary approach

A mixed-model assembly line is a type of production line which is used to assemble a variety of product models with a certain level of similarity in operational characteristics. This variety causes workload variance among other problems resulting in low efficiency and line stops. To cope with these problems, a hierarchical design procedure for line balancing and model sequencing is proposed. It is structured in terms of an amelioration procedure. On the basis of our evolutionary algorithm, a genetic encoding procedure entitled priority-based multi-chromosome (PMC) is proposed. It features a multi-functional chromosome and provides efficient representation of task assignment to workstations and model sequencing. The lean production perspective recognises the U-shape assembly line system as more advanced and beneficial compared to the traditional straight line system. To assure the effectiveness of the proposed procedure, both straight and U-shape assembly lines are examined under two major performance criteria, i.e., number of workstations (or line efficiency) as static criterion and variance of workload (line and models) as dynamic criterion. The results of simulation experiments suggest that the proposed procedure is an effective management tool of a mixed-model assembly line system.     

Simultaneous balancing and sequencing of mixed-model parallel two-sided assembly lines

Growing interests from customers in customised products and increasing competitions among peers necessitate companies to configure their manufacturing systems more effectively than ever before. We propose a new assembly line system configuration for companies that need intelligent solutions to satisfy customised demands on time with existing resources. A mixed-model parallel two-sided assembly line system is introduced based on the parallel two-sided assembly line system previously proposed in the literature. The mixed-model parallel two-sided assembly line balancing problem is illustrated with examples from the perspective of simultaneous balancing and sequencing. An agent-based ant colony optimisation algorithm is proposed to solve the problem. This algorithm is the first attempt in the literature to solve an assembly line balancing problem with an agent-based ant colony optimisation approach. The algorithm is illustrated with an example and its operational procedures and principles are explained and discussed.     

A genetic algorithm for the stochastic mixed-model U-line balancing and sequencing problem

Mixed-model assembly lines are widely used to improve the flexibility to adapt to the changes in market demand, and U-lines have become popular in recent years as an important component of just-in-time production systems. As a consequence of adaptation of just-in-time production principles into the manufacturing environment, mixed-model production is performed on U-lines. This type of a production line is called a mixed-model U-line. In mixed-model U-lines, there are two interrelated problems called line balancing and model sequencing. In real life applications, especially in manual assembly lines, the tasks may have varying execution times defined as a probability distribution. In this paper, the mixed-model U-line balancing and sequencing problem with stochastic task times is considered. For this purpose, a genetic algorithm is developed to solve the problem. To assess the effectiveness of the proposed algorithm, a computational study is conducted for both deterministic and stochastic versions of the problem.     

Measuring complexity in mixed-model assembly workstations

In an effort to maintain or increase their market share and at the same time prevent costs from escalating, manufacturing organisations are increasingly using their current manufacturing system to produce custom output. As a consequence, the large number of product variants increases significantly the complexity of manufacturing systems, both for the operators as for the support services. This is especially true in automotive industry, where customisation is increasing at a rapid pace. To counter the ensuing loss of productivity, a more fundamental approach to dealing with this complexity in manufacturing processes is required. In order to investigate the impact of complexity on production performance, one must first delineate the concept and then identify as unambiguously as possible highly complex workstations. This article defines complexity at the workstation level and proposes a complexity measure for mixed-model assembly workstations. Based on data from several leading automotive companies from Belgium and Sweden, some statistical models are proposed to characterise workstations complexity. The models are described and their validity and accuracy are discussed.     

Design configuration for a closed-station,mixed-model assembly line: A filing cabinet manufacturing system

A closed-station assembly line with mixed models encountered in a filing cabinet manufacturing company is considered. Utility and idle times play an important role on the performance and economy of a closed-station system. This paper addresses a problem that minimizes the total cost of the utility and idle times caused due to different line parameters (launch interval, station length, starting point of work, upstream walk, locus of the operator's movement, etc.) and operation sequences of the mixed models. A mixed-integer-programming model for a closed-station system is developed to determine line parameters optimally. The model is tested on a three-station, mixed-model assembly line in a filing cabinet manufacturing system. The research shows that a set of line parameters is available for which the total cost of utility and idle times is minimal. Results also indicate that the minimum total cost of utility and idle times in a closed-station system decreases with line length. A sensitivity analysis is performed to study the effects of line and launch intervals in such a manufacturing line.     

Workload balancing and manufacturing complexity levelling in mixed-model assembly lines

To effectively react and meet the current ever growing demand for individualised motor vehicles, built to customer specific requirements, automotive industry has accelerated its transition towards mass-customisation. As a result, the number of new model introductions has drastically increased over the past three decades. To cope with this intensified customisation, the current automotive assembly platforms are designed to assemble a wide range of relatively different models, and are turned into mixed-model assembly lines (MMALs). This implies that the set of tasks to be performed on each workstation is no longer stable but varies highly with the model-mix. As a consequence, the manufacturing complexity increases at the workstations and throughout the whole assembly system. This paper proposes a method to monitor manufacturing complexity at each workstation while the MMAL is being balanced. An entropy-based quantitative measure of complexity, which incorporates the variability of each task duration, is developed. This measure is used to monitor the manufacturing complexity level at each workstation. An integrated mixed-line balancing and complexity monitoring heuristic is proposed, to determine workload balance solutions, in which manufacturing complexity is levelled throughout the workstations composing the line. This procedure is tested on a real data-set provided by an automotive manufacturer. The results are reported and thoroughly discussed.     

Application of Axiomatic Design principles to control complexity dynamics in a mixed-model assembly system: a case analysis

The purpose of this paper is to test the validity of Axiomatic Design (AD)-based complexity theory as an explanatory construct and as a methodological guidance for the early detection of need for change in flexible manufacturing systems in order to maintain competitiveness even in turbulent environmental conditions. The AD approach postulates that there are general design principles that govern the behaviour of a system. This proposition is empirically investigated for a flexible mixed-model assembly system by the examination of a long-term study conducted in a medium-sized industrial company. The findings of the long-term study suggest the introduction of a company specific cycle of functional periodicity in combination with a set of functional requirements working together as a regular trigger to detect whether the system range is moving away from the once defined manufacturing system's design range. The paper extends the research work made in the field of AD by focusing on mechanisms that help to control the effects of time-dependent complexity in manufacturing (re)design. Examples of methods and lead measures are given that can be used by organisations in early detecting and controlling complexity driven efficiency losses in manufacturing systems.     

Mixed-model assembly line sequencing using beam search

In today's manufacturing environments, companies have to produce a large variety of products in small quantities on a single assembly line. In this paper, we use a beam search (BS) approach to solve the model-sequencing problem of mixed-model assembly lines (MMALs). Specifically, we develop six BS algorithms for part-usage variation and load-leveling performance measures. The results of computational experiments indicate that the proposed BS methods are competitive with the well-known heuristics in the literature. A comprehensive bibliography is also provided.     

Kitting optimisation in Just-in-Time mixed-model assembly lines: assigning parts to pickers in a hybrid robot–operator kitting system

With increasing components’ variety in mixed-model assembly lines, industrials show interest in kitting operations using robots. This paper deals with a hybrid kitting system that consists of a robot and an operator working in series to deliver parts to a Just-In-Time mixed-model assembly line. We develop a mathematical model that optimally assigns stock keeping units to either the robot or the operator so that the cycle time of the overall system is optimised. To test the model, a case study from the automotive sector is presented and a sensitivity analysis is carried out on relevant system parameters.     

A modified colonial competitive algorithm for the mixed-model U-line balancing and sequencing problem

Implementation of mixed-model U-shaped assembly lines (MMUL) is emerging and thriving in modern manufacturing systems owing to adaptation to changes in market demand and application of just-in-time production principles. In this study, the line balancing and model sequencing (MS) problems in MMUL are considered simultaneously, which results in the NP-hard mixed-model U-line balancing and sequencing (MMUL/BS) problem. A colonial competitive algorithm (CCA) is developed and modified to solve the MMUL/BS problem. The modified CCA (MCCA) improves performance of original CCA by introducing a third type of country, independent country, to the population of countries maintained by CCA. Implementation details of the proposed CCA and MCCA are elaborated using an illustrative example. Performance of the proposed algorithms is tested on a set of test-bed problems and compared with that of existing algorithms such as co-evolutionary algorithm, endosymbiotic evolutionary algorithm, simulated annealing, and genetic algorithm. Computational results and comparisons show that the proposed algorithms can improve the results obtained by existing algorithms developed for MMUL/BS.     

Balancing and sequencing of stochastic mixed-model assembly U-lines to minimise the expectation of work overload time

A mixed-model assembly U-line is a flexible production system capable of manufacturing a variety of similar models, and it has become popular as an important component of the just-in-time production system. However, it poses new challenges for the optimal design of assembly lines because both the task assignment and the production sequence affect the workload variance among workstations. As a consequence, this paper addresses the line balancing problem and the model sequencing problem jointly and proposes a 0–1 stochastic programming model. In this model, task times are assumed to be stochastic variables independently distributed with normal distributions and the objective is to minimise the expectation of work overload time for a given combination of cycle time and number of workstations. To solve the problem, a simulated annealing-based algorithm is developed, which can also be used to minimise the absolute deviation of workloads in a deterministic environment. The experimental results for a set of benchmark problems show that the proposed algorithm outperforms the existing algorithms in terms of solution quality and running time.     

Balancing of mixed-model parallel U-shaped assembly lines considering model sequences

As a consequence of increasing interests in customised products, mixed-model lines have become the most significant components of today’s manufacturing systems to meet surging consumer demand. Also, U-shaped assembly lines have been shown as the intelligent way of producing homogeneous products in large quantities by reducing the workforce need thanks to the crossover workstations. As an innovative idea, we address the mixed-model parallel U-shaped assembly line design which combines the flexibility of mixed-model lines with the efficiency of U-shaped lines and parallel lines. The multi-line stations utilised in between two adjacent lines provide extra efficiency with the opportunity of assigning tasks into workstations in different combinations. The new line configuration is defined and characterised in details and its advantages are explained. A heuristic solution approach is proposed for solving the problem. The proposed approach considers the model sequences on the lines and seeks efficient balancing solutions for their different combinations. An explanatory example is also provided to show the sophisticated structure of the studied problem and explain the running mechanism of the proposed approach. The results of the experimental tests and their statistical analysis indicated that the proposed line design requires fewer number of workstations in comparison with independently balanced mixed-model U-lines.     

Systemic criterion of sustainability in agile manufacturing

Agile manufacturing systems work in a constantly changing global market, particularly assembly systems at the last stage of product differentiation. Meanwhile, sustainability is becoming a key issue for manufacturing strategy. This paper formulates a systemic criterion of sustainability in agile manufacturing and computes it through flexibility and complexity. It is defined as a ratio of utility and entropy as a sustainability measurement. Under a unified framework, utility allows one to quantify the contributions to agility, in particular system flexibility. Complexity is measured by entropy. Thus, an original complementary role of flexibility and the complexity of the system are proposed. Developed from the distribution of system states, the systemic approach to sustainability in terms of output evolution is enriched. Based on a simple assembly line integer model simulation, a first quantitative analysis illustrates the concepts introduced.     

Balancing mixed-model assembly lines: a computational evaluation of objectives to smoothen workload

Mixed-model assembly lines are widely used in a range of production settings, such as the final assembly of the automotive and electronics industries, where they are applied to mass-produce standardised commodities. One of the greatest challenges when installing and reconfiguring these lines is the vast product variety modern mixed-model assembly lines have to cope with. Traditionally, product variety is bypassed during mid-term assembly line balancing by applying a joint precedence graph, which represents an (artificial) average model and serves as the input data for a single model assembly line balancing procedure. However, this procedure might lead to considerable variations in the station times, so that serious sequencing problems emerge and work overload threatens. To avoid these difficulties, different extensions of assembly line balancing for workload smoothing, i.e. horizontal balancing, have been introduced in the literature. This paper presents a multitude of known and yet unknown objectives for workload smoothing and systematically tests these measures in a comprehensive computational study. The results suggest that workload smoothing is an essential task in mixed-model assembly lines and that some (of the newly introduced) objectives are superior to others.     

Research issues on factors influencing the choice of kitting versus line stocking

Kitting and line stocking systems are common alternatives for component storage in assembly environments. Despite the need for knowledge about when and where each system would be applicable in industry, research on the choice of kitting versus line stocking systems in industry is quite sparse. This paper identifies a number of research issues that might influence this system choice decision based on an analysis of the kitting operations and the potential move to line stocking at an electronics assembly company. Research questions are presented in the areas of product characteristics (volume, variety, and size), storage and material handling, production control, performance impact, and implementation. The issues identified here highlight factors that might influence the choice between kitting and line stocking, and present a rich array of research opportunities in a number of relevant areas.     

变速箱多品种混流装配线信息管理系统设计

基于现代汽车制造企业信息化、网络化和柔性化的要求,设计并开发了一个变速箱多品种混流装配线信息管理系统,该系统以信息技术、计算机应用技术和质量管理方法为手段,对变速箱装配线上的信息进行采集、监控、分发与管理,并保存产品质量信息,提高了汽车零部件企业生产现场的信息化水平,具有良好的应用前景.     

Analysis and improvement of multi-product assembly systems: an application study at a furniture manufacturing plant

In this paper, we introduce an application study of modelling, analysis and continuous improvement of an assembly system at a furniture manufacturing plant using production systems engineering methods. Analytical models have been developed to characterise the assembly system making multiple products, and recursive procedures have been derived to evaluate line production rate. Lot size analysis is carried out, and bottleneck analysis methods are introduced to identify the bottlenecks, whose improvement can lead to the largest improvement in system performance. Such methods provide a quantitative tool for plant engineers and managers to operate and improve assembly line with high productivity, and are also applicable to other large-volume manufacturing systems.     

Investigations into the impact of flexibility on manufacturing performance

This paper provides investigative insights into the impact of routeing flexibility, machine flexibility, and product-mix flexibility on the performance of a manufacturing plant. The study employs simulation modelling as the primary tool. The facility modelled is an automobile engine assembly plant consisting of a FMS (flexible manufacturing systems), job shop, and assembly line. A variety of experiments, with the FMS exhibiting one or more of the above three flexibilities at different levels, were simulated on the model. In each experiment the manufacturing performance as given by flow time and work-in-process inventory was tracked. The experiments focused first on the FMS itself, and then on the entire plant. Measures for the three flexibilities are introduced. The simulation results are analysed in detail. The results indicate significant performance benefits in context of the FMS, but little in context of the overall plant