Throughput Rate Improvement in a Multiproduct Assembly Line Using Lean and Simulation Modeling and Analysis

Nagi, Mahmoud; Chen, F. Frank; Wan, Hung Da

doi:10.1016/j.promfg.2017.07.153

Cited by 14 publications

(8 citation statements)

References 6 publications

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“…At present, line balancing techniques have received much attention than other line efficiency and process improvement techniques 23 such as lean manufacturing (VSM), [32][33][34][35] Lean-six sigma, 36,37 Six sigma, 38 and hybrid approach (lean manufacturing and line balancing). 39 Line balancing techniques involve several constraints that have to be put into consideration for example task assignment, task precedence, cycle time, and resource constraints. 40 This makes line balancing an NP-hard or complex combinatorial problem.…”

Section: Literature Reviewmentioning

confidence: 99%

Improvement of garment assembly line efficiency using line balancing technique

Bongomin

Mwasiagi

Nganyi

et al. 2020

Engineering Reports

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The current competitiveness of garment manufacturing industries is highly dependent on ability to improve efficiency and effectiveness of resource utilization through proper application of industrial engineering techniques such as line balancing and time study. However, very few apparel industries have comprehended industrial engineering function due to little knowledge on practical application of industrial engineering techniques. The present study aimed at balancing a trouser assembly line using the ranked positional weight technique to increase the line efficiency as well as minimize the number of workstations without violating the constraints: precedence relations, cycle time, and resource type. The empirical study was conducted at Southern Range Nyanza Limited (NYTIL) garment manufacturing facility to demonstrate the practical application of ranked positional weight line balancing technique. Results showed that ranked positional weight method is suitable only for assembly line balancing with no constraint on the resource. However, most complex garment assembly lines consist of a number of different machine types rendering ranked positional weight method practically ineffective for improving line efficiency of a complex garment assembly line. Therefore, profound line balancing using simulation-based optimization to improve the line efficiency of complex garment assembly line should be investigated. K E Y W O R D S assembly line, heuristic line balancing, line efficiency, performance indicators, ranked positional weight, resource constraints

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Section: Literature Reviewmentioning

confidence: 99%

Improvement of garment assembly line efficiency using line balancing technique

Bongomin

Mwasiagi

Nganyi

et al. 2020

Engineering Reports

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“…Looking at balancing manual assembly lines with a high number of product variants (mixed-model assembly), kaizen events and complexity reduction have proven useful since they fill the gap between mathematical balancing models developed by academia and actual techniques used in industry [125]. Mixed-model assembly lines throughput rate can be increased by using Lean in conjunction with simulation [126]. To increase productivity and reduce the necessary shop floor space, continuous flow can be achieved through the use of Standardized Work (SW), U-shape assembly lines and material handling systems [127].…”

Section: Lean Production Tools For Assembly Operationsmentioning

confidence: 99%

Lean Manual Assembly 4.0: A Systematic Review

2020

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In a demand context of mass customization, shifting towards the mass personalization of products, assembly operations face the trade-off between highly productive automated systems and flexible manual operators. Novel digital technologies—conceptualized as Industry 4.0—suggest the possibility of simultaneously achieving superior productivity and flexibility. This article aims to address how Industry 4.0 technologies could improve the productivity, flexibility and quality of assembly operations. A systematic literature review was carried out, including 234 peer-reviewed articles from 2010–2020. As a result, the analysis was structured addressing four sets of research questions regarding (1) assembly for mass customization; (2) Industry 4.0 and performance evaluation; (3) Lean production as a starting point for smart factories, and (4) the implications of Industry 4.0 for people in assembly operations. It was found that mass customization brings great complexity that needs to be addressed at different levels from a holistic point of view; that Industry 4.0 offers powerful tools to achieve superior productivity and flexibility in assembly; that Lean is a great starting point for implementing such changes; and that people need to be considered central to Assembly 4.0. Developing methodologies for implementing Industry 4.0 to achieve specific business goals remains an open research topic.

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“…Although production is arranged into model-specific lots, this approach reduces inventories, adds flexibility and focuses on process flow. The estimated monthly demand (Table 2) is divided by the number of working days in the month (22) so that production of each model is repeated once a day in the amounts shown in Table 2. Single tasks or work elements to assemble each model are identified by a number in Table 3.…”

Section: Problem Statementmentioning

confidence: 99%

“…Practitioners seem to be reluctant to methods that require computational complexity [9] and thus many companies use only trial and error methods [13,20] such as playing with the sequence using an electronic spreadsheet until the result is satisfactory [21]. Namely, LM relies on visual aids such as stacked bar charts called yamazumi charts [22]. In this paper, we present a method that was conceived as a simple tool for a real company and thus it can be implemented on an electronic spreadsheet for the sake of simplicity.…”

Section: Introductionmentioning

confidence: 99%

Balancing Workload and Workforce Capacity in Lean Management: Application to Multi-Model Assembly Lines

et al. 2020

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While multi-model assembly lines are used by advanced lean companies because of their flexibility (different models of a product are produced in small lots and reach the customers in a short lead time), most of the extant literature on how to staff assembly lines focuses either on single-model lines or on mixed-model lines. The literature on multi-model lines is scarce and results given by current methods may be of limited applicability. In consequence, we develop a procedure to staff multi-model assembly lines while taking into account the principles of lean manufacturing. As a first approach, we replace the concepts of operation time and desired cycle time by their reciprocal magnitudes workload and capacity, and we define the dimensionless term of unit workload (load/capacity ratio) in order to avoid magnitudes related to time such as cycle time because, in practice, they might not be known. Next, we develop the necessary equations to apply this framework to a multi-model line. Finally, a piece of software in Python is developed, taking advantage of Google’s OR-Tools solver, to achieve an optimal multi-model line with a constant workforce and with each workstation performing the same tasks across all models. Several instances are tested to ensure the performance of this method.

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Throughput Rate Improvement in a Multiproduct Assembly Line Using Lean and Simulation Modeling and Analysis

Cited by 14 publications

References 6 publications

Improvement of garment assembly line efficiency using line balancing technique

Improvement of garment assembly line efficiency using line balancing technique

Lean Manual Assembly 4.0: A Systematic Review

Balancing Workload and Workforce Capacity in Lean Management: Application to Multi-Model Assembly Lines

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