Assembly line balancing

The disruption caused due to the current pandemic situation in the areas of supply chains, tourism, aviation, hospitality, sports and fashion is enormous. This effect is more visible in manufacturing sector especially in fashion, appeal and garment industry. This resulted in the companies emphasizing on the effective utilization of resources and enhanced productivity. Although, the concept of lean manufacturing, value stream mapping (VSM), Jidoka, Kaizen, 5S, Kanban, Poka Yoke, line balancing and many more are available in the literature, that can enhance productivity, the incorporation of data analytics and software-based simulations as a method to support decision making in real time production activity to enhance productivity is the need of the hour. The aim of the research paper is to develop a framework of model driven decision support system (MD-DSS) where real time data is fed to the system and data simulation and communication technologies help in improving the productivity of the manufacturing process. An empirical study was conducted at AL Apparel Manufacturing PLC, Addis Ababa (Ethiopia) garment manufacturing facility to demonstrate the proposed model. Data is collected through observations, document studies, and time study measurements for skimmer trouser having 34 operations. The assembly line is balanced using discrete event Arena simulation program. The results indicated that the proposed model has high line efficiency and increased productivity.

A new heuristic algorithm and new reduction techniques for the type 1 assembly line balancing problem are presented. The new heuristic is based on the well-known Hoffmann heuristic and builds solutions from both sides of the precedence network to choose the best. The reduction techniques aim at augmenting precedences, conjoining tasks and increasing operation times. The heuristic is tested on its own and also in combination with the reduction techniques. The tests, which are carried out on a well-known benchmark set of problem ...

The consideration of this paper is given to address the straight and U-shaped assembly line balancing problem. Although many attempts in the literature have been made to develop deterministic version of the assembly line model, the attention is not considerably given to those in uncertain environment. In this paper, a novel bi-objective fuzzy mixed-integer linear programming model (BOFMILP) is developed so that triangular fuzzy numbers (TFNs) are employed in order to represent uncertainty and vagueness associated with the task processing times in the real production systems. In this proposed model, two conflicting objectives (minimizing the number of stations as well as cycle time) are considered simultaneously with respect to set of constraints. For this purpose, an appropriate strategy in which new two-phase interactive fuzzy programming approach is proposed as a solution method to find an efficient compromise solution. Finally, validity of the proposed model as well as its solution approach are evaluated though numerical examples. In addition, a comparison study is conducted over some test problems in order to assess the performance of the proposed solution approach. The results demonstrate that our proposed interactive fuzzy approach not only can be applied in ALBPs but also is capable to handle any practical MOLP models. Moreover, in light of these results, the proposed model may constitute a framework aiming to assist the decision maker (DM) to deal with uncertainty in assembly line problem.

Download: https://doi.org/10.2307/j.ctv5cg94w
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First chapter download: https://agendapub.com/images/pdfs/chapters/9781911116721_chp.pdf

"...Process cycle time reduction to increase Productivity, Quality and Efficiency of G-435cc diesel engine assembly line at Greaves cotton Ltd...'

The project was successful as the required target was achieved.
Some of the achievements are listed below:-
1]2nd shift was successfully eliminated.
2]Productivity improved by 16%.
3]Monthly saving of Rs.46, 500 (as second shift is eliminated).
4]Cycle time reduced by 13 sec.

In today's economic context the workforce is a crucial asset in manufacturing industries. The employee performance and productivity are affected by many factors related on one hand to the line efficiency and, on the other hand, to the well-being of the workers. On the basis of new technologies and driven by Industry 4.0 paradigms, the need of a high production rate cannot neglect the safeguarding of the workers. In case of repetitive manual tasks, workers are exposed to the risk of musculoskeletal disorders (MSDs), that can be reduced by applying ergonomics principles both in design (e.g. workstation design, equipment tools identification, etc.) and in operative phases (e.g. workload balance, tasks assignment, etc.). In the operative phase, job rotation is one of the most widespread methods for alleviating physical fatigue and reducing the stress due to repetitive tasks. However, often, job rotation strategies fail due to the lack of systematic approach or effective management of rotation schedules, being very difficult to identify an effective job rotation schedule allowing maintaining the same productivity rate. The problem is of particular interest under the perspective of the workforce aging, a social European phenomenon which is also affecting production systems performance. Designing and scheduling of human-based assembly systems require a joint evaluation of production system performance and a good balancing of MSDs risk among workers. The authors proposed a model for minimizing the exposure risk of workers involved in repetitive manual tasks, by balancing the human workloads and reducing the ergonomic risk within acceptable limits, for a given production target. Risk and its acceptability are evaluated using the RULA method, according to a mixed integer programming approach. Results shown the effectiveness of the model to identify the optimal job rotation schedules jointly achieving productivity and ergonomic risk goals.

This technical paper provides a brief review of the literature on assembly line balancing, more specifically, as it relates to the apparel industry. The fashion industry, including the production, shipping, sales and marketing of clothing, is one of the largest on the planet. It is also extremely labour intensive. With regard to the fabrication of garments, ideally, if each item is processed in an assembly line in a predetermined order, with no two operators working on the same piece at the same time, no problems due to imbalance should occur. But this is rarely the case. It is believed that there is a great deal of lost productivity and decreased efficiency as a result of assembly lines being unbalanced (i.e. a misallocation or suboptimal use of resources exists).

The Assembly Line Balancing Problem (ALBP) engages the interest of many researchers. However, the number of researchers that treat this problem is still small in the field of apparel manufacturing. The fact that an apparel assembly line is labour intensive and insufficiently automated further complicates the problem. Operator Skill Level (OSL) as a category that has a significant effect on ALBP in the industry also has not been analysed enough. This study presents a model for evaluation and comparison of the OSL and based on that, designs algorithm for optimal scheduling of the operators on the production line in response to customer demand. The application of this model is demonstrated through conducting a case study in an apparel company. It is determined that the proposed model can lead to significant improvement of the performance of the production line by better operator allocation based on skill levels. The model can ensure improvements related to increasing the line efficiency for 28%, daily output for 27.3% and decrease labour force for 18.5% and production time for 20%.

The pulse of any manufacturing industry is to clutch more profits with optimized low possible inputs. The main difficulties facing by the industries nowadays are disturbances in the assembly line due to lack of material within reach, possibilities of 3M in the process, lack of established standard time for activities carried by the operators, imbalanced product flow. Lean manufacturing system (LMS) is characterized by reduced product development and manufacturing lead-time, team-based work organizations, low setup/changeover times, multifunctional workers and JIT deliveries from a few reliable suppliers. This project aims to improve the production capacity by balancing the assembly line and continuously improving assembly line for better working area. These challenges are perennial that encapsulates the journey of questioning, "How can we do better than yesterday to help both the organization and people?". Lean techniques like Heijunka, 5S, KAIZEN, TAKT Time analysis, De-bottlenecking, JIT, are integrated with the existing assembly process to eliminate waste in each step of the workflow, which will lead to improving productivity, production capacity and prevention of failures. M.O.S.T (Maynard Operation and Sequence Technique) analysis conducted identify non-value-added activities to improve productivity, line balancing and reduce the cycle time.

The need for high product variety, smaller batch size, shorter delivery time and higher quality has encouraged apparel companies to concentrate on the development of digitization and information management. This speeds the response to those rapid changes occurring in the apparel industry. However, on the shop floor, it is difficult to achieve line balancing due to the different pitch time of each workstation. Simultaneously, differences in operators’ efficiency make this difficulty far greater. This paper will develop a simulation technique that can be applied to production lines, balancing the data derived and offering clear measurements of operators’ efficiencies. The data collected by the researcher from a dress assembly line in factory in China is used to build a simulation using ProModel software. An optimization solution is suggested that may be one route to improving production line performance. Results derived from the simulation hypothesise that by considering the operators’ efficiencies the production line could be changed generating higher productivity and lower work in process (WIP). Thus, simulation may also be effective in helping achieve better line balancing, even predicting problems before production starts.

In this modern world, fashion & styles are changing frequently. The emergence of fast changes in fashion has given rise to shorten production cycle time in the garment industry. To meet the dynamic customer demands of momentous quantities in shorten lead time, assembly line production systems are used, where the garment components are assembled into a finished garment through a sub-assembly process. So in the era of product customization, the optimal usage of resources especially the available facilities & operators who are adding the value of product is important. Therefore the assembly line has to be planned in much more flexible way. This paper deals with the maximum utilization of manpower in labor intensive assembly lines. The objective is to accurately delegate workers to the various operations required to complete the product based on their skill & experience so as to achieve the highest level of productivity and delivery as per planned target. The experimental result showed meaningful improvement in productivity as compared to the existing system.

Worker performance must be considered in line balancing, because as a worker becomes more experienced in performing a specific task, in other words his/her cumulative production quantity increases, his/her task time per one piece of product decreases in a non-linear sense. Therefore, task times are not independent from workers’ performance. Another fact is, that every worker cannot perform every task at the same processing time. In addition, every worker cannot be able to perform every task in production systems. These facts can significantly cause actual task times differ from the presumed standard times.

This paper presents a version of the U-shaped Assembly Line Balancing Problem and an asso-ciated heuristic solver where parallel stations are used to accommodate tasks with processing time greater than the cycle time. Computational results for the heuristic applied to problems created from industry standard test sets show that the heuristic performs well when compared to optimum solution bounds.

The current industry demands high productivity removing every constraint inherited during manufacturing a product with limited resources. Re-configurability and Flexibility to produce multiple components depending on customer demand is a key factor. This projects aims at optimizing the productivity of a discrete heavy duty manufacturing company which adopts a Fixed-Worker-Assembly-Line (FWAL) to manufacture multiple products. The dynamic nature of heavy duty manufacturing assembly line is improved by converting FWAL into a Walking-Worker-Assembly-Line (WWAL). The productivity of proposed WWAL is calculated using ProModel simulation software and compared with FWAL to ensure optimization. Better utilization of resources and reduction of WIP is carried out in WWAL in order to generate an optimized and dynamic manufacturing unit and establish a common set of rules in converting a FWAL into WWAL.

A new hybrid assembly line design, called Parallel U-shaped Assembly Line system, is introduced and characterised along with numerical examples for the first time. Different from existing studies on U-shaped lines, we combine the advantages of two individual line configurations (namely parallel lines and U-shaped lines) and create an opportunity for assigning tasks to multi-line workstations located in between two adjacent U-shaped lines with the aim of maximising resource utilisation. Utilisation of crossover workstations, in which tasks from opposite areas of a same U-shaped line can be performed, is also one of the main advantages of the U-shaped lines. As in traditional U-shaped line configurations, the newly proposed line configuration also supports the utilisation of crossover workstations. An efficient heuristic algorithm is developed to find well-balanced solutions for the proposed line configurations. Test cases derived from existing studies and modified in accordance with the proposed system in this study are solved using the proposed heuristic algorithm. The comparison of results obtained when the lines are balanced independently and when the lines are balanced together (in parallel to each other) clearly indicates that the parallelisation of U-shaped lines helps decrease the need for workforce significantly.

The mixed model assembly line is becoming more important than the traditional single model due to the
increased demand for higher productivity. In this paper, a set of procedures for mixed-model assembly line
balancing problems (MALBP) is proposed to make it efficiently balance. The proposed procedure based on
the meta heuristics genetic algorithm can perform improved and efficient allocation of tasks to workstations
for a pre-specified production rate and address some particular features, which are very common in a real
world mixed model assembly lines (e.g. use of parallel workstations, zoning constraints, resource limitation).
The main focus of this study is to study and modify the existing genetic algorithm framework. Here a heuristic
is proposed to reassign the tasks after crossover that violates the constraints. The new method minimises the
total number of workstation with higher efficiency and is suitable for both small and large scale problems.
The method is then applied to solve a case of a plastic bag manufacturing company where the minimum
number of workstations is found performing more efficiently.

The 21st century has witnessed a number of incredible changes ranging from the way of life and the technologies that emerged. Currently, we have entered a new paradigm shift called industry 4.0 where science fictions have become science facts, and technology fusion is the main driver. Therefore, ensuring that any advancement in technology reach and benefit all is the ideal opportunity for everyone. In this paper, disruptive technologies of industry 4.0 have been explored and quantified in terms of the number of their appearances in literature. This research mainly aimed at identifying industry 4.0 key technologies which have been ill-defined by previous researchers and to enlighten the required skills of industry 4.0. Comprehensive literature survey covering the field of engineering, production, and management from both academia and business was done from publication databases: Google scholar, ScienceDirect, Scopus, Sage, Taylor & Francis and Emerald insight. The results of the stud...

Assembly lines are usually constructed as the last stage of the entire production system and efficiency of an assembly line is one of the most important factors which affect the performance of a complex production system. The main purpose of this paper is to mathematically formulate and to provide an insight for modelling the parallel two-sided assembly line balancing problem, where two or more two-sided assembly lines are constructed in parallel to each other. We also propose a new genetic algorithm (GA)-based approach in alternatively to the existing only solution approach in the literature, which is a tabu search algorithm. To the best of our knowledge, this is the first formal presentation of the problem as well as the proposed algorithm is the first attempt to solve the problem with a GA-based approach in the literature. The proposed approach is illustrated with an example to explain the procedures of the algorithm. Test problems are solved and promising results are obtained. Statistical tests are designed to analyse the advantage of line parallelisation in two-sided assembly lines through obtained test results. The response of the overall system to the changes in the cycle times of the parallel lines is also analysed through test problems for the first time in the literature.

The basic type of Assembly Line Balancing (ALB) problem is the allocation of work elements to a set of production work stations considering cycle time, precedence constraints, and assembly diagram to achieve predefined performance criteria such as line efficiency and smoothness index. In this paper, a mixed integer programming model for solving multiple product ALB problems with processing times larger than cycle time as well as technological constraints is presented. The performance of presented model in finding optimal solution is compared with models presented in the literature by solving sample problems. The obtained results were quite satisfactory. Also, the relative advantages of the proposed model in comparison with some approaches in the literature are verified and shown using Kruskal-Wallis non-parametric testing approach. This was accomplished by calculating the measures of performance such as line smoothness, line efficiency and deviations of solved sample problems.

Line-Balancing is distribution of total work load among various stations evenly as to achieve the production target. The problem is to minimize the difference between maximum station time and individual station time subject to element time constraint, precedence relationship constraint. The assembly line as planned and installed based on the production rate required; any change in demand value, product design requires change in assembly line. The case study involves Kilbridge and Wester (KBW) method and Ranked Position Weighted (RPW) method line balancing Heuristic Algorithm to balance the manual assembly line. Result is selected as best of two method and proposed arrangement for distribution of workload among various stations is made for the radiator assembling plant considering line-efficiency(E) and smoothness index(SI) as performance criterion.

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.

Assembly lines are one of the essential parts of manufacturing systems that influence the costs and efficiency. In real world applications, the performance of human resource directly affects the efficiency of assembly lines. Heavy physical workloads along with monotonous body postures during repetitive jobs negatively affect the performance of assembly line workers and cause of Work-related Musculoskeletal Disorders (WMSDs). These problems totally decrease the life quality of the workers. Furthermore, WMSDs result in high compensation costs for companies. In order to increase the efficiency of assembly lines, the companies should not only consider cycle time and precedence constraints, but also it's necessary to consider the physical workloads of the stations. This paper addresses Assembly Line Balancing Problem (ALBP) Type 2 where the number of workstation lines is known. The main objective is not only balancing the cycle time but also balancing the physical workload of the stations simultaneously. Rapid Entire Body Assessment (REBA) method from the literature is proposed to determine workload of operations in the assembly line. A goal programming model is developed for the problem. A well known small sized benchmark problem instance is solved by using CPLEX solver in order to validate the model.