Bottleneck Workstation Research Articles

Optimization of Production Process by Applying Theory of Constraint (TOC) at CV. Wijaya Mandiri Label

CV. Wijaya Mandiri Label is a company engaged in the printing industry sector located in Sidoarjo which provides printing services inside and outside Sidoarjo. In the production process, problems arise after several years of operation at work stations that cause bottlenecks in the production capacity of bontax and OPP sticker printing, thus hindering the production process to run optimally. This resulted in an inefficient sticker production process in meeting targets that made throughput not optimal. To overcome these problems, researchers conducted research that explored the use of Theory of Constraints (TOC) and supporting methods, namely linear programming, to optimize the company's production process and analyze data on working hours and product production demand. From the results of the research, it was concluded that the company experienced Capacity Constraints which caused bottlenecks at the fourth work station in the last six months. After exploiting the constraints on the bottleneck workstation, throughput is obtained using a linear programming calculation formulation with the results of x1= 0 and x2 = 3,948.47 amounting to IDR16,781,000 in WinQSB software. The final stage of constraint elevation is carried out by allocating operators to bottleneck work stations and obtaining an increase in throughput of IDR6,322,300 or a percentage increase of 27.4% using WinQSB software.

Manufacturing cost reduction techniques for automobile crankcase mould inserts

The manufacturing of automobile moulds is itself a challenging job and very tedious task requiring high accuracy of component profiles. The required complicated and complex profiles are generated when the mould inserts are relinquished from several numbers of workstations, which run for a longer process time. As the accuracy needed for the component area is very high and it (insert) has to pass through several bottleneck workstations, the production time and increased buffer time are observed. This chapter focuses on providing economical methods for manufacturing hot die steel inserts. These techniques are implemented on a pressure die-casting insert component. The present solution is derived for manufacturing time reduction and minimisation of the die-casting inserts (moving and fixed die) at every stage. Implementing combined electrodes, assembly machining and cluster plate machining/sparking techniques are critical development advancements in the research. In the combined electrode concept, one electrode is designed in the same area to cover multiple areas that were initially covered by separate individual electrodes. Furthermore, this concept is outstretched by the cluster plate concept. Those electrodes that cannot be covered by a single electrode are machined together to act as a single electrode and later separated while individual sparking. Combined electrode design, assembly machining and cluster machining/sparking of the electrodes reduce the total machining time of the die and the machining centre. Reducing the machine run time will reduce the production cost and increase profit. The results achieved show that the combined electrode design setup shows 75% savings in the combined sparking setup, whereas the cluster plate machining setup shows 35% savings in the tool list generation (from software used) of the net savings. The proposed solution opens up new avenues for similar automobile components by setting benchmarks to decrease the rope length associated with manufacturing and increase profit.

Minimization of Non-Value-Added Activities in an Aerospace Industry

Abstract-- The industry was having lesser productivity than the required due to the presence of certain ‘non-value added’ activities. Hence, the requirement was to improve productivity by means of cost reduction and rationalisation of manpower. Since the main purpose was to eliminate any process that does not add value to the final output. To reduce the waste, the lean manufacturing is the best choice among the available techniques. The Value Stream Mapping (VSM) is one of the major components in lean manufacturing techniques. This helps in identifying the major opportunities for performance improvement in the assembly line of the aerospace industry. The Value Stream Mapping was developed in the required assembly lines of the aerospace industry. The Value Stream Mapping consists of Time-Study, 5s implementation and skill based line balancing at the required workstations. Time-Study was conducted at the bottleneck workstations. The results were analysed by categorising them as value added (VA) and non-value added (NVA) components. This has benefited in identifying waste in the assembly line. The activities which were not adding value to the final product were eliminated and compared with previous results. Based on the analysis, the required man-power was added to improve the productivity. Keywords— Value Stream Mapping, Lean manufacturing, Time-Study, 5s, Productivity

Reduction of Non-Value-Added Activities in An Aerospace Industry Using Value Stream Mapping and Time Study

Abstract: The industry was having lesser productivity than the required due to the presence of certain ‘non-value added’ activities. Hence, the requirement was to improve productivity by means of cost reduction and rationalisation of manpower. Since the main purpose was to eliminate any process that does not add value to the final output. To reduce the waste, the lean manufacturing is the best choice among the available techniques. The Value Stream Mapping (VSM) is one of the major components in lean manufacturing techniques. This helps in identifying the major opportunities for performance improvement in the assembly line of the aerospace industry. The Value Stream Mapping was developed in the required assembly lines of the aerospace industry. The Value Stream Mapping was used for other techniques like Time-Study, 5s implementation and skill based line balancing at the required workstations. Time-Study was conducted at the bottleneck workstations. The results were analysed by categorising them as value added (VA) and non-value added (NVA) components. This has benefited in identifying waste in the assembly line. The activities which were not adding value to the final product were eliminated and compared with previous results. Keywords: Value Stream Mapping, Lean manufacturing, Time-Study, 5s, Productivity

Combining metaheuristics and process mining: Improving cobot placement in a combined cobot assignment and job shop scheduling problem

Human workers can share a workspace with modern collaborative robots (cobots). The main differences to traditional robots are, that workers do not need a safety distance when interacting with cobots, as they move slower than typical industrial robots. Cobots also have fast setup times compared to traditional resources. The hybridization is based on a previous work of the authors, where a job shop scheduling problem that is extended with a robot to workstation assignment with a hybrid genetic algorithm is solved. In this paper, the potential of hybridizing an optimization algorithm with process mining techniques to improve the solution quality by gaining information on the solution structure is analyzed. This additional information should help to guide the search process. Process mining techniques are presented to analyze the solutions and learn from them. The idea of this work is to understand the solutions generated by the genetic algorithms as process executions, e.g., the production of a part as a process instance executed across the selected work stations. Then, by generating process event log data out of selected solutions, state-of-the-art process mining techniques can be used as visualization and scanning tools for the underlying processes. This way, for example, bottleneck workstations in the production process can be highlighted. Based on created scenarios, this paper demonstrates how genetic algorithms and process mining techniques can be combined. In the future, it is planned that information that is mined from generated logs of an evaluation framework is used to improve the performance of hybrid genetic algorithms by using this information in a feedback loop. Generated insight in cobot placement can also be used for prescriptive analytics in real-world manufacturing companies that want to utilize cobots. The focus of this paper lies in the discussion of the usage of potential information extracted from process mining.

Batch Assignment of Parallel Machines in an Automotive Safety Glass Manufacturing Facility

In this paper, optimization algorithms are used to solve a batch assignment problem of parallel processing furnaces in American Glass Products (AGP), a world leader company in the design and manufacturing of curved armored glass for transportation purposes. The problem consists in optimizing the bending process, which is considered to be the bottleneck workstation in the armored glasses production line in AGP. The objective is to maximize the efficiency of the furnaces and minimize the tardiness delivery of orders. Due to the complexity and constraints of the problem, we developed a proper dispatch algorithm and a Tabu search technique. The results are encouraging: the indicators of furnace usage hours and tardiness delivery improved by 32 % and 7 %, respectively compared to the decisions made in the plant during an actual production week. This work was the winner of an operation research challenge between around 100 graduate students. The challenge was organized by Javeriana University and AGP.

Reconfiguration of Virtual Cellular Manufacturing Systems via Improved Imperialist Competitive Approach

This paper constructs an integrated virtual reconfiguration model that can simultaneously group workstations, schedule virtual cells, and select energy consumption levels. If managers prefer the physical proximity of machines in a certain virtual cell, the material handling cost in it can be reduced. However, the distances among machines in other virtual cells are probably large, which may cause greater material handling cost. If a virtual cell for a certain product type has priority to be created, the backorder cost of that type can be decreased or even avoided. Nevertheless, the creation of virtual cells for other product types may be delayed, perhaps leading to the higher backorder cost of other product types. In addition, managers can choose a high energy consumption level of a machine to expedite its production to reduce backorder cost at the expense of more energy consumption cost. To minimize the total operational cost, we develop a novel Discrete Imperialist Competitive Algorithm with a Priority rule-based heuristic (DICAP). It includes a colony movement strategy, a competition strategy, a collapse mechanism, a development strategy, and a sufficient convergence policy. Numerical experiments and t-test are conducted to validate that the proposed DICAP outperforms genetic algorithm and simulated annealing. Note to Practitioners —Virtual cellular manufacturing systems can create an expectation of improving machine utilization and productivity, reducing reconfiguration cost, and adaptation to product specification changes in reality. However, managers often feel difficult to make appropriate decisions for three interrelated issues, i.e., workstation grouping, virtual cell creation and release, and energy consumption options. Workstation grouping depends on the availability of machines and workers, and the availability may be related to the creation and release time of some virtual cells. Whether a virtual cell is created in time has an influence on the selection of energy consumption levels, because managers need to consider both backorder cost and energy consumption cost. In addition, there often exists a bottleneck workstation in each virtual cell. Therefore, it is essential and worthwhile to select appropriate energy consumption levels of machines to smooth the production efficiency of grouped workstations. To effectively address the issues, this paper presents an integrated virtual reconfiguration model. A novel Discrete Imperialist Competitive Algorithm with a Priority rule-based heuristic is developed to minimize the total operational cost. Numerical experiments and t-test results indicate that the proposed algorithm outperforms two commonly used ones, i.e., genetic algorithm and simulated annealing in solution quality. It is suitable for virtual reconfiguration problem with industrial size in practice.

Lean Precast Production System based on the CONWIP Method

To enhance the level of precast production management, and to reduce the costs of precast production, a lean precast production system is developed based on the constant work-in-process (CONWIP) method. Then the performance of this system is verified using the Discrete Event Simulation (DES). A quantitative performance evaluation between the lean precast production system and the current precast production process is provided using the JaamSim simulation platform. Cases and site visits to precast concrete plant in China are combined to collect the production procedures and initial parameters involved in precast production. Through simulations, Non-value Adding (NVA) activities, as well as bottleneck workstations, are identified in precast production. The optimal number of cards to be used in the lean precast production system is also presented. Our simulation experiments show that the lean precast production system provides an effective way to control queue length and shorten the WIP and cycle time, while also maintaining throughput and saving 25.4% of labour cost.

Worker assignment and production planning with learning and forgetting in manufacturing cells by hybrid bacteria foraging algorithm

We consider a joint decision model of worker assignment and production planning in a dynamic cellular manufacturing system of fiber connector manufacturing industry. On one hand, due to the learning and forgetting effects of workers, the production rate of each workstation will often change. Thus, the bottleneck workstation may transfer to another one in the next period. It is worthwhile to reassign multi-skilled workers such that the production rate of bottleneck workstation may increase. On the other hand, because of the limited production capacity and variety of orders, late delivery or production in advance often occurs at each period. The parts with operational sequence need to be dispatched to the desirable cells for processing. The objective is to minimize backorder cost and holding cost of inventory. To solve this complicated problem, we propose an efficient hybrid bacteria foraging algorithm (HBFA) with elaborately designed solution representation and bacteria evolution operators. A two-phase based heuristic is embedded in the HBFA to generate a high quality initial solution for further search. We tested our algorithm using randomly generated instances by comparing with the original bacteria foraging algorithm (OBFA), discrete bacteria foraging algorithm (DBFA), hybrid genetic algorithm (HGA) and hybrid simulated annealing (HSA). Our results show that the proposed HBFA has better performance than the four compared algorithms with the same running time.

Suzhal – An Alternative Layout to Improve Productivity and Worker Well-being in Labor Demanded Lean Environment

Ergonomics continues to be relevant in work-places in which a significant amount of manual labor exists, such as in some of the Cellular manufacturing Systems (CMS). In order to distribute the workload evenly over all the workers in the line, some of the industries resorted to the practice of rotating all the workers through all workstations in the cell (Nagare cell) that prevents monotony and boredom. The presence of automated equipment in the cell will hamper this strategy for job rotation. This study aims to demonstrate the application of ergonomically designed looping layout in the assembly cell in the labor demanded lean manufacturing environment. The study was conducted in a process line in an automobile ancillary unit. The current process line which was conventional U-shaped line was simulated and the productivity has been verified and validated with the real life environment. Process map showed that the operators walked long distances, felt stress in certain workstations and that inventory piled up at the bottleneck workstation. We identify sub-cells within the cell. With the same manpower, we develop a new layout (Suzhal) and make workers rotate within each sub-cell. The proposed layout was simulated and results have been compared with the current layout. The analysis shows a reduction in the total operating cycle time, higher alertness among operators, better distribution of workloads in the group and hence higher productivity.

Real-time administration of tool sharing and best matching to enhance assembly lines balanceability and flexibility

Collaboration has been found in previous studies on the design of assembly lines to be a useful mechanism. In this study, the focus is on a collaborative assembly (CA) framework, inspired by the design principles of CCT, the Collaborative Control Theory, to improve balanceability and flexibility of assembly lines through tool sharing (TS) among idle and bottleneck workstations. TS is widely practiced in advanced assembly facilities to reduce cost and improve consistency and standardization in assembly and in assembly-and-test utilities, relying often on real time control. The framework developed here addresses the systems design aspect of Mechatronics, covering the planning, execution, and control mechanisms. Planning includes assembly line balancing (ALB) and initial TS decisions, made continually by solving a bi-objective mixed-integer program (BOMIP). A collaborative multi-agent system (CMAS) enhanced with a TS-best matching (BM) protocol is developed to execute the plan, control the process, and modify the TS decisions, considering dynamic changes in the system’s operations. Experiments show that the new CA framework significantly outperforms classic approaches (i.e., ALB without TS-BM) in terms of cycle time, utilization of tools, and balanceability. In addition, the control mechanism is proven to augment the line’s flexibility against the inherent uncertainties of assembly processes, compared to the previously developed static CA frameworks.

Research on the Improvement of General Assemble Line Bottleneck for the Car

As this paper takes the engine assemble line of a car’s general assemble line as the research subject, with the line balance tools to analyze the bottleneck of the production line,we put forward the corresponding method of determining the bottleneck workstation . And according to the principle and method of production line balance, we have studied from several aspects to improve and optimize the bottleneck workstation. The proposed methods and measures have reached the expected goal through the test and application of a bottleneck workstation.

Combination effects analysis of bottleneck-load order review/release and the dispatching rule: Application to a printed circuit board manufacturing line with multiple bottlenecks

The purpose of this paper is to consider the interaction among shop floor control strategies (order review/release and dispatching, ORR) and its effect on the performance of the printed circuit board manufacturing system with multiple bottleneck workstations. For that purpose, we suggest the pull from ORR strategies based on bottleneck-load and simulation tests and TOPSIS analysis are performed to compare various combinations of bottleneck-load ORR mechanisms and dispatching rule at each bottleneck workstation. An experiment is performed based on a real case in Korea and used for data from simulation test. The performance of proposed ORR strategies is improved when the strategies are combined with a suitable dispatching rule at each bottleneck workstation. The experimental results demonstrate that the interaction between the bottleneck-load ORR and the optimal combination of the dispatching rule at each bottleneck workstation is highly relevant with respect that the performance indicators have a characteristic of “lower is better”, such as average tardiness, cycle time, and WIP level.

Implementing lean standard work to solve a low work-in-process buffer problem in a highly automated manufacturing environment

Over the past few decades, a considerable number of studies have been reported on assembly lines or less automated factories. Little attention has been given to implementing lean tools to a highly automated manufacturing environment. It is, therefore, necessary to make a more highly automated factory lean by considering both the manufacturing system variability and demand uncertainty. The purpose of this paper is to propose an effective lean tool to help practical lean participants successfully implement lean practices in a highly automated manufacturing environment. This study presents an example of how lean standard work is implemented and the throughput of a pacemaker workstation is improved by solving the low work-in-process buffer problem. A practical case from a photovoltaic module process with a semi-automated production line is used to illustrate the proposed method. The implementation results are promising. They showed a 37.5% labour reduction prior to the pacemaker workstation and a 304.7% increase in the daily throughput at the bottleneck workstation.

A Bottleneck Detection Algorithm for Complex Product Assembly Line Based on Maximum Operation Capacity

Because of the complex constraints in complex product assembly line, existing algorithms not always detect bottleneck correctly and they have a low convergence rate. In order to solve this problem, a hybrid algorithm of adjacency matrix and improved genetic algorithm (GA) was proposed. First, complex assembly network model (CANM) was defined based on operation capacity of each workstation. Second, adjacency matrix was proposed to convert bottleneck detection of complex assembly network (CAN) into a combinatorial optimization problem of max-flow. Third, an improved GA was proposed to solve this max-flow problem by retaining the best chromosome. Finally, the min-cut sets of CAN were obtained after calculation, and bottleneck workstations were detected according to the analysis of min-cut sets. A case study shows that this algorithm can detect bottlenecks correctly and its convergence rate is high.

Minimising throughput loss in assembly lines due to absenteeism and turnover via work-sharing

In this paper we analyse the loss of throughput rate of assembly line caused by slow pace of substitute workers (replacing absentees) having no prior experience in the required tasks. We proposed work-sharing mechanisms that improve the balance of the workload during the learning period. The proposed mechanisms add to the experienced neighbouring workers some of the workload of the inexperienced worker substituting an absentee. We call this workload ‘shared work’. After the performance of the substitute workers improves due to learning, the shared work is re-assigned to them (relieving their experienced neighbours). We provide analytic expressions for the line throughput rate, which is determined by sets of bottleneck workstations. These sets of consecutive workstations consist of the inexperienced workers replacing the absentees and the experienced workers assisting them during the learning periods. The decision variables of this model are: (1) the amount of shared work, and (2) the time in which the shared work is re-assigned to the substitute worker. Unique optimal values of these two variables are found via numerical study, for buffered and non-buffered lines. Experiments show that the proposed work-sharing mechanisms can significantly improve the line’s throughput, compared to the original system without work-sharing.

PENINGKATAN KAPASITAS PRODUKSI MELALUI PENERAPAN THEORY OF CONSTRAINT, PENJADWALAN MESIN PARALEL DAN BOTTLENECK SCHEDULING PADA PERUSAHAAN SHEET METAL WORK

This study aims to increase the production capacity of the server rack 08U Type Double ASeriesWallmounted BRI on company X. Current production did not reached the expected target of117 units / week because of the bottleneck workstation. The study began by identifying the bottleneckworkstation using the Theory of Constraints (TOC). The result of identification process showed twobottleneck work stations, that are work station Punching and Ovencoating. The production capacitywas improved by performing the steps as follows: 1) Add 1 machine at punching station, 2) performjob scheduling on parallel machines at punching station using Short Processing Time (SPT) criteria;3) perform job sequencing on bending station using Weighted Shortest Processing Time (WSPT)criteria; 4 ) adds overtime at ovencoating stations, and 5) implementing bottleneck scheduling methodto sequence all jobs. The Results of this study showed that makespan was reduced by 12.03% andproduction capacity increased by 41.9% so that the production target of 117% can be achieved.

Dynamic Tool Sharing with Best Matching Protocols for Efficient Assembly Line Balancing

In a typical assembly line, workstations can be classified into two sets: A) Fully loaded ( i.e. , bottleneck) and B) Partially loaded, with respect to the total processing times of their tasks and the cycle time. Collaborative Control Theory (CCT) is applied in this paper for efficient Assembly Line Balancing (ALB). Collaboration is carried out through: 1) Dynamic Tool Sharing (TS) between workstations in Sets A and B, and 2) Dynamic Best Matching (BM) between tasks and workstations. The purpose: Minimize the number of workstations and the cycle time, thus maximizing the line utilization/efficiency and the production throughput, and increase capability in dealing with demand variability. Collaboration between workstations is enabled, under TS protocol, in order for the workstations in Set A to make use of idle tools of workstations in Set B, thus minimizing the total processing time of the bottleneck workstation(s) ( i.e. , cycle time). A dynamic BM protocol is designed for optimal matching of tasks to workstations with respect to their processing times, precedence relations, and the cycle time. A bi-objective Mixed-Integer Programming (MIP) formulation is developed for modeling and analyzing the ALB-TS-BM decisions, minimizing the number of workstations ( i.e., Type -I ALB), and the average cycle time ( i.e. , Type -II ALB). A Fuzzy Goal Programming (FGP) method with imprecise goal hierarchy is applied for solving the bi-objective MIP model. The ALB-TS-BM model is original and first ALB solution method to consider CCT by TS, generalizable to and implementable in various instances of ALB problems through proper application of CCT principles. An illustrative example is used to exemplify the concept and its advantages over conventional ALB methods.

Heuristic scheduling policies for a semiconductor wafer fabrication facility: minimizing variation of cycle times

This paper presents heuristic scheduling policies for semiconductor wafer fabrication facilities. The proposed heuristic scheduling policies include the advanced operation due date (OPNDD) for a sequence control policy and the adaptive constant work-in-process (CONWIP) for an input release control policy. The objective of the proposed scheduling policies is to reduce the variation of cycle times in the wafer fab. The advanced OPNDD sets the higher priority to the front opening unified pod (FOUP) with the smallest operation due date that is computed using a generalized stochastic Petri net model, and at the same time regulates the queue lengths of the FOUPs in each stoker by preventing excessive queue lengths in bottleneck workstations. The adaptive CONWIP controls dynamically the input release time of FOUPs using the adaptive WIP level according to the current status of the wafer fab. The simulation experiments show that the proposed scheduling method is efficient in reducing the variation of cycle times.

Scheduling of parallel machines with sequence-dependent batches and product incompatibilities in an automotive glass facility

This application is motivated by a complex real-world scheduling problem found in the bottleneck workstation of the production line of an automotive safety glass manufacturing facility. The scheduling problem consists of scheduling jobs (glass parts) on a number of parallel batch processing machines (furnaces), assigning each job to a batch, and sequencing the batches on each machine. The two main objectives are to maximize the utilization of the parallel machines and to minimize the delay in the completion date of each job in relation to a required due date (specific for each job). Aside from the main objectives, the output batches should also produce a balanced workload on the parallel machines, balanced job due dates within each batch, and minimal capacity loss in the batches. The scheduling problem also considers a batch capacity constraint, sequence-dependent processing times, incompatible product families, additional resources, and machine capability. We propose a two-phase heuristic approach that combines exact methods with search heuristics. The first phase comprises a four-stage mixed-integer linear program for building the batches; the second phase is based on a Greedy Randomized Adaptive Search Procedure for sequencing the batches assigned to each machine. We conducted experiments on instances with up to 100 jobs built with real data from the manufacturing facility. The results are encouraging both in terms of computing time--5 min in average--and quality of the solutions--less than 10 % relative gap from the optimal solution in the first phase and less than 5 % in the second phase. Additional experiments were conducted on randomly generated instances of small, medium, and large size.