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The Seru Production System is a cellular production system that originated in Japanese manufacturing industry. Seru Production Systems evaluates the efficiency of assembly line and the flexibility of job-shop production together. Workers must be cross-trained and have advanced competency levels for different operations in Seru Production Systems. In this study, the employees' production rate at different labor competency levels assigned in the Seru Production System is compared with production rate they put forward while working in traditional assembly line production system. This paper examines various competence levels of employees capable of producing the entire product and their effects on total production output. First, traditional assembly line production rates were calculated via integer programming using well-known test problems. Then, these test problems were converted into serus run by workers with different competence levels, relevant operation times were calculated, and production rates were obtained. Paired t test is used to compare the production rates. The results show that Seru Production Systems provided more production than traditional assembly line. Moreover, a 2-way analysis of variance is applied to show that the output rates obtained from the traditional assembly line and Seru production methods are affected by different test problems and different worker competency levels. [ABSTRACT FROM AUTHOR]

Modular polyketide synthases (PKSs) are capable of synthesizing diverse natural products with fascinating bioactivities. Canonical enoyl‐CoA hydratases (ECHs) are components of the β‐branching cassette that modifies the polyketide chain by adding a β‐methyl branch. Herein, it is demonstrated that the deletion of an atypical ECHQ domain (featuring a Q280 residue) of Art21, a didomain protein contains an ECHQ domain and a thioesterase (TE) domain, reprograms the polyketide assembly line from synthesizing tetracyclic aurantinins (ARTs) to bicyclic auritriacids (ATAs) with much lower antibacterial activities. Genes encoding the ECHQ‐TE didomain proteins distribute in many PKS gene clusters from different bacteria. Significantly, the ART PKS machinery can be directed to make ARTs, ATAs, or both of them by employing appropriate ECHQ‐TE proteins, implying a great potential for using this reprogramming strategy in polyketide structure diversification. [ABSTRACT FROM AUTHOR]

Complexity is an important quantification of uncertain operation in assembly lines and the key source of invisible uncertainty problems in smart manufacturing. The purpose of this paper is to propose a complexity measurement approach to assess the complexity of assembly lines integrating humans, machines and configurations. First, the complexity models of the three states of the operation related to humans and machines are built based on information entropy and the operation time model. Then, an operational complexity model is built at the station level; it is constructed with a single station, parallel stations and sublines based on Kolmogorov entropy. The model quantitatively describes the cumulative complexity along with the material flow. Furthermore, the complexity model of the overall system is given, and the Lempel–Ziv algorithm is applied to measure the complexity flow along with the stations. The complexity equilibrium index is derived to quantify the balancing degree among the stations. The model incorporates uncertain operation into system modeling to quantify the influence of uncertainties on the state of the assembly line. An engine assembly line is used to validate that the approach can measure the complexity from operation to station to system. [ABSTRACT FROM AUTHOR]

Nowadays the organization of domestic serial production of high-tech products requires a lot of time. On the one hand, the reason is the restructuring of logistics chains with foreign suppliers, on the other hand, the building of cooperation in the country. For example, the duration of the implementation of promising production projects in the space industry is still years. Factories are changing approaches in the organization of work – one of the main ways to influence the duration of production is to reduce the time of their own production cycle. As a rule, the analysis of the organization of serial production begins with the final assembly, which determines the tact of work for all other sites that produce components. When evaluating the effectiveness of the organization of assembly production, criteria and factors are determined. The time of the product assembly cycle is taken as the efficiency criterion. It is necessary to determine the degree of significance for each factor and understand their mutual influence on each other. The purpose of the research is to develop a unified system of factors affecting the cycle, and a method based on this system for evaluating the effectiveness of the organization of assembly production. The article considers the technological process as a factor affecting the product assembly cycle.

The research aims to use the latest technology, namely "Concurrent Engineering ", to redraw production and assembly lines to be more efficient and take less time in manufacturing and delivery. Which will help to earn more money, reduce the cost, achieve quality standards, and continue the production line in the assembly lines of the General Company for Mechanical Industries / Automotive Assembly Line, calculating the workstations and stages until the final production and presenting it to the customer. It was noted that there were multiple problems that led to losses on the assembly line as a result of the lack of distribution and timing of activities across the stages of the production line, causing bottlenecks in some workstations. This was reflected in a loss of about (398) minutes at a cost of about $3,900 per minute, which led to insufficient use of human or material resources (machinery and equipment). The current study presented a proposal through which the assembly line can be restructured and the implementation of some activities that are close in completion time can be synchronized, which in turn leads to reducing the total completion time from (937.5 to 772 minutes), that is, by 16.75%, in addition to maximizing working times and machine operating efficiency. And reduce wasted time at most stations. [ABSTRACT FROM AUTHOR]

Copyright of Management & Quality / Zarządzanie i Jakość is the property of Scientific Society of Organization & Management / Towarzystwo Naukowe Organizacji i Kierownictwa and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

As the take-off of China's macro economy, as well as the rapid development of infrastructure construction, real estate industry, and highway logistics transportation industry, the demand for heavy vehicles is increasing rapidly, the competition is becoming increasingly fierce, and the digital transformation of the production line is imminent. As one of themost important components of heavy vehicles, the transmission front andmiddle case assembly lines have a high degree of automation, which can be used as a pilot for the digital transformation of production. To ensure the visualization of digital twins (DT), consistent control logic, and real-time data interaction, this paper proposes an experimental digital twin modeling method for the transmission front and middle case assembly line. Firstly, theDT-based system architecture is designed, and theDTmodel is created by constructing the visualization model, logic model, and data model of the assembly line. Then, a simulation experiment is carried out in a virtual space to analyze the existing problems in the current assembly line. Eventually, some improvement strategies are proposed and the effectiveness is verified by a new simulation experiment. [ABSTRACT FROM AUTHOR]

Abstract Modular polyketide synthases (PKSs) are capable of synthesizing diverse natural products with fascinating bioactivities. Canonical enoyl‐CoA hydratases (ECHs) are components of the β‐branching cassette that modifies the polyketide chain by adding a β‐methyl branch. Herein, it is demonstrated that the deletion of an atypical ECHQ domain (featuring a Q280 residue) of Art21, a didomain protein contains an ECHQ domain and a thioesterase (TE) domain, reprograms the polyketide assembly line from synthesizing tetracyclic aurantinins (ARTs) to bicyclic auritriacids (ATAs) with much lower antibacterial activities. Genes encoding the ECHQ‐TE didomain proteins distribute in many PKS gene clusters from different bacteria. Significantly, the ART PKS machinery can be directed to make ARTs, ATAs, or both of them by employing appropriate ECHQ‐TE proteins, implying a great potential for using this reprogramming strategy in polyketide structure diversification.

In the era where mass production is inevitable, developments in the manufacturing process have helped industries to produce goods in batches of enormous quantities. With the drastic growth in technology, it is crucial to update, and improve assembly lines continuously. This study aims to systematically understand the area where an assembly line needs improvement to enhance its process and productivity. Published articles related to assembly line improvements, lean techniques, and simulation were synthesized exhaustively. A Discrete Event Simulation model of an automated manufacturing company was developed based on the data acquired and observations. Integration of lean techniques along with simulation adds to the effectiveness of the proposed method. Crucial areas that need improvement were identified, and lean techniques such as Kaizen and Poka-Yoke were applied. The efficiency of the proposed improvements was visualized by altering the simulation model. The average WIP was reduced from 87.2 to 81.2, and the cycle time of seven stations was reduced as a result of the implementation of Lean principles. Laser Marking Station (Fixture clamping and Stopper Cylinder) and Pad Printing & Vision Inspection Station witnessed a twofold improvement in the proposed model. There was an improvement in throughput by 7.14%. The study would prove helpful for managers and policymakers to visualize the usefulness of implementing lean techniques with minimal investment. [ABSTRACT FROM AUTHOR]

On the sandy coastal plains, environmental filters that limit seedling establishment and survival create a naturally heterogeneous landscape, formed by vegetation patches inserted in a matrix of bare sandy soil. The succession processes in these ecosystems depend on some pioneer species that facilitate the recruitment and survival of other species. Here, we evaluated the spatial pattern and changes of vegetation patches of restinga (i.e., coastal sandy plain vegetation) over one decade (2011–2021). The research was carried out in Alagoas State, Northeast of Brazil. We considered as patches the vegetation islands inserted in a matrix of bare sandy soil and applied methodologies of photointerpretation. Landscape metrics included patch area, edge, shape, and core area. To test the effect of landscape metrics on species occurrence and species richness per patch, we applied generalized linear models (GLM) with binomial and quasi‐Poisson distributions, respectively. We used the "betapart" package to evaluate the importance of turnover and nestedness as drivers of beta diversity among patches. Our data indicate that a key plant (Myrciaria floribunda), which can propagate by root suckers, initiates a succession process, creating regeneration nuclei, which seem to follow a deterministic succession pattern until the patch reaches 10 m2 in area. In the successional sequence, the patches grow and coalesce with neighboring patches. Species richness of patches presented an unimodal response to patch size. Overall, there is a greater contribution of species turnover to among‐patch beta diversity. However, for patches smaller than 10 m2, beta diversity was mostly driven by nestedness, reflecting a process of species addition to the growing patches. The succession pattern found in the study area should be considered for the formulation of nature‐based restoration models, expected to be more efficient and effective for ecosystems with similar environmental filters. [ABSTRACT FROM AUTHOR]

The study focuses on optimizing the production process of a Turkish family company specializing in seat belt manufacturing, boasting an annual capacity of 810,000 units and employing 150 individuals. Serving major clients such as Otokar, Ford Otosan, Bmc, Karsan, Anadolu Isuzu, Mercedes, Man, Temsa, and Türk Traktör, the company utilizes pressing, plastic injection, and assembly lines in its production. With a specific emphasis on the sequencing and scheduling of the assembly lines, a mathematical model was formulated and solved using GAMS software. Comparative analysis, incorporating scenario assessments, revealed that the proposed model significantly enhanced efficiency compared to various scenario outcomes. [ABSTRACT FROM AUTHOR]

Copyright of Smart Rail Transit is the property of Smart Rail Transit Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose: With hybrid simulation techniques getting popular for systems improvement in multiple fields, this study aims to provide insight on the use of hybrid simulation to assess the effect of lean manufacturing (LM) techniques on manufacturing facilities and the transition of a mass production (MP) facility to incorporating LM techniques. Design/methodology/approach: In this paper, the authors apply a hybrid simulation approach to improve an educational automotive assembly line and provide guidelines for implementing different LM techniques. Specifically, the authors describe the design, development, verification and validation of a hybrid discrete-event and agent-based simulation model of a LEGO® car assembly line to analyze, improve and assess the system's performance. The simulation approach examines the base model (MP) and an alternative scenario (just-in-time [JIT] with Heijunka). Findings: The hybrid simulation approach effectively models the facility. The alternative simulation scenario (implementing JIT and Heijunka LM techniques) improved all examined performance metrics. In more detail, the system's lead time was reduced by 47.37%, the throughput increased by 5.99% and the work-in-progress for workstations decreased by up to 56.73%. Originality/value: This novel hybrid simulation approach provides insight and can be potentially extrapolated to model other manufacturing facilities and evaluate transition scenarios from MP to LM. [ABSTRACT FROM AUTHOR]

This research contributes to a innovative approach to address the increasing issues of workplace mental health and stress, particularly in high-pressure environments like assembly lines which also affects workers performance and companies productivity. Recognizing the harmful effects of stress on worker productivity, this study introduce stress-monitoring model using advanced machine learning techniques. Proposed model integrates Internet of Things (IoT) technology and machine learning techniques, utilizing a wearable watch to gather open-source physiological data indicative of workers stress in assembly lines. Key physiological markers, such as heart rate, respiration rate, and skin conductance, are analyzed. Based on these physiological indicators, the primary objective is to develop and validate framework that can accurately predict worker stress levels using IoT and machine learning models. The empirical results of the proposed approach demonstrate that the most effective model achieves an impressive accuracy score, with the XGBoost model providing 99% accuracy and Matthew’s correlation coefficient (MCC) of 0.99, surpassing the performance of Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), k-Nearest Neighbors (kNN), and Support Vector Machine (SVM). The practical implications of these findings suggest a significant potential for implementing such technology in high-stress work settings, offering a proactive tool for stress management and contributing to enhanced worker well-being and productivity.

This article aims to analyze the levels of waste of components used in destructive testing for releasing the assembly line of an automotive parts factory. In this way, it aims to apply an improvement that involves the reduction of the amount of parts destroyed daily, consequently reducing their monthly costs. For this, based on the case study methodology, the percentages of discard in relation to sales of all parts currently produced were surveyed, in order to identify the line that has more discarded components and, from this, to analyze the waste factors, based on the Lean Manufacturing concepts. After the waste analysis and the application of process improvement, there was a reduction in the cost of parts for destruction. The cost, which was 0.71% of the total monthly sales, became 0.19%.

This paper introduces an integrated methodology to enhance the efficiency of patch panel assembly lines by harnessing advanced artificial intelligence (AI) techniques. The primary objective is to minimise the total completion time of patch panels, a pivotal metric for manufacturing efficiency. The study employs the Assembly Line Production Optimisation (ALPO) model to analyze and enhance the production capacity of the bottleneck station. Existing challenges related to patch panel assembly line task distribution, process content, and tooling layout are scrutinised against production process standards for operational measurements. To achieve improvement, Deep Neural Network (DNN) and Recurrent Neural Network (RNN) models are employed in hidden layers, supplemented by deep feed-forward (DFF) layers for output, in adherence to engineering design principles. The bottleneck station's load rate is successfully reduced to below 80%, contributing to an overall balance rate increase from 73% to 88%. These outcomes signify a notable enhancement in production efficiency and employee satisfaction. The research utilises a dataset derived from the Microsoft Azure AI-based PdM dataset. The paper illustrates how AI techniques offer a comprehensive solution to address the inherent complexities in patch panel assembly line optimisation. [ABSTRACT FROM AUTHOR]

Machine vision with image sensors has been employed in smart manufacturing such as the popular automatic optical inspection (AOI) by deploying an image acquisition camera to optically scan the target device for quality defects. With the rapid progress of image sensor techniques, the RGB-D image sensor device that can capture operator assembly gesture actions to make intelligent interactions between a robot and an operator has been developed. In this study, we propose a smart assembly-line design for intelligent manufacturing or factory applications where a working mode of human–robot collaboration (HRC) will be incorporated. In the proposed HRC assembly line, the operator and manipulator (robotic arm) will co-work with each other where the appropriately deployed RGB-D image device (the well-known Intel RealSense camera in this work) is used to acquire assembly gesture data of the operator to further perform operator gesture recognition. The manipulator will then perform the corresponding feedback action according to the recognized operation gesture (e.g., grabbing the scissors and then moving to the operator if the gesture of winding the tape is recognized). For operator gesture recognition, we first construct three different sensing modalities of deep learning recognition channels, which are the RGB convolution neural network (CNN)-long short-term memory (LSTM) channel with RGB gesture image inputs, the depth CNN-LSTM channel with depth gesture image inputs, and the 3D-(x, y, z) LSTM raw channel with skeleton raw data inputs. A decision fusion scheme is then developed for hybridizations of recognition decision outputs of these three separated deep learning gesture recognition channels with different gesture sensing modalities. In this work, various weight combination strategies to achieve the decision fusion of three deep learning recognition channels are used to evaluate the effectiveness of operator gesture recognition. Experiments on classifications of ten categories of operator assembly gestures show that the half-quarter-quarter strategy with the setting of (wRGB, wDepth, w3D) = (0.5, 0.25, 0.25) for weight allocations of channel decisions can achieve the highest recognition accuracy [ABSTRACT FROM AUTHOR]

In the traditional assembly line balancing (ALB) problem, the processing times of tasks are assumed to be fixed and worker independent. However, these times vary among workers due to factors such as experience and skill. The type of problem in which workers are divided into hierarchical levels and the processing times and costs differ across the levels is known as the assembly line balancing with hierarchical worker assignment (ALBHWA) problem. In this study, for the first time in the literature, the minimisation of cycle time and total worker cost for the ALBHWA problem with a given number of workstations is considered. A mathematical modelling approach is developed to solve the problem and the performance of the model is evaluated through adaptation of the test problems from the literature. The results indicate that the proposed model is able to optimally solve the small-sized problems in reasonable time and achieve feasible solutions for the larger-sized instances. [ABSTRACT FROM AUTHOR]

Improving production processes includes not only activities concerning manufacturing itself, but also all the activities that are necessary to achieve the main objectives. One such activity is transport, which, although a source of waste in terms of adding value to the product, is essential to the realization of the production process. Over the years, many methods have been developed to help manage supply and transport in such a way as to reduce it to the necessary minimum. In the paper, the problem of delivering components to a production area using trains and appropriately laid-out carriages was described. It is a milk run stop locations problem (MRSLP), whose proposed solution is based on the use of heuristic algorithms. Intelligent solutions are getting more and more popular in the industry because of the possible advantages they offer, especially those that include the possibility of finding an optimum local solution in a relatively short time and the prevention of human errors. In this paper, the applicability of three algorithms -- tabu search, genetic algorithm, and simulated annealing -- was explored. [ABSTRACT FROM AUTHOR]

To solve the AGV (automated guided vehicle) scheduling problem in the no-buffer assembly line, a heuristic scheduling algorithm base on composite score is proposed, reducing the waiting time of AGVs when execute tasks in the system. Firstly, the classical AGV fleet size determination algorithm based on the mathematical model is improved. Then, an improved tabu search-based AGV look-ahead scheduling algorithm (LSA) is proposed, which has a composite score strategy. Different from the most reported algorithms, LSA takes parts delay time, AGV empty travel distance and other objects into account. Finally, the proposed algorithms are compared with other reported algorithms. The simulation experiments prove that LSA has better performance than other algorithms. The robotic experiments prove that the proposed algorithm works well in actual production scenarios. [ABSTRACT FROM AUTHOR]

In recent years, the use of robots and cobots allow to increase productivity and quality of products. Due to the higher investment, the robustness and efficiency of flow lines are crucial to reduce the throughput loss. The solution of installing buffers between stations increases costs and factory space. To improve the efficiency and robustness of assembly lines, the literature proposed some variants to the simple assembly line balancing problem. The introduction of fractional tasks and parallel workstations are two promising models proposed in recent works to reduce throughput loss caused by short failures. The potential of the two approaches has been studied individually, but no work has evaluated the integration of fractional and parallel tasks can further improve the efficiency of the production lines. This paper proposes a matheurstic method to design assembly lines integrating fractional tasks and parallel workstations. The approach proposed aims to reduce the computational complexity of the design of the assembly lines and provides a series of design alternatives. The simulation model tests the robustness of the design alternatives against short failures. The numerical results highlight how the proposed model improves the performance and the robustness of the assembly line when unforeseen events such as failures occur. The integration of fractional tasks and parallel tasks can improve the robustness against short failures. This benefit is relevant for robotic assembly lines, and the increasing use of cobots that are mainly used in the automotive, electronics sector, and metal machinery industries. [ABSTRACT FROM AUTHOR]

The multi-man concept is usually applied for assembly lines of complex large sized products incorporating large number of tasks with varying sized components. Most researchers consider multi-manned assembly line problem under the objective of minimizing number of stations resulting in workers walking around the two sides of the station. The aim of the present work is to balance a two-sided multi-manned assembly line using a genetic algorithm combined with a proposed assignment heuristic. The model is studied under the objective of minimizing the number of workers and mated stations simultaneously, with additional space constraint. This helps to minimize workers interference and time waste in workers movement. For the first time a dynamic crossover and mutation ratio technique is used in the assembly line balancing problem. Applying the proposed algorithm gives competitive results. The use of dynamic crossover and mutation proved to yield better results compared to the stationary values.

Multi-sided assembly line balancing problems usually occur in plants producing big-sized products such as buses, trucks, and helicopters. In this type of assembly line, in each workstation, it is possible to install several workplaces, in which a single operator performs his/her own set of tasks at an individual mounting position. In this way, the operators can work simultaneously on the same product without hindering each other. This paper considers for the first time the multi-sided assembly line balancing problem with the objective of minimising the cycle time, proposing a new mathematical formulation to solve small-sized instances of this problem. Besides, a metaheuristic algorithm based on variable neighbourhood search hybridised with simulated annealing is developed to solve large-sized instances. The algorithm is called adaptive because of the adopted neighbourhood selection mechanism. A novel three-string representation is introduced to encode the problem solutions and six different neighbourhood generation structures are presented. The developed approach is compared to other meta-heuristics, considering some well-known in literature test instance and a real world assembly line balancing problem arising in a car body assembly line. The experimental results validate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

This paper describes the application of computer simulation for the purpose of analysis of an assembly line and the subsequent proposal of changes to increase productivity. Tecnomatix Plant Simulation software was used for modeling, simulations, and analyses. Based on simulations and analyses of the original state, the bottlenecks of the line were identified, and improvement measures were proposed. The simulation model was adjusted, and the new state of the line was simulated. Based on the new simulation, it was proven that the proposed improvement would help in increasing the productivity of the assembly line. Computer simulation, in addition to verifying the production process itself, enables the optimal setting of the assembly line without interfering with the production itself.

Copyright of Chinese Journal of Liquid Crystal & Displays is the property of Chinese Journal of Liquid Crystal & Displays and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the field of industry, especially in the production areas, it is particularly important that the monitoring of assembly efficiency takes place in real-time mode, and that the related data-based estimation also works quickly and reliably. The Manufacturing Execution System (MES), Enterprise Resource Planning (ERP) and Customer Relationship Management (CRM) systems used by companies provide excellent support in data recording, processes, and storing. For Overall Equipment Effectiveness (OEE) data showing the efficiency of assembly lines, there is a regular need to determine expected values. This paper focuses on OEE values prediction with Multiple Linear Regression (MLR) as supervised machine learning. Many factors affecting OEE (e.g., downtimes, cycle time) are examined and analyzed in order to make a more accurate estimation. Based on real industrial data, we used four different methods to perform prediction with various machine learning algorithms, these were the cumulative, fix rolling horizon, optimal rolling horizon and combined techniques. Each method is evaluated based on similar mathematical formulas. [ABSTRACT FROM AUTHOR]

This article aims to analyze the levels of waste of components used in destructive testing for releasing the assembly line of an automotive parts factory. In this way, it aims to apply an improvement that involves the reduction of the amount of parts destroyed daily, consequently reducing their monthly costs. For this, based on the case study methodology, the percentages of discard in relation to sales of all parts currently produced were surveyed, in order to identify the line that has more discarded components and, from this, to analyze the waste factors, based on the Lean Manufacturing concepts. After the waste analysis and the application of process improvement, there was a reduction in the cost of parts for destruction. The cost, which was 0.71% of the total monthly sales, became 0.19%. [ABSTRACT FROM AUTHOR]

As a result of constant competitive pressure, companies are forced to constantly look for ways to produce more efficiently. To increase production efficiency and competitiveness, the actual situation needs to be analyzed and measures proposed. However, proposals, when put into practice, do not always result in improvements, due to various errors and omissions in their design. A helpful tool to minimize failures is to apply computer simulations, in which the proposed solutions are being tested and a proven solution implemented into practice afterwards. This is especially important when a proposed solution requires increased investment costs and time. This paper deals with streamlining technological processes on an assembly line of a turbocharger with an electrically controlled actuator, by automating a section of the assembly line (reduced number of operators and defective products), based on analysis and identified deficiencies. The Tecnomatix Plant Simulation software was chosen to analyze the assembly line's condition, as well as to simulate proposed measures' impact on the line's improvement. The design brings increased efficiency of a turbocharger assembly process and a reduced number of workers. According to the simulation results, when proposed improvements are applied, the annual production of the assembly line increases from 89,575 pieces to 98,139 pieces, which is 8,564 pieces more, i.e., an increase of 9.56%, while reducing the number of workers from four to three. [ABSTRACT FROM AUTHOR]

Parts kitting is a frequently adopted method to feed parts from a warehouse to an assembly line. While kitting allows minimisation of space occupation and Work In Process holding cost at the workstations, also simplifying materials flow and supporting manual assembly, it is penalised by high workforce cost for manual kits preparation. For this reason, automated kitting systems have been also proposed although their practical application is somewhat limited owing to the relevant capital investment and scarce performances of robotised kitting systems. Moreover, economic models allowing a quantitative comparison of manual and automated kitting systems are not yet available in the literature. As a contribution to fill this gap, in this paper a cost model useful to compare manual and automation-assisted parts retrieval and kitting systems is presented. The model can be used as a decision-making tool when planning and justifying kitting systems. The model includes capital investment, workforce, space occupation and quality costs. A case study as an application example is also included to demonstrate the model capabilities. Results show that automation-assisted kitting systems can be competitive in comparison to manual kitting and that break-even conditions can be also identified by the proposed method. [ABSTRACT FROM AUTHOR]

Customers are frequently drawn in by lucrative deals and discounts offered by businesses. These interested customers are referred to as encouraged arrivals. The major goal of this study is to evaluate the performance of the automobile assembly line in order to decrease waiting time by coordinating the activities at each workstation using stopwatch time study approach. The novelty of this research is to convert poisson arrival to encouraged arrival with some discounts (like.,10%, 20%). The queuing problem is represented by the notation M/M/1: FCFS/8/8 in Kendall's notation. It is a single channel, multi-server service with infinite system capacity and an infinite number of calling population. Data concerning the system's encouraged arrival and service distribution were established. These data were used to calculate the system performance parameter. The finding of the study was used to predict the system's performance and effectiveness and to make logical recommendations for possible future improvements. According to the results, it is possible to conclude that increasing the level of automation reduces part waiting time, decreasing the cost of waiting. When compared to the poisson arrival system, the size of the Markovian encouraged arrival queuing system is increased as shown in the table. Little's law is verified that system size and queue size is same as in length. Little's law is used to predicts lead time based on production rate and work-inprocess. Here it is verified as shown in table. [ABSTRACT FROM AUTHOR]

A multi-manned assembly line is a generic type of assembly line which is common industrial procedures in industry of large sized products. In such line, the position of tasks in the product is critical to be considered to eliminate worker interference and, as a result, decrease unplanned waiting time. However, limited literature considers the position of tasks from the mounting position perspective. This paper introduces a Genetic Algorithm with the objective of minimizing number of stations to address the multi-manned multi-position assembly line balancing problem. A new constraint is defined, technological constraint where the tasks are constrained with their installation and position in the product and equipment required for them in the station. The performance of the model is compared to the existing approaches and it proves its effectiveness. The practical applicability was also examined through balancing a real-life assembly line problem and the results show its validity in practical application.

This study presents an approach to solving the assembly line balancing problem (ALBP) using the Methods-Time Measurement (MTM) time standard and simulation software. ALBP is a common problem in manufacturing where a set of tasks with fixed times must be assigned to a series of sequential workstations in order to minimize the total idle time and reduce the assembly cost per product. This study uses MTM, a widely used production process scheduling method, to create a new time analysis of an assembly process that was previously balanced using the Work-Factor method and time study. This literature review shows that there are a lack of combinations of updated time analyses with newer simulation approaches in the current literature, and this was the motivation for the present work. An assembly line simulation was performed using Simio software to evaluate different design options and operating scenarios. The results show that the use of MTM and simulation can help minimize idle time and improve assembly line performance, thereby reducing costs and increasing efficiency. This study shows that the approach of using MTM and simulation is effective in solving ALBP and is a useful tool for manufacturing companies to improve the performance of their assembly lines and reduce costs. [ABSTRACT FROM AUTHOR]

This paper describes the application of computer simulation for the purpose of analysis of an assembly line and the subsequent proposal of changes to increase productivity. Tecnomatix Plant Simulation software was used for modelling, simulations, and analyses. Based on simulations and analyses of the original state, the bottlenecks of the line were identified, and improvement measures were proposed. The simulation model was adjusted, and the new state of the line was simulated. Based on the new simulation, it was proven that the proposed improvement would help in increasing the productivity of the assembly line. Computer simulation, in addition to verifying the production process itself, enables the optimal setting of the assembly line without interfering with the production itself. [ABSTRACT FROM AUTHOR]