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In manual order picking systems, a paper list specifying the name, location, and amount of each item is often given, and this would exert mental pressure on pickers while finding target shelf bins in high-density picking environments. Augmented reality (AR) can provide a friendly alternative to improve the manual order picking performance by conveying picking information into visual instruction. Nevertheless, there is still no systematic consensus to deploy the pick-by-AR associated with actual warehouse workplaces. To establish a spatial correspondence between the visual guidance with the actual workplace, the multi-marker-based global map about the warehouse floor is established in advance. Instead of traditional single marker-based pick-by-AR methods, the warehouse floor-related map can provide an accurate and continuous navigation performance for intuitive AR guidance, allowing the picker to move freely on the warehouse floor without limiting to some certain locations. Besides, a systematic pick-by-AR solution is available by integrating the proposed method to a lightweight wearable AR device, and this easy-to-deploy pick-by-AR solution can alleviate the worker's mental effort while doing picking action. Finally, the pick-by-AR system described in the paper is deployed in the automobile assembly line, and experimental results illustrate that the proposed method can improve the picking efficiency while reducing the picking errors compared with the current paper-based order picking. [ABSTRACT FROM AUTHOR]

This paper introduces a web-platform system that performs semi-automatic compute of several risk indexes, based on the considered evaluation method (e.g., RULA—Rapid Upper Limb Assessment, REBA—Rapid Entire Body Assessment, OCRA—OCcupational Repetitive Action) to support ergonomics risk estimation, and provides augmented analytics to proactively improve ergonomic risk monitoring based on the characteristics of workers (e.g., age, gender), working tasks, and environment. It implements a body detection system, marker-less and low cost, based on the use of RGB cameras, which exploits the open-source deep learning model CMU (Carnegie Mellon University), from the tf-pose-estimation project, assuring worker privacy and data protection, which has been already successfully assessed in standard laboratory conditions. The paper provides a full description of the proposed platform and reports the results of validation in a real industrial case study regarding a washing machine assembly line composed by 5 workstations. A total of 15 workers have been involved. Results suggest how the proposed system is able to significantly speed up the ergonomic assessment and to predict angles and perform a RULA and OCRA analysis, with an accuracy comparable to that obtainable from a manual analysis, even under the unpredictable conditions that can be found in a real working environment. [ABSTRACT FROM AUTHOR]

The advances in Industry 4.0 provide both challenges and opportunities for digital manufacturing and assembly systems. This paper first addresses the state-of-the-art readiness for Industry 4.0 concerning assembly and manufacturing systems through a literature review of the relevant papers recently published. Then it assesses the challenges faced nowadays by assembly and manufacturing systems. Third, it focuses on the most promising future developments and evolution of such production systems as well as their digitalisation. Finally, this manuscript illustrates the content of the papers selected for this special issue. Through the study presented in this special issue, valuable contributions to both theory and application in this area have been achieved, and a useful reference for future research is given. [ABSTRACT FROM AUTHOR]

Currently, the largest percentage of the employed workforce in the manufacturing industry is involved in the assembly process, making ergonomics a key factor when dealing with assembly-related problems. During these processes, repetitive tasks and heavy component handling are frequent for workers, who may result overloaded from an energetic point of view, thus affecting several aspects not only relating to the human factor but also to potentially reduced productivity. Different organizational strategies and technological solutions could be adopted to overcome these drawbacks. For these purposes, the present paper proposes a genetic algorithm for solving the typical problem of assembly line balancing, taking into account job rotation and human–robot collaboration for enhancing ergonomics of workers. The objectives of the problem are related to both economic aspects and human factor: (i) the cost for implementing the assembly line is minimized, evaluated on the basis of the number of workers and differentiated by skill levels and on equipment installed on workstations, including collaborative robots, and (ii) the energy load variance among workers is also minimized, so as to smooth their energy expenditure in performing the assigned assembly operations, calculated according to their movements, physiological characteristics, job rotations and degree of collaboration with robots. The paper finally presents and discusses the application of the developed tool to an industrial assembly case. [ABSTRACT FROM AUTHOR]

Assembly sequence planning is one of the most important processes in mass production. However, this process is currently impeded by the lack of feedback for the next process how to plan an excellent assembly line. In this paper, we introduce the priority graph model, develop the subassembly recognition method, and design the selection algorithm with feedback weights for assembly line design in topological sequencing. We show that the method can quickly plan a satisfactory sequence compared to heuristic algorithms. Due to the different weights from assembly line designers, satisfactory assembly sequences with different adaptability can be planned. This work has implications for co-design of assembly sequence planning and assembly line design. [ABSTRACT FROM AUTHOR]

Virtual reality (VR) offers a promising set of technologies to digitally simulate industrial processes and interaction between humans and machines. However, the use of immersive VR simulations is still limited in industry due to the uncertainty of benefits in respect with traditional digital tools, and the lack of structured methodologies to effectively implement immersive virtual simulations in practice. This paper deals with the application of VR to create virtual manufacturing simulations with the aim to design assembly lines in compliance with factory ergonomics. It proposes a methodology to allow the virtualization and simulation of assembly tasks using a combination of VR tools by replicating, or rather anticipating, what would happen at the shop floor. The adopted tools are Unity 3D for virtual environment generation, HTC VIVE to immerse the user in the virtual factory layout, Xsens as tracking system, and Leap Motion for gesture recognition. The paper also compares the new VR-based procedure with a more traditional desktop-based digital simulation on industrial cases. Results show that the new methodology is more precise to detect the operator's comfort angles and more powerful to predict process criticalities and optimize factory layout design. At the same time, it is less sensitive to errors during ergonomic assessment related to the expert's subjectivity during the analysis. [ABSTRACT FROM AUTHOR]

Acoustic lining assemblies with millions of high-density array holes are key structures for high-performance and low-noise aero-engines. However, the material specificity, variable curvature shape structure, high-order number of holes, and small-sized hole spacing of acoustic lining assemblies pose great challenges to the hole-making technology. In this paper, in view of the machining requirements of millions of acoustic lining holes, a hole matrix unit design method for batch hole making is proposed. The optimal hole matrix unit dimension is calculated with the angle deviation of normal vector as the constraint by matching the structural features of the acoustic lining assembly, dividing and interpolating the hole-making surface, and solving the normal vector of the hole position. The experimental results show that the proposed hole matrix unit design method can effectively control the angle deviation of normal vector of the acoustic lining holes and ensure the processing accuracy of the holes. [ABSTRACT FROM AUTHOR]

Sensors can produce large amounts of data related to products, design, and materials; however, it is important to use the right data for the right purposes. Therefore, detailed analysis of data accumulated from different sensors in production and assembly manufacturing lines is necessary to minimize faulty products and understand the production process. Additionally, when selecting analytical methods, manufacturing companies must select the most suitable techniques. This paper presents a data analytics approach to extract useful information, such as important measurements for the dimensions of a shim, a small part for aligning shafts, from the manufacturing data of a power transfer unit (PTU). This paper also identifies the best techniques and analytical approaches within the following six individual areas: (1) identifying measurements associated with faults; (2) identifying measurements associated with shim dimensions; (3) identifying associations between station codes; (4) predicting shim dimensions; (5) identifying duplicate samples in faulty data; and (6) identifying error distributions associated with measurement. These areas are analysed in accordance with two analytical approaches: (a) statistical analysis and (b) machine learning (ML)-based analysis. The results show (a) the relative importance of measurements with regard to the faulty unit and shim dimensions, (b) the error distribution of measurements, and (c) the reproduction rate of faulty units. Additionally, both statistical analysis and ML-based analysis have shown that the measurement 'PTU housing measurement' is the most important measurement among available shim dimensions. Additionally, certain faulty stations correlated with one another. ML is shown to be the most suitable technique in three areas (e.g. identifying measurements associated with faults), while statistical analysis is sufficient for the other three areas (e.g. identifying measurements associated with shim dimensions) because they do not require a complex analytical model. This study provides a clearer understanding of assembly line production and identifies highly correlated and significant measurements of a faulty unit. [ABSTRACT FROM AUTHOR]

Assembly sequence planning (ASP) plays an important role in the product design and manufacturing. A good assembly sequence can help to reduce the cost and time of the manufacturing process. However, ASP is known as a classical hard combinatorial optimization problem. With the increasing of the quantity of product components, ASP becomes more difficult and the traditional graph-based algorithm cannot solve it effectively. In this paper, the memetic algorithm (MA), which has been successfully applied in many areas, is used to solve the ASP problem. MA combines the parallel global search nature of evolutionary algorithm with local search to improve individual solutions. It can balance global search ability and local search ability very well. To improve the optimization performance of the approach, efficient genetic representation and operator schemes have been developed. To verify the feasibility and performance of the proposed approach, case study has been conducted and comparison has been made between memetic algorithm and genetic algorithm. The result shows that the proposed approach has achieved significant improvement. [ABSTRACT FROM AUTHOR]

Frequent changes in customer needs and large product variety are forcing manufacturing companies to move from mass production to mass customization. Customized production can be achieved by introducing reconfigurable production systems (RMS). The customized flexibility and several characteristics of RMSs provide many opportunities in terms of process and production planning. However, those characteristics greatly increase the complexity of the design and planning of production systems. This paper presents a decision support system relying on a skill-based approach to design a reconfigurable assembly line considering the planning of assembly processes and monitoring. The proposed decision aid system is modular in design and is composed of four modules. The main input data is a CAD model of a new product variant for the identification of the assembly and monitoring requirements. Besides, a current assembly system layout with its resource descriptions exists. In the first developed module, assembly-by-disassembly and a skill-based approach are used to generate different assembly plans. In the second module, feature recognition and skill-based approaches generate process monitoring alternatives. The third module uses a linear program (LP) that aims to minimize the total cost of workstation activation and reconfiguration, as well as cycle time, and to maximize the process quality of the assembly tasks. A user-based generative model design approach is applied to optimize the values of three objective functions. In the fourth and final module, a simulation of the optimized assembly plan allows either the validation of the assembly plan and process monitoring plan or initiates a new iteration due to their infeasibility. To further demonstrate how the proposed methodology works, some computational experiments are provided for two use cases. [ABSTRACT FROM AUTHOR]

The 4th industrial revolution (Industry 4.0, I4.0) is based upon the penetration of many new technologies to the industrial world. These technologies are posed to fundamentally change assembly lines around the world. Assembly systems transformed by I4.0 technology integration are referred to here as Assembly 4.0 (A4.0). While most I4.0 new technologies are known, and their integration into shop floors is ongoing or imminent, there is a gap between this knowledge and understanding the form and the impact of their full implementation in assembly systems. The path from the new technological abilities to improved productivity and profitability has not been well understood and has some missing parts. This paper strives to close a significant part of this gap by creating a road map to understand and explore the impact of typical I4.0 new technologies on A4.0 systems. In particular, the paper explores three impact levels: strategic, tactical, and operational. On the strategic level, we explore aspects related to the design of the product, process, and the assembly system. Additionally, the paper elaborates on likely changes in assembly design aspects, due to the flexibility and capabilities that these new technologies will bring. Strategic design also deals with planning and realizing the potential of interactions between sub-assembly lines, kitting lines, and the main assembly lines. On the tactical level, we explore the impact of policies and methodologies in planning assembly lines. Finally, on the operational level, we explore how these new capabilities may affect part routing and scheduling including cases of disruptions and machine failures. We qualitatively assess the impact on performance in terms of overall flow time and ability to handle a wide variety of end products. We point out the cases where clear performance improvement is expected due to the integration of the new technologies. We conclude by identifying research opportunities and challenges for advanced assembly systems. [ABSTRACT FROM AUTHOR]

This paper researches how to realize the automatic assembly operation on a two-finger precision manipulator. A multi-layer assembly support system is proposed. At the task-planning layer, based on the computer-aided design (CAD) model, the assembly sequence is first generated, and the information necessary for skill decomposition is also derived. Then, the assembly sequence is decomposed into robot skills at the skill-decomposition layer. These generated skills are managed and executed at the robot control layer. Experimental results show the feasibility and efficiency of the proposed system. [ABSTRACT FROM AUTHOR]

This paper aims to propose a novel placing method, i.e., place-between-paste-and-pad (PB), for mini-scale passive components to enhance electronic assembly lines' yield. PB means a component is designed to be placed at the midpoint between the pastes and pads on the length direction while it aligns with the pads' center on the width direction. An experiment that involves 12 printed circuit boards (PCB) and 4500 resistors R0402M (0.40 mm × 0.20 mm) is designed and conducted to get comparative results of PB and two industrial placing methods, i.e., place-on-pad and place-on-paste. Based on this experiment's results, PB outperforms the other two methods in terms of minimizing the components' final misalignment. Furthermore, PB is a low-cost placing strategy because PB does not need the real-time communication between the solder paste inspection machine and the pick-and-place machine. The placement method proposed in this study is expected to offer a low-cost exploration in the pick-and-place procedure to enhance the surface mount assembly quality of mini-scale passive components. [ABSTRACT FROM AUTHOR]

In this paper, we first investigate a semi-automated automotive engine assembly line in which the traditional strategy of using fixed workers in each manual assembly section is replaced by a new strategy of using walking workers. With this approach, both worker and engine travel simultaneously down the line; each worker is previously trained to accomplish a series of assembly tasks independently from start to finish in each manual assembly section. The study has shown great improvement of the overall system performance in terms of flexibility, efficiency, responsiveness and re-configurability using dynamic, flexible and skilled walking workers. Nevertheless, the main problem of this design is that each worker needs to be cross-trained to acquire a satisfactory level of skills associated with the assignment of assembly tasks. This is crucial for achieving a relatively even working speed at which each worker assembles a product down the line without major interruption between two adjacent workstations. In theory, the familiar degree of completing assigned tasks by each worker through training can be measured and expressed as a learning curve. In this case, the learning curve has been used to determine a trade-off decision between the complexity of assigned tasks and the duration of completing these tasks by a walking worker at a stabilised level. It has also been used to investigate the impact of the system variation that may affect the performance of individual walking workers through a learning process. Thus, the paper also describes a framework to assess the human performance by modelling the learning curve for each walking worker based in an integrated model. This model was created using a simulation tool Witness with its key input/output data manipulated externally by a series of Microsoft Excel worksheets incorporating the effect of a number of human factors in terms of cognitive and physical elements. With this method, the possible and realistic assignment of selected assembly tasks for each walking worker can be quantified. [ABSTRACT FROM AUTHOR]

widespread supposition on mixed-model assembly line-balancing problems assigns a task, which is shared between two or more models to a single station. Bukchin and Rabinowitch (European Journal of Operational Research, 174:492-508, ) relaxed the restriction for mixed-model straight-line assembly line problems and allowed tasks common to multiple models to be assigned to different stations, called task duplication. In this paper, considering the same relaxation but for mixed-model U-shaped assembly lines, a novel genetic algorithm (GA) approach for solving large-scale problems is developed. Although superiorities of U-shaped assembly lines over straight lines have been discussed in several articles, this paper makes the advantage more tangible by providing a quantitative example. This paper also presents a novel two-stage genetic algorithm which is fittingly devised for solving the new proposed model. In order to evaluate the effectiveness of the GA, one small-scale and one medium-scale problem are solved using both the proposed GA and Lingo 8.0 software, and the obtained outcomes are compared. The computational results indicate that the GA is capable of providing high-quality solutions for small- and medium-scale problems in negligible central processing unit (CPU) times. It is worth mentioning that, for large-scale problems, such as Kim and Arcus test problems, no analogous results for those obtained by our proposed GA exist. To conclude, it can be said that the proposed GA performs well and is able to solve large-scale problems within acceptable CPU times. [ABSTRACT FROM AUTHOR]

In this paper, we consider a three-stage assembly flowshop scheduling problem with bi-objectives, namely the mean flow time and maximum tardiness. This problem can be considered as a production system model consisting of three stages: (1) different production operations are done in parallel, concurrently and independently, (2) the manufactured parts are collected and transferred to the next stage, and (3) these parts are assembled into final products. In this paper, sequence-dependent setup times and transfer times are also considered as two important presumptions in order to make the problem more realistic. We present a novel mathematical model for a production system with a new lower bound for the given problem. Obtaining an optimal solution for this type of complex, large-sized problem in reasonable computational time by using traditional approaches and optimization tools is extremely difficult. Thus, we propose two meta-heuristics, namely simulated annealing and tabu search, to solve a number of test problems generated at random. Finally, the computational results are illustrated and compared in order to show the efficiency of the foregoing meta-heuristics. [ABSTRACT FROM AUTHOR]

Product requirements have changed dramatically in today’s industries forcing companies to implement flexible transfer lines manufacturing diverse product types. However, most of the researches dealing with transfer lines are so far limited to the mono-product and homogeneous lines (i.e., perfectly balanced). This paper addresses the problem of estimating the performance of multi-product, flexible transfer lines. Such lines are composed of several machines in series and can be used to manufacture a variety of products in a batch production environment. The machines are subject to random operation-dependent failures, and there are no intermediate buffers between adjacent machines. This paper aims to propose an analytical model for assessing the steady-state availability of such lines. A simulation model is also developed to mimic the real dynamic behaviour of flexible transfer lines. Thousands of production line configurations are tested in order to compare analytical results with simulation results. We used statistical tests to prove that the proposed formulae are exact and robust to model the steady-state availability of multi-product, unbuffered, flexible transfer lines subject to random failures. [ABSTRACT FROM AUTHOR]

This paper presents a fuzzy goal programming approach to solve a multi-objective mixed-model assembly line sequencing problem in a just-in-time production system. A mixed-model assembly line is a type of production line capable of diversified small-lot production and is able to promptly respond to sudden demand changes for a variety of models. Determining the sequence of introducing models to such an assembly line is of particular importance for the efficient implementation of just-in-time (JIT) systems. In this paper, we consider three objectives, simultaneously: minimizing total utility work, total production rate variation, and total setup cost. Because of conflicting objectives, we propose a fuzzy goal programming-based approach to solve the model. This approach is constructed based on the desirability of decision maker (DM) and tolerances considered on goal values. To illustrate the behavior of the proposed model, some of instances are solved optimally and computational results reported. [ABSTRACT FROM AUTHOR]

In an individualized shee metal assembly line, form and dimensional variation of the in-going parts and different disturbances from the assembly process result in the final geometrical deviations. Securing the final geometrical requirements in the sheet metal assemblies is of importance for achieving aesthetic and functional quality. Spot welding sequence is one of the influential contributors to the final geometrical deviation. Evaluating spot welding sequences to retrieve lower geometrical deviations is computationally expensive. In a geometry assurance digital twin, where assembly parameters are set to reach an optimal geometrical outcome, a limited time is available for performing this computation. Building a surrogate model based on the physical experiment data for each assembly is time-consuming. Performing heuristic search algorithms, together with the FEM simulation, requires extensive evaluations times. In this paper, a neural network approach is introduced for building surrogate models of the individual assemblies. The surrogate model builds the relationship between the spot welding sequence and geometrical deviation. The approach results in a drastic reduction in evaluation time, up to 90%, compared to the genetic algorithm, while reaching a geometrical deviation with marginal error from the global optimum after welding in a sequence. [ABSTRACT FROM AUTHOR]

In automotive body assembly systems, an optimum assembly sequence planning (ASP) not only increases production efficiency and product quality, but also decreases cost and process cycle time. Typically, ASP evaluation approaches are focused on design for assembly criteria, and very few studies have considered the impact of ASP on dimensional accuracy. The major challenges involving quality-driven ASP evaluation can be enumerated into three categories: (1) batch of compliant non-ideal parts to consider real part defects; (2) variation propagation modeling in multi-station assembly (MSA) system in the presence of stochastic manufacturing errors both at product and process levels; and, (3) the development of dimensional quality criteria for quantitative ASP comparisons. This paper proposes a methodology based on the modeling of dimensional errors propagation in MSA with a batch of compliant non-ideal parts to improve product dimensional quality through optimizing ASP and assembly line configuration. It entails three main steps: (i) assembly sequence generation by k-ary assembly operation method for a predetermined assembly line configuration; (ii) variation propagation simulation taking into account a batch of non-ideal parts, station-to-station repositioning errors, and spring-back phenomenon in MSA system; and, (iii) robust optimization of ASP based on developed quality criteria which contains two quantitative indices. The potential benefits of the proposed methodology are successfully demonstrated on automotive front-rail assembly process. [ABSTRACT FROM AUTHOR]

Two-sided assembly line balancing (ALB) problems usually occur in plants which are producing large-sized high-volume products, such as buses, trucks, and domestic products. Many algorithms and heuristics have been proposed to balance the well known classical one-sided assembly lines. However, little attention has been paid to solve two-sided ALB problems. Moreover, according to our best knowledge, there is no published work in the literature on two-sided ALB problems with zoning constraints (2sALBz). In this study, an ant-colony-based heuristic algorithm is proposed for solving 2sALBz problems. This paper also makes one of the first attempts to show how an ant colony heuristic (ACH) can be applied to solve 2sALBz problems. In the paper, example applications are presented and computational experiments are performed to present the suitability of the ACH to solve 2sALBz problems. Promising results are obtained from the solution of several test problems. [ABSTRACT FROM AUTHOR]

In this paper, exact algorithms for solving the simple assembly line balancing type I problem are presented. The proposed algorithms consist of a constructive and two destructive algorithms. Several well-known lower-bound computational methods are also applied in these algorithms. Computational experiments were carried out to test the performance of the proposed algorithms based on a set of benchmark problem instances. The computational results show that the algorithms proposed in this paper are efficient in solving the simple assembly line balancing benchmark problem instances. Moreover, a problem instance whose optimal solution had previously been unknown is solved by one of the proposed algorithms. [ABSTRACT FROM AUTHOR]

Today, the assembly process is the least automated phase of production for mechanical products. The percentage of the automated assembly line operations of automobiles fluctuates between 10 and 20% according to manufacturers. The use of industrial robots in the assembly lines played a decisive role in the development of their activity despite the high cost. Indeed, this strategy is a key element that increases productivity. The use of robots in assembly tasks requires the trajectory determination of parts to be assembled from the design phase of the product. This problem is difficult if the part may interfere with other elements and requires combined trajectories to avoid the interference. Therefore, the simulation of part assembling trajectories from the design phase is an interesting and topical research issue. The main objective of this paper is to develop a new approach to generate multidirectional combined trajectories of parts. A mathematical formulation of the proposed approach is firstly proposed, being based on both the position matrix concept and the bounding box method. A didactic example is used to illustrate the different stages of the proposed approach. To highlight the computer implementation of the proposed method, an industrial case study is presented. This example was chosen to illustrate the effectiveness of the proposed approach such as the gain of assembly time, the reduction of costs by robotization of the work, and the programming assistance of these robots. [ABSTRACT FROM AUTHOR]

Assembly planning plays a major role in the manufacturing industry. In order to reduce computational complexity, this paper presents a knowledge-based approach to the assembly sequence planning problem. The CSBAT (connection-semantics-based assembly tree) hierarchy proposed in this paper provides an appropriate way to consider both geometric information and non-geometric knowledge. In this research, the typical or standard CSBAT is applied to a given assembly problem. The structure of the KBASP (knowledge-based assembly sequence planning system) is proposed and there are different ways to construct plans for a CSBAT: by retrieving the typical base, by retrieving the standard base, and by geometric reasoning. The approach proposed in this paper can generate assembly sequences for each CSBAT directly, without the problem of merging plans for different child CSBATs. The application shows that the knowledge-based approach can reduce the computational complexity drastically and obtain more feasible and practical plans. [ABSTRACT FROM AUTHOR]

In order to improve the accuracy of productivity calculation and prediction, this paper aims to establish a mathematical model, which takes multi-factor revision into account, to evaluate the personnel operational capacity (POC) of aircraft assembly lines. Firstly, the assembly operation is divided into assembly operating elements (AOEs), which is based on the features of aircraft assembling and is for the provision of statistical units. Secondly, effective man-hour (EMH) is adopted as a yardstick to measure the POC. Then, considering the technical characteristics and environmental constraints of the real assembly line, detailed quantitative descriptions about the chosen key factors, namely assembling accuracy, learning effect, and assembling intensity, are provided, and these quantitative descriptions are used for the revision of the EMH in order to guarantee a higher precision. After that, several critical parameters such as the cycle time, tact time, and output of an assembly line can be solved out, from which the POC can be analyzed and reflected. Finally, this method has been successfully applied to a practical case, and the result justifies its advantage as well as feasibility. [ABSTRACT FROM AUTHOR]

We conducted a simulation to compare the following two strategies for the allocation of improvement programmes in a flow shop environment with a single product type: (i) the allocation of improvement programmes focused on the capacity constraint resource and (ii) the allocation of improvement programmes distributed along the production line. Our results show that when the utilisation of the restrained resource is high and the difference in the processing time between the restrained resource and the non-constrained resource is significant (higher than 5 %), the allocation of improvement programmes focused on the capacity constraint resource is the best choice. Because utilisation of the restrained resource and the difference between the restrained resource and the non-constrained resource diminish, there are a growing number of cases in which the distributed strategy prevails. Based on our results, a third strategy is proposed, as follows: the allocation of improvement programmes distributed equally upstream from the restrained resource, including the restrained resource itself. Our results suggest that the third strategy is an interesting choice for situations in which focusing large improvements on the constrained resource is impracticable and the utilisation of this resource is high. Finally, we present an algorithm that enables production managers in a practical situation to make a proper choice among the three allocation strategies tested in this paper. [ABSTRACT FROM AUTHOR]

In this paper, the segmented assembly path-planning problem is proposed to reveal an integrated assembly path-planning task. We define the two phases of an assembly path-planning task and address their differences. A new method based on rapid-growing random trees (RRT) is presented for obtaining a minimum-cost path and making the total cost of the solution path remain constant for solving the same path-planning tasks in different iterations. The approach is also able to guarantee a solution with smooth rotation motions. We test this algorithm in various examples with good performance. And we also discuss the impact of the random sample set size of the algorithm in path optimization and execution time in various situations including segmented assembly path-planning task. Based on the results from the tests, suggestions for selecting a proper random sample set size are given. [ABSTRACT FROM AUTHOR]

Mass production system design is a key for the productivity of an organization. Mass production system can be classified into production line machining a component and production line assembling a product. In this paper, the production line assembling a product, which is alternatively called as assembly line system, is considered. In this system, balancing the assembly line as per a desired volume of production per shift is a challenging task. The main objectives of the assembly line design are to minimize the number of workstations for a given cycle time (type 1), to minimize the maximum of the times of workstations for a given number of workstations (type 2), and so forth. Because this problem comes under combinatorial category, the use of heuristics is inevitable. Development of a mathematical model may also be attempted, which will help researchers to compare the solutions of the heuristics with that of the model. In this paper, an attempt is made to present a comprehensive review of literature on the assembly line balancing. The assembly line balancing problems are classified into eight types based on three parameters, viz. the number of models (single-model and multi-model), the nature of task times (deterministic and probabilistic), and the type of assembly line (straight-type and U-type). The review of literature is organized as per the above classification. Further, directions for future research are also presented. [ABSTRACT FROM AUTHOR]

embly line balancing has a considerable place in industrial importance. Hence, a lot of researchers are interested in this subject and several papers have been published so far. Many exact, heuristic, metaheuristic, and hybrid approaches have been used to solve this type of problems. Recently Ponnanbalam et al. (Int J Adv Manuf Technol 16:341–352, 2000) have considered a multi-objective genetic algorithm utilizing several simple heuristic rules for solving the simple assembly line balancing problems, one of these rules was “rank positional weight (RPW)” originally published in Helgeson and Birnie (J Ind Eng 12(6):394–398, 1961). Through providing two possible justifications, this note suggests that the mentioned rule can be mistakenly utilized and some revisions in Ponnanbalam et al. (Int J Adv Manuf Technol 16:341–352, 2000) seem to be necessary. [ABSTRACT FROM AUTHOR]

In manufacturing industries, digitization of design and manufacturing processes adds competitiveness to business in terms of automation, interconnectedness, better user experience, easier process analysis, and machine intelligence. In this paper, we have delineated our experience of estimating efforts required for digitizing design and manufacturing processes of large complex products prevalent in industries where myriad of such processes exist along with their individual complexities. We have analyzed process complexities and reconstructed use case points method of estimation. Prediction error analysis has been performed based on various established methods while validating estimation model. Historical data has been used for model training and validation. A sustained productivity factor of 28.5 consultant-hour/use case point exhibits acceptable average estimation error. We also delve into the replication of digitization effort estimation of homologous components. Analysis of an automotive sheet metal component realization process and its digitization effort estimation has been presented as a proof of concept. The method can be adopted for process digitization in both design and manufacturing realms. [ABSTRACT FROM AUTHOR]

This paper presents a multiobjective formulation of the buffer allocation problem in unreliable production lines. Majority of the solution methods for buffer allocation problems assume that the process times, time between failures, and repair times are deterministic or exponentially distributed. This paper relaxes these restrictions by proposing a simulation-based methodology which can consider general function distributions for all parameters of production lines. Factorial design has been used to build a meta-model for estimating production rate based on a detailed, discrete event simulation model. We use genetic algorithm combined to line search method to solve the multiobjective model and determining the optimal (or near optimal) size of each buffer storage. [ABSTRACT FROM AUTHOR]

A mixed-model assembly line is a type of production line where different models of a product are assembled on. Mixed-model assembly lines can respond to unanticipated changes in product demands quickly without keeping so many inventories. Designing mixed-model assembly line involves solving the traditional problems of the assembly line design (consists of balancing problem, determining cycle time, and the number and sequence of stations) in addition of determining the sequence of products in assembly line. The main goal of this paper is presenting a method in order to determine the sequence of products in mixed-model assembly line by considering Just-in-Time systems. Moreover, supplying some required components from feeding lines is considered. A mathematical model is presented which is capable of specifying the sequence of products in the mixed-model assembly line by considering main criteria and keeping feeding lines balanced. Mathematical model can be used for solving small-size problems. Because the combinatorial nature of sequencing problems typically provides an intractable search space for problems of 'real world' size, the search heuristics of simulated annealing and ant colony algorithms are presented and used to find solutions for several problem sets. Experimentations show that the simulated annealing approach outperforms the ant colony approach in objective function performance. [ABSTRACT FROM AUTHOR]

Mixed-model production is the practice of assembling different and distinct models in a line without changeovers with responding to sudden demand changes for a variety of models. In this paper, we specify sequence of models to minimize conveyer stoppages. We assume that our lines are fixed and we cannot change the balance of the lines. When the condition of lines like setup cost and demand of each model change, it is important to specify the sequence for minimizing the conveyer stoppages without balancing the line again because the main lines are fixed. We consider three objective functions simultaneously: minimizing the variation in the actual and required production capacity of the line and minimizing the objectives which increase the chance of conveyer stoppage, including: (a) minimizing the total setup time, (b) minimizing the total production variation cost, and (c) minimizing the total utility work cost. Because of conflicting objectives, we propose the fuzzy goal programming-based approach to solve the model. Finally, we present an estimator for nearness of conveyer stoppages and study about affecting of sub-lines and changing the conveyer velocity in a station for reducing stoppages. [ABSTRACT FROM AUTHOR]

In mechanical assemblies, individual components are placed together to deliver a certain function. The performance, quality, and cost of the mechanical assembly are significantly affected by its tolerances. Toleranced dimensions inherently generate an uncertain environment in a mechanical assembly. This paper presents a proper method for tolerance analysis of mechanical assemblies with asymmetric tolerances based on an uncertainty model. This mathematical approach is based on fuzzy logic and tolerance accumulation models such as worst-case and root-sum-square methods. A fuzzy-based tolerance representation is developed to model uncertainty of tolerance components in the mechanical assemblies. According to this scheme, toleranced components are described as fuzzy numbers with their membership functions constructed using the statistical distributions of manufactured variables. In this way, the uncertainty of assembly requirements and accumulation of tolerances are represented in the form of fuzzy number. In this paper, a new factor, the fuzzy factor, is introduced that helps converting the membership functions into fuzzy intervals that can be used for modal interval analysis. Equations for estimation of percent contributions of individual tolerances are introduced in terms of uncertainty parameter. These equations yield percent contributions of upper and lower bounds of independent variables (manufactured dimensions) on the upper and lower bounds of dependent variables (assembly dimensions). The proposed method is applied to an example, and its results are discussed. [ABSTRACT FROM AUTHOR]

This paper is concerned about the sequencing problems in pull production systems which are composed of one mixed-model assembly line and one flexible fabrication flow line with limited intermediate buffers. Two objectives are considered simultaneously: minimizing the total variation in parts consumption in the assembly line and minimizing the makespan in the fabrication line. The mathematical models are presented. Since the problem is Non-deterministic Polynomial-hard (NP-hard), a multiobjective genetic algorithm is proposed for solving the models, in which a method to generate the production sequence for the fabrication line from the production sequence for the assembly line is put forward, and Pareto ranking method and sharing function method are employed to evaluate the individuals' fitness. The feasibility and efficiency of the multiobjective genetic algorithm is shown by computational comparison with an adaptive genetic algorithm and a multiobjective simulated annealing. [ABSTRACT FROM AUTHOR]

In the body shop of an automobile assembly plant, having access to correct and timely information is very important in solving problems encountered in the assembly process. The Variation Reduction Adviser (VRA) system used within General Motors (GM) is a database containing problems encountered in this process and their possible solutions. The VRA acts as an electronic logbook that shares information across shifts within a plant as well as across multiple plants. The VRA also serves as a problem-solving tool by which solutions to problems encountered may be retrieved and reused. To function effectively as a problem-solving tool, it is important that relevant information is quickly retrieved from the VRA database. Traditionally, keyword-based retrieval strategies have been used. In these approaches, the user types in a list of words or phrases and those records in the database that contain those words or phrases exactly as typed are retrieved. The problem with this approach is that records containing words or phrases that are semantically related to the ones typed in but not exactly the same are not retrieved. For instance, if the user types “left-hand side,” the traditional keyword search will not find records that contain the abbreviation “LHS.” This paper describes a search mechanism based on a thesaurus (a simple version of an ontology) that overcomes this problem. It describes the standard criteria to measure the effectiveness of a search, defines a new criterion, and shows that in terms of these criteria, the ontology-guided approach gives better search results than the exact match mechanism. The results are shown in the context of real searches during the use of the VRA in a GM assembly plant. [ABSTRACT FROM AUTHOR]

In the last decades, the necessity to make production more versatile and flexible has forced assembly line production systems to change from fixed assembly lines to mixed model assembly lines, where the output products are variations of the same base product and only differ in specific customizable attributes. Such assembly lines allow reduced setup time, since products can be jointly manufactured in intermixed sequences (Boysen, Flieder, Scholl. Jena Research Papers in Business and Economics, Friedrich-Schiller-Universitat Jena, 1;1–11, ; Boysen, Flieder, Scholl. Jena Research Papers in Business and Economics, Friedrich-Schiller-Universitat Jena, 2;1–33, ). Unfortunately, the installation of customization options typically leads to variations in process times, and when the cycle is exceeded within a certain station, an overload is created, forcing other stations to wait and idle. Normally, process time variation in an un-paced line are absorbed by buffers, but in some industrial application the buffer dimensions are critical not only for the reduction of work in progress but also in reducing other constrains (space, technology, model dimensions, etc.). The problem of balancing mixed model assembly lines (MALBP), in the long term, and that of sequencing mixed model assembly lines (MMS), in the short term (Merengo, Nava, Pozetti. Int J Prod Res 37:2835–2860, ), are the two major problems to solve. The object of this paper is to illustrate an innovative balancing–sequencing step-by-step procedure that aims to optimize the assembly line performance and at the same time contain the buffer dimensions in function of different market demand and production mix. The model is validated using a simulation software and an industrial application is presented. [ABSTRACT FROM AUTHOR]

This paper presents a systematic approach for automatic assembly sequence planning (ASP) by using an integrated framework of assembly relational model (ARM) and assembly process model (APM), which are established by object-oriented method. ARM, consisting of assembly, components and liaisons, is the static model of assembly to describe the geometric relationships between components in terms of contact, constraint and interference matrixes. APM, containing states and sub-processes, is the dynamic model of assembly to represent all potential alternatives in assembly process. An algorithmic procedure is also presented by which APM of an assembly can be constructed systematically by analyzing states from lower levels to higher levels. Through the procedure, all feasible sequences of a product can be generated, and the optimum one can be determined by further evaluating each sequence. To explain the approach more clearly, a practical assembly with five components is used as an illustration in the paper. [ABSTRACT FROM AUTHOR]

Mixed-model assembly lines are widely used in manufacturing. This can be attributed to increased product variety and potential just-in-time (JIT) benefits obtained by applying mixed-model assembly lines. Because of market demand volatility, the flexibility of such a line is increasingly becoming more important and, consequently, determining an accurate sequence is becoming more complex. In this paper, first, we use the real options approach to evaluate one specific type of flexibility, i.e., product-mix flexibility. This methodology is applied to determine the products’ quantity that must be satisfied by the mixed-model assembly line. Then, in order to determine a desired sequence, we consider three objectives simultaneously: (1) total utility work cost, (2) total production rate variation cost, and (3) total set-up cost. A nonlinear zero–one model is developed for the problem whose objective function is a weighted sum of the above-mentioned objectives. Moreover, two efficient metaheuristics, i.e., a genetic algorithm (GA) and a memetic algorithm (MA), are proposed. These solution methods are compared with the optimal solution method using Lingo 6 software over a set of randomly generated test problems. The computational results reveal that the proposed memetic algorithm performs better than the proposed genetic algorithm. [ABSTRACT FROM AUTHOR]

Disassembly has gained much attention due to the growing concerns of material resources, energy conservation, and environmental conscious. The process of disassembly attempts to breakup a product into several pieces, with the expectation that the pieces together have a net value greater than the discarded product. In analyzing these aspects, one needs to determine all feasible ways to disassemble a product. This is especially true for the complex products like automobile, aircraft, etc. Most researchers took the algorithm of complete-disassembly planning to design for disassembly, although the feasible disassembly sequence can be obtained, parts of a assembled entity should be removed totally. And the required S (refers to disassembly sequence) could be gained through the proper analysis and evaluation; however, there are so many difficulties in this process and it is hard to obtain the optimum solution, especially when there are many parts in assembled body (such as automotive product). Therefore, it is very necessary to research the selectable disassembly algorithm of mechanical parts. This paper puts forward an algorithm on the selectable disassembly strategy of mechanical parts based on disassembly wave concept. It is comparatively easy and efficient to search, and get the optimal selectable disassembly sequence of mechanical parts with less amount of computing. It is so significant for all the steps of maintaining, recycling and discarding. [ABSTRACT FROM AUTHOR]

This paper presents a mathematical model that allows for the best thread-forming speed to be calculated based on a detailed efficiency function. The optimum thread-forming speed is calculated at several stages of the assembly process, and thus allows the creation of flexible control systems for automatic assembly devices. Controlling screwing speeds according to the suggested rule can reduce the torque (required to assemble threaded connections) by 15–20%. [ABSTRACT FROM AUTHOR]

In this paper, a scheduling problem in the flexible assembly line (FAL) is investigated. The mathematical model for this problem is presented with the objectives of minimizing the weighted sum of tardiness and earliness penalties and balancing the production flow of the FAL, which considers flexible operation assignments. A bi-level genetic algorithm is developed to solve the scheduling problem. In this algorithm, a new chromosome representation is presented to tackle the operation assignment by assigning one operation to multiple machines as well as assigning multiple operations to one machine. Furthermore, a heuristic initialization process and modified genetic operators are proposed. The proposed optimization algorithm is validated using two sets of real production data. Experimental results demonstrate that the proposed optimization model can solve the scheduling problem effectively. [ABSTRACT FROM AUTHOR]

In order to accompany the increasing variety of costumers’ demands, manufacturers tend to produce different models of the same product on an assembly line by introducing group assembly (GA) design concepts that improve the flexibility of assembly systems. Generally, when the demand for a set of similar products is relatively low and the set-up time is significant, the beneficial effects of the task repeatability of the straight line configuration are difficult to achieve. As a consequence, the fixed-point assembly philosophy is often preferred. This paper addresses the application of a mixed-model assembly balancing problem to an assembly-to-order environment in the case of low production rates and large number of tasks. The aim of this work is to propose an alternative design procedure for the balancing of semi-automated and mixed-model assembly systems under low product demand effects by the application of multi-turn circular transfers, such as a multi-stations rotating table. This layout configuration permits a job enlargement for human operators and, at the same time, provides an increment in task repeatability through the work-pieces assembling by increasing the number of the turns of the transfer. Finally, the developed heuristic procedure is tested on a simple rotating table assembly cell, a partial representation of a complete assembly system of domestic air compressors. [ABSTRACT FROM AUTHOR]

This paper describes the design and evaluation of a pilot information system to ease the burden of document configuration management for an aerospace manufacturer. The documents that comprised the content of the system are used to control manual activities associated with a large automated machine tool, such as machine setup, test piece checking and maintenance. The information content was in the form of web pages and PDF documents, both of which were presented to users via an Internet kiosk, in order to maximise usability and system security. The system was designed using a formal task analysis and evaluated using a method based on task-technology-fit theory and the technology acceptance model. It was shown that users would accept such a system and use it in preference to other sources of similar information. The greatest financial benefit of such systems is likely to be due to a reduced mean time to repair the machine. [ABSTRACT FROM AUTHOR]

Assembly sequence planning (ASP) is the foundation of the assembly process planning and design for assembly (DFA). In ASP, geometric feasibility is the prerequisite in the valid assembly sequences searching. The assembly precedence relations’ (APRs) deriving and fulfilling are the essential tasks in the geometric feasible assembly sequence planning. In this paper, a systematical approach called geometric constraint analysis (GCA) is proposed and the corresponding software system is developed and integrated with CAD system. Using this system, only with a few mouse clicks on CAD draft, assembly precedence relations (APRs) can be derived correctly and completely. Then, all the geometric feasible assembly sequences can be inferred out automatically. Moreover, an optimal algorithm is designed and realized in the GCA method, by which, the most optimal assembly sequence in terms of the operation convenience can be found out from the immense geometric feasible sequences. [ABSTRACT FROM AUTHOR]

Cellular manufacturing (CM) is an important application of group technology (GT) in which families of parts are produced in manufacturing cells or in a group of various machines. Cell design/formation is the first step in the design of cellular manufacturing systems. Many efforts have been made towards cell design taking into consideration multiple criteria. This paper presents a Pareto-optimality-based multi-objective tabu search (MOTS) algorithm to the machine-part grouping problems with multiple objectives: minimizing the weighted sum of inter-cell and intra-cell moves and minimizing the total cell load variation A new approach is developed to evaluate the non-dominance of solutions produced by the tabu search. Comparisons between MOTS and the genetic algorithm (GA) are done and the results show that MOTS is quite promising in multi-objective cell design . [ABSTRACT FROM AUTHOR]

In this paper, the effects of various dispatching rules on the operation and performance of cellular manufacturing systems (CMS) are evaluated. When the study of a CMS considers the automated material handling, it is crucial to reduce the gridlock probability (i.e., the probability of an unsuccessful load transfer attempt occurring in the interface point between the intercell and intracell handling system). Preventing an unsuccessful load transfer is critical for the operation of the entire system as a blockage between the automated guided vehicle (AGV) and the overloaded cell results in a total system shutdown. The gridlock probability is influenced by the dispatching rule used to schedule the load transfers in the system. Therefore, in order to reduce this probability it is necessary to use a dispatching rule that will decrease the number of waiting loads in the transfer spurs. The main objective of the paper presented herein is to identify a dispatching rule that maintains the system operational at all times. A group of dispatching rules, including the first come first served (FCFS), shortest imminent operation (SI), longest imminent operation (LI), most remaining operations (MRO), shortest processing time (SPT), shortest remaining process time (SR), and a newly developed rule proposed by the authors, loads with the minimum number of processing first (MNP), are tested and evaluated with respect to whether the capacity of the transfer spurs of the cells is exceeded. This paper presents a simulation model of a cellular manufacturing system, which is used to further explore the effects of the dispatching rules on the system performance. The results show superior performance of the newly proposed MNP rule. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new joint-based assembly modeling method. In joint-based assembly modeling, the assembly constraints are specified on the components, but not on the geometric elements of the components. The proposed method generates assembly models from kinematic joint constraints by applying three procedures (1) to extract all feasible JMFs (Joint Mating Feature) for each mating component using information on joint constraints, (2) to derive mating alternatives for each pair of mating components after reducing the number of JMFs using the pruning criteria, and (3) to generate an assembly model by choosing the intended one from the mating alternatives for each pair of mating components and solving the JMF constraints. Since the joint constraints are expressed in terms of the relations between components rather than relations between geometric elements, the proposed method is more intuitive and natural for assembly modeling and supports modeling activities effectively by minimizing user interactions. By using joint mating constraints for assembly modeling, moreover, the kinematic behaviors of assemblies determined in the conceptual design stage can be directly applied and consistently maintained up to the detailed design stage. In the proposed method, it is also not necessary to re-input the mating constraints even when the component topology is changed. [ABSTRACT FROM AUTHOR]

In the design activity, part geometry is assembled to create an assembly model. The number of parts may range from a few tens to a few million and typically the relationship among them constructs closed-loops with under-constrained states. In this paper, a 3D constraint solving method is proposed for closed-loop assemblies with under-constrained states. The proposed constraint solving method determines assembly configurations by applying the following procedures: 1. Transform the geometric mating relations into the kinematic joint relations, 2. Convert the closed-chain kinematic assembly to an open kinematic assembly by removing a joint, 3. Compute an open kinematic configuration by solving the open kinematic problem and 4. Obtain the closed-loop kinematic configuration by pasting the ‘cut’ links of the open assembly. The cut and paste operations minimise the number of constraint variables that have to be solved simultaneously. Thus, it can maximise the efficiency and robustness of an assembly constraint solver. The proposed constraint solving method combines the simplicity of a sequential solving approach with the universality of a simultaneous solving approach. [ABSTRACT FROM AUTHOR]

Modern manufacturing systems are expected to be flexible and efficient in order to cope with challenging market demands. Thus, they must be flexible enough as to meet changing requirements such as changes in production, energy efficiency, performance optimization, fault tolerance to process or controller faults, among others. Demanding requirements can be defined as a set of quality of service (QoS) requirements to be met. This paper proposes a generic and customizable multi-agent architecture that, making use of distributed agents, monitors QoS, triggering, if needed, a reconfiguration of the control system to recover QoS. As a proof of concept, the architecture has been implemented to provide availability of the control system understood as service continuity. The prototype has been tested in a case study consisting of an assembly cell where assessment of the approach has been conducted. [ABSTRACT FROM AUTHOR]