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Ever since the times of Henry Ford up to today’s industry 4.0 era, flow-oriented assembly processes, where an assembly line conveys the workpieces from workstation to workstation, are very important for mass-producers in manifold branches of industry. Among the most elementary optimization problems in this context is the assembly line balancing problem, which decides on the division of labor among the stations of an assembly line. This paper surveys the scientific literature on assembly line balancing that has been published since the last major review papers have appeared in 2006 and 2007, respectively. We cover all essential stages of the decision making process: we address novel methods to efficiently gather the relevant (precedence graph) data, review especially new problem variants and models treated in the literature, and survey the most important algorithmic developments. Furthermore, we outline a possible research agenda for the next fifteen years.

In this paper, we study an automated warehousing system, where racks are moved by robots to multiple workstations so that pickers at each workstation can retrieve the products from the racks to fill up the orders. In this context, the order and rack sequences should be considered simultaneously and the workload balance and rack conflicts among multiple workstations should also be taken into considerations. However, these factors have not been addressed in the current literature. To fill this gap, we formulate a comprehensive multi-workstation order and rack sequencing problem as a mixed integer programming model that accounts for workload balancing and rack conflicts. To solve the model, we propose an adaptive large neighborhood search method, which builds on a newly developed data-driven heuristic that exploits the structure of the problem and simulated annealing. We show that our proposed approach performs well on both small-scale problem instances with synthetic data and a large-scale real-world dataset supplied by a large e-commerce company. In the latter case, it can save up to 62% in rack movements compared to the company’s current practice.

Ergonomics aspects in the process of designing work facilities in an industry are important factors. Likewise, several other aspects that are closely related to ergonomics. Like anatomy and physiology, it is also necessary to know the causes of work discomfort, both from a human perspective as well as energy expenditure due to the workload it receives. The work station is an important part of an industry. With an ergonomic work station, employees can work safely, comfortably and productively. Conversely, if the work station is not ergonomic, incorrect postures will arise, so that the person's work performance will decrease, ineffective and efficient. This is because these postures can cause fatigue faster than ergonomic conditions. Workstations that cause work postures that are not ergonomic are found at the weaving operation station at PT “XX. The posture will be analyzed using biomechanics. And heart rate analysis is also performed to determine energy costs. Ergonomic workstations are also closely related to the match between the dimensions of the operator's body segments with the dimensions of the facilities used. If there is a mismatch, it will reduce the effectiveness of the operator's work. For this reason, work facilities that do not conform to the dimensions of the relevant operator body segment need to be redesigned. This redesign uses the operator population anthropometric data in the weaving operation.

In the pursuit of increasing efficiency, productivity and flexibility at production lines and their corresponding workstations, manufacturing companies have started to heavily invest in “collaborative workspaces” where close interaction between humans and robots promises to lead to these goals that neither can achieve on their own. Therefore, it is necessary to know the contributions, recommendations and guidelines that literature presents in terms of designing a manufacturing workplace where humans and cobots interact with each other to accomplish the defined objectives. These aspects need to be explored in an integrated and multidisciplinary way to maximize human involvement in the decision chain and to promote wellbeing and quality of work. This paper presents a systematic literature review on designing human-robot collaboration (HRC) workspaces for humans and robots in industrial settings. The study involved 252 articles in international journals and conferences proceedings published till 2019. A detailed selection process led to including 65 articles to further analysis. A framework that represents the complexity levels of the influencing factors presented in human-robot interaction (HRI) contexts was developed for the content analysis. Based on this framework the guidelines and recommendations of the analysed articles are presented in three categories: Category 1 – the first level of complexity, which considers only one specific influencing factor in the HRI. This category was split into two: human operator, and technology; Category 2 – the second level of complexity, includes recommendations and guidelines related to human-robot team’s performance, and thus several influencing factors are present in the HRI; and, finally, Category 3 – the third level of complexity, where recommendations and guidelines for more complex and holistic approaches in the HRI are presented. The literature offers contributions from several knowledge areas capable to design safe, ergonomic, sustainable, and healthy human-centred workplaces where not only technical but also social and psychophysical aspects of collaboration are considered.

OBJECTIVES The active factor along with light exercise can reduce static muscle work and increase muscle flexibility and endurance. Accordingly, this study aimed to design and prototype a new active footrest, implemented in conventional sitting workstations and to test its usability among office workers. METHODS The steps taken to design and prototype the active footrest were a) selection of an exercise appropriate for goals of ergonomic interventions, b) idea development, c) selection of the best conceptual design, d) design with SOLIDWORKS version 2016 software, and e) fabrication of a prototype. Afterward, the usability of the active footrest prototype was assessed among 20 office workers (10 females) using field data by the System Usability Scale. RESULTS Upon the completion of the design steps, the active footrest prototype was prototyped by taking into account design criteria (e.g. functionality, inclusive design, easy application, and reduction of additional body movement), anthropometric data and mechanical properties. The participants rated the usability of the active workstation as 89 ± 8.21 (out of 100) and indicating good usability results. CONCLUSION In this study, an active footrest was designed and prototyped to perform knee extension exercise with the capability of being implemented in conventional sitting workstations.

OBJECTIVES There is a pressing need to improve safety and efficiency in the operating room (OR). Postsurgical adverse events, such as surgical site infections and surgical flow disruption, occur at a significant rate in industrial countries where a considerable portion of such complications result in death. The aim of the study was to identify an ideal room design that improves the flow of staff members using risk and safety performance measures. METHODS Operating room designs were compared by using computer simulation modeling to analyze traffic flow inside an OR. The study was conducted in two phases. A historical data set was first created based on surgical flow data obtained from 23 video observations of actual surgical procedures. A detailed simulation-based model was then developed. RESULTS As room size increases, staff members have more available space to maneuver in the room, resulting in more distance walked but far fewer undesirable contacts. An angled table orientation is preferred with the circulating nurse workstation at the foot of the OR table, as it provides more space for staff to move across the room without increasing the number of contacts. Furthermore, when the nurse workstation is near the wall, staff members experience fewer undesirable contacts. CONCLUSIONS Simulation modeling was used to assess the impact of OR layout alternatives on three performance metrics, and the medium-sized OR prototype performs well across the metrics. Future research will consider the relative influence of several factors on traffic-based safety and efficiency performance metrics, resulting in a more predictive simulation design model.

The physical built environment has long been an area of interest for researchers and can have large impacts on occupants in terms of their satisfaction and productivity. This research thesis utilizes post-occupancy data in occupied buildings to examine the effects of the physical workstation environment and the broader building amenities on occupants. Multi-variate regression models were used to analyze the data, taking into account demographic and workstation factors, the physical workstation environment, and satisfaction with amenity features. While the explained variance in the regression models were generally small, the results showed significant effects of various demographic factors, workstation characteristics, and physical workstation parameters on components of occupant satisfaction. Analyses of satisfaction with the broader building amenities further illustrated that elements outside of the immediate workstation can influence occupant satisfaction, well-being, and organizational productivity.

Background The aim of the present paper is to construct an emulator of a complex biological system simulator using a machine learning approach. More specifically, the simulator is a patient-specific model that integrates metabolic, nutritional, and lifestyle data to predict the metabolic and inflammatory processes underlying the development of type-2 diabetes in absence of familiarity. Given the very high incidence of type-2 diabetes, the implementation of this predictive model on mobile devices could provide a useful instrument to assess the risk of the disease for aware individuals. The high computational cost of the developed model, being a mixture of agent-based and ordinary differential equations and providing a dynamic multivariate output, makes the simulator executable only on powerful workstations but not on mobile devices. Hence the need to implement an emulator with a reduced computational cost that can be executed on mobile devices to provide real-time self-monitoring. Results Similarly to our previous work, we propose an emulator based on a machine learning algorithm but here we consider a different approach which turn out to have better performances, indeed in terms of root mean square error we have an improvement of two order magnitude. We tested the proposed emulator on samples containing different number of simulated trajectories, and it turned out that the fitted trajectories are able to predict with high accuracy the entire dynamics of the simulator output variables. We apply the emulator to control the level of inflammation while leveraging on the nutritional input. Conclusion The proposed emulator can be implemented and executed on mobile health devices to perform quick-and-easy self-monitoring assessments.

Specific government regulations for waste products and increasing environmental awareness are concerns for companies. Disassembly operations have become essential tools for green manufacturing and for reducing ecological hazards from waste electrical and electronic equipment. An effective and efficient line design may be vital to encourage companies to establish a disassembly center. The line-balancing problem is a critical issue in a disassembly center. Large products may allow simultaneous disassembly of parts using more than one operator at a workstation. However, multi-manned disassembly line balancing creates a more complicated problem. Thus, an efficient solution technique based on a constraint programming (CP) approach is proposed for multi-manned disassembly line balancing with AND/OR precedence relations to minimize cycle time as a primary objective and the total number of workers as a secondary objective. A mixed-integer linear programming (MILP) model based on previous studies was proposed to define the problem. A CP approach was developed for the first time to solve this problem. A genetic algorithm was used to show the relative performance of the CP method for large problems. The proposed CP approach demonstrates superior performance.

BACKGROUND: In the 90s, digital human manikins (DHMs) were introduced in planning of workstations, by static or semi-static simulations. Modern DHMs can simulate dynamic work and offer a rapid way for a virtual pre-production ergonomic evaluation. Work-related musculoskeletal disorders may affect surgical performance and patient safety. A prototype of an open console, which is contrary to the conventional closed consoles and may be seen as a representative for a new generation, has been designed to reduce workload for robotic surgery surgeons. OBJECTIVE: The aim of this project was to test a new DHM tool with improved usability to evaluate the ergonomics of a console of a robotic surgical system in a pre-production stage. METHODS: The DHM tool IMMA was used together with a 3D model of the prototype console. Twelve manikins who represented females and males from two national populations were introduced. Manikin-console distances, after console adjustments per manikin, were compared with a US checklist and Swedish standard for VDU work. RESULTS: The DHM tool was useful for this case, but the distances of the checklist and the standard were needed to be obtained “manually”. The automatic functions of the DHM worked smoothly but were not optimized for VDU work. The prototype fulfilled most, but not all, of the ergonomic criteria of the checklist and the standard. CONCLUSIONS: There is room for improvements of the adjustable ranges of the console prototype. DHMs may facilitate rapid pre-production evaluation of workstations for static work; if ergonomic assessment models for VDU work are built-in, there may be a revival of DHMs in static work situations.

In a paced aircraft final assembly line, some disturbances can be collected timely on the basis of the cyber-physical production system. In order to reduce the execution deviation, some workers need to switch among stations after a fixed period. Thus, a worker allocation problem with the multistage workstation is introduced first. Then, an integer programming formulation is presented to formulate the problem with the objective of shortest workstation cycle and the workload balance of both stations and workers. Moreover, a modified nondominated sorting genetic algorithm (NSGA-IV) is proposed to solve it, which tradeoff the convergence and the population diversity in the decision space. Finally, the NSGA-IV algorithm compares with five multiobjective evolutionary algorithms in a real-world case. Compared with manual allocation, the takt time of an aircraft final assembly line is reduced by 20.86% by using the NSGA-IV algorithm.

The optimization of the distribution system is one of the most important operations for running an efficient power system. At the distribution stage, a wide variety of development frameworks are ac...

Manual operations are still playing a pivotal role in the performance of product-based industries due to the operator’s ability to flexible learning. The operators are doing various repetitive tasks in awkward postures. This causes upper body Musculoskeletal Disorders (MSDs), which critically affect the operator’s upper limb and lower back. So, this study is conducted to address the ergonomic aspects of manual operations to reduce the risk of upper body MSDs. Rapid upper limb assessment (RULA) and lower back analysis (LBA) are performed in JACK software to analyze the upper working posture and measure the forces acting on the L4/L5 spinal segment. The Taguchi experimental design approach was applied to optimize the workstation of an assembly line in the automotive industry to diminish forces and ANOVA to find the significance of design factors. Analysis of means (ANOM) and S/N ratios are conducted along with surface and contour plots. The results reveal that the upper working posture and forces acting are critical for the operator and roots upper body MSDs and thrilling fatigue. The outcomes recommend amending the design of the workstation. The Taguchi approach suggested optimum design, improving compression and Anterio-Posterior (AP) shear forces of 2.21 and 4.83%, respectively. The conveyor height has the most astonishing effect on compression and AP shear forces acting on the L4/L5 spinal segment with a contribution of 90.63 and 93.57%, respectively. The findings of this study make it easier for the industrial and managerial staff to perform an ergonomics evaluation for estimating the risk of MSDs. Further, the work can be extended to the dynamic posture analysis and to define exposure towards MSDs.

Pop is increasingly assimilating the compositional practices of hip-hop and EDM (electronic dance music). This shift is driven by a new generation of Digital Audio Workstations (DAWs). These are le...

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.

The contribution examines the acceptance of Augmented Reality (AR) in assembly scenarios by a model-based approach for acceptance evaluation. After a critical literature research and analysis, a proprietary model for acceptance measurement is developed, which includes and synthesizes previous models and simplifies them considerably for the purpose of industrial assembly. Consequently, a structural model is derived which is based on the basic concepts of the Unified Theory of Acceptance and Use of Technology (UTAUT) and Technology Acceptance Model (TAM). This is built up as a path model to explain user acceptance. Following, a laboratory experiment is set up to collect data. At the final assembly workstation of the FHWS c-Factory the study participants assemble a toy truck once without and once with AR support. The c-Factory is a concept factory for smart production in an IoT environment. Afterwards, relevant data are collected by means of a survey. The evaluation shows that the acceptance of AR is given and the model is resilient. The results show also, that AR is accepted by the participants supporting their work.

In manufacturing systems, mixed model assembly lines are used to produce different products to deal with the problem of customers’ demands variety, and minimizing the cycle time in such assembly line is a critical problem. This paper addresses the mixed model assembly line balancing problem type 2 that consists in finding the optimal cycle time for a given number of workstations. A hybrid Greedy randomized adaptive search procedure-Genetic algorithm is proposed to find the optimal assignment of tasks among workstations that minimize the cycle. A Ranked Positional Weight heuristic is used in the construction phase of the proposed GRASP, and in the local search phase, a neighborhood search procedure is used to ameliorate the constructed solutions in the construction phase. The GRASP is executed many times in order to seed the initial population of the proposed genetic algorithm, and the results of the executions are compared with the final solutions obtained by the hybrid GRASP-GA. In order to test the proposed approaches, a numerical example is used.

Surgeons must intraoperatively view cross-section images under sterilization conditions. Keyboard and computer mouse are sources of contamination. A computer vision algorithm and a hand movement pattern analysis technique have been applied to solve the problem based on surgeon’s behaviors. This paper proposed a new method to control the radiological image viewer in an operating room. A pattern code of hand movement and a grid square guideline are used. Our proposed algorithm comprises three steps: hand tracking, pattern code area identification, and hand movement pattern recognition. First, the system is fed with a sequence of three-dimensional data. A 3D camera captures the whole target body. A skeleton tracking algorithm is used to detect the human body. The left-hand joint in the skeleton data set is tracked. Second, as this algorithm supports one hand movement, a grid square guideline is defined. Hand movements are interpreted from the hand path moving in the grid square area. Finally, the pattern code is defined as a feature vector. By using the feature vector and closest point classifier, the hand movements are recognized by the K-Nearest Neighbors algorithm. To test the performance of the proposed algorithm, data from twenty subjects were used. Seven commands were used to interface with the computer workstation to control the radiological image viewer. The accuracy rate was 95.72%. The repeatability was 1.88. The advantage of this method is that one hand can control the image viewer software from a distance of 1.5 m satisfactorily without contacting computer devices. Our method also does not need big data set to train the system.

Moving target detection is involved in many engineering applications, but basketball has some difficulties because of the time-varying speed and uncertain path. The purpose of this paper is to use computer vision image analysis to identify the path and speed of a basketball goal, so as to meet the needs of recognition and achieve trajectory prediction. This research mainly discusses the basketball goal recognition method based on computer vision. In the research process, Kalman filter is used to improve the KCF tracking algorithm to track the basketball path. The algorithm of this research is based on MATLAB, so it can avoid the mixed programming of MATLAB and other languages and reduce the difficulty of interface design software. In the aspect of data acquisition, the extended EPROM is used to store user programs, and parallel interface chips (such as 8255A) can be configured in the system to output switch control signals and display and print operations. The automatic basketball bowling counter based on 8031 microprocessor is used as the host computer. After the level conversion by MAX232, it is connected with the RS232C serial port of PC, and the collected data is sent to the workstation recording the results. In order to consider the convenience of user operation, the GUI design of MATLAB is used to facilitate the exchange of information between users and computers so that users can see the competition results intuitively. The processing frame rate of the tested video image can reach 60 frames/second, more than 25 frames/second, which meet the real-time requirements of the system. The results show that the basketball goal recognition method used in this study has strong anti-interference ability and stable performance.

El presente trabajo describe una nueva versión del sistema AUDIX, diseñada como una estación de trabajo informatizada, para la audiometría objetiva y subjetiva. El sistema, esta integrado por un ordenador (PC) con una serie de programas de cómputo (“software”) el cual se conecta mediante una interfaz universal (universal serial bus USB) con un bloque electrónico especializado (“hardware”). El bloque electrónico tiene dos amplificadores bioeléctricos y un estimulador acústico digital totalmente programable con dos canales independientes. Esto permite generar de manera simultánea por ambos oídos, estímulos complejos diferentes (mezcla de tonos modulados en amplitud). Los estímulos acústicos pueden ser presentados a través de audiófonos (suprauriculares o de inserción), vibrador óseo y/o altavoces. El software programado sobre una plataforma Windows, tiene 5 módulos diferentes para la adquisición y análisis de PEA transientes y de estado estable, audiometría conductual, administración de base de datos y calibración. La base de datos del sistema permite almacenar, borrar, extraer, crear y realizar copias de respaldo. Durante la adquisición de los PEA se utilizan diferentes métodos estadísticos como indicadores para la detección objetiva de las respuestas. Puede visualizarse en forma concurrente la actividad bioeléctrica de base (monitoreo de EEG) y el resultado de la promediación (PEA). Los resultados del examen electroaudiométrico son analizados fuera de línea de una manera flexible, generándose múltiples reportes gráficos y permitiendo la comparación automática con datos normativos. En el caso de los PEAee los resultados pueden ser presentados en el formato estándar de un audiograma convencional utilizando diferentes escalas (dB: HL, SPL, nHL). El sistema AUDIX ha sido validado ampliamente en la práctica clínica resultando de utilidad para la detección temprana de las pérdidas auditivas y la caracterización precisa de la audición en toda la gama de frecuencias audibles.

The problem of designing advanced computing systems in the class of structures of integrated modular avionics is considered. The unified topology of the internal network of the computer on the basis of Space Wire exchange channels and variants of its execution for various onboard applications is offered. Equivalent reliability schemes of each of the specific structures are introduced and the probabilities of trouble-free operation of each structure are analyzed. Families of graphic dependencies are given. The analysis of the existing principles and algorithms for testing multiprocessor multimodal onboard digital computer systems is given; the new testing algorithm for the multiprocessor systems which follows the software design standards for products of integrated modular avionics is offered. The structure of the unified automated workplace for checking the functional modules of integrated modular avionics is considered. Specific requirements inherent in the workplaces for testing integrated avionics are identified: an increased level of control of the hardware component of products; the ability to simulate the failure state of individual components of avionics to check the mode of reconfiguration of the computer system; modular construction of software with the division of verification tests into components performed at the level of each CPM and the computer as a whole in single-task and multitasking modes; openness of architecture of a workplace, which provides an ability to change the level of control complexity of a product and control of one class of complexity; intra-project unification of both hardware and software of the workstation of the inspection.

This article studies the scheduling problem for a remanufacturing system with parallel disassembly workstations, parallel flow-shop-type reprocessing lines and parallel reassembly workstations. The problem is formulated as a multi-objective optimization problem which contains both energy consumption and makespan to be addressed using an improved multi-objective invasive weed optimization (MOIWO) algorithm. Two vectors regarding workstation assignment and operation scheduling jointly form a solution. A hybrid initialization strategy is utilized to improve the solution quality and the Sigma method is adopted to rate each solution. A novel seed spatial dispersal mechanism is introduced and four designed mutation operations cooperate to enhance search ability. A group of numerical experiments and a practical case involving the disassembly of transmission devices are carried out and the results validate the effectiveness of the MOIWO algorithm for the considered problem compared with existing methods.

Background As humanity plans for crewed long-duration missions to Moon bases, Mars, and beyond, astronauts will need more autonomy via training and hardware to deal with medical emergencies. Significant communication delays and long evacuation distances mean a surgical workstation will be a necessity on a spacecraft and could save lives. The aim of this study was to assess the feasibility and design of such a microgravity surgical workstation. Methods This research was conducted using two main approaches: a thorough literature review to summarise current knowledge and inform the enclosure design; and concurrently an iterative process to engineer a workstation design proposal. To the best of our knowledge, a similar surgical enclosure has never been investigated and few containment solutions have been tested in parabolic flight. This study proposes the design of a Crew Operating Microgravity Theatre Enclosure (COMTE), which has been shaped by conclusions from parabolic animal surgery experiments and direct feedback from space medicine experts and astronauts. Results A full technical characterisation of the proposed design is included in this paper, and a prototype was constructed. The defining principle of the COMTE ‘glovebox’ or sealed enclosure was to use unique fluid capillary edge-effects in microgravity to contain surgical fluids and blood during an operation. This aims to improve operator visualisation of the surgical field, whilst ensuring safety through maintaining a sterile surgical site with clear plastic and preventing contamination of the closed-loop spacecraft atmosphere. Additionally, the proposed design includes extensive research on weight, volume, and power requirements, and has been reviewed by external experts. Conclusions This engineering research not only safeguards astronauts but could present a unique solution to terrestrial surgery in remote and extreme environments. In conclusion, this paper proposes a novel engineering solution to the problem of safe and efficient surgery in space, and further work on the design will lead to both ground and parabolic testing.

Algoritma kriptografi RSA menjadi metode yang paling sulit diretas karena kerumitan persamaan matematis yang digunakan. Semakin rumit persamaan matematis yang digunakan, semakin besar pula daya komputasi yang digunakan untuk memproses algoritma tersebut. Penggunaan Single-Board Computer (SBC) mulai digunakan untuk menggantikan alat pemrosesan komputasi seperti komputer personal baik berupa laptop maupun workstation. Penetlitian ini bertujuan untuk mengetahui hasil optimasi pemroresan enkirpsi dan dekripsi RSA menggunakan SBC yang tersusun sebagai bentuk cluster. Metode yang digunakan adalah metode pemrosesan enkripsi dan dekripsi RSA dengan pembagian beban komputasi yang diterapkan dalam arsitektur SBC berdasarkan ketersediaan sumberdaya pada tiap SBC dalam cluster SBC. Cluster SBC yang dibangun terdiri atas 5 buah SBC Raspberry Pi 4 model B yang terkoneksi melalui sebuah switch 8 port. Hasil penelitian yang didapat adalah proses enkripsi dan dekripsi pada cluster SBC dapat mengalahkan komputer tunggal. Cluster SBC yang memiliki 16 core dari 4 buah prosesor worker SBC berjalan lebih cepat dibandingkan komputer tunggal yang memiliki 4 core dari prosesornya. Selain itu, efisiensi juga didapat dari biaya yang dikeluarkan untuk membeli perangkat. Dengan biaya pembelian yang sama, performa yang didapat lebih tinggi pada cluster SBC sehingga SBC dapat dijadikan alternatif pemrosesan enkripsi dan dekripsi.

In, the recent scenario, the utilization of robots in different areas such as packaging, loading/unloading, transportation, and especially assembly lines enhance the productivity of production systems. The increasing interest of customers in customized products and full fill customer demand within time is a challenge for the companies to balance and configure their robotic assembly line more efficient and effective than ever before. Robotic two-sided assembly line balancing problem (RTALBP) generally occurs in plants producing high volume, large-sized products, where there is a process of installing more than one robot on every single station of the assembly line for manufacturing the product. The main aim of this paper is to develop a new mathematical model with the objective of workload maximization on each workstation that directly minimizes the number of workstations when cycle time is fixed. Robotic two-sided assembly line balancing problem is well known NP-hard problem that’s why an exact solution approach is proposed to solve the problem. In this paper, real-life assembly line balancing based production case study data is collected, and a proposed mathematical model is applied to get a feasible solution. Benchmark problem and production case study problem is solved using a branch and bound algorithm on Lingo 16 solver. Computational results indicated proper allocation of robots and reduce the number of robots which indirectly increased efficiency and save cost and space for assembling the products.

This study proposes a decision model to solve a workstation problem in the footwear industry by considering multiple conflicting objectives that influence the decision-making process. Following the appearance of employee reports of pain symptoms and due to limited resources and the need to protect health, companies strive to improve working conditions. Ranking workstations for ergonomics interventions may help if an appropriate decision is made through a well-structured decision-making process. Accordingly, the association of two Problem Structuring Methods (PSMs), Value Focused-thinking (VFT), and Strategic Options Development and Analysis (SODA) were used to structure a hierarchy of key objectives for evaluating the decision model. Preference modeling with the Decision Maker was conducted in a flexible and interactive manner, aided by the Flexible and Interactive Tradeoff Method (FITradeoff). Partial information was gathered about the preferences of the Decision Maker that lead to finding a recommendation that less cognitive effort is required. Decision Maker answered 10 questions and the method found six levels of ordering, indicating FITradeoff method is effective for rank workstations for ergonomic interventions. It was concluded that the combination of the structuring methods VFT and SODA, and the multicriteria method FITradeoff facilitates ergonomic decision-making.

ECMA-74 Annex C.15 prescribes procedures for acoustical testing of personal computers and workstations. The dramatic advances in computer technology and use over the past two decades motivated the formation of an IT industry workgroup shortly after InterNoise 2018 to update the annex for these changes. The updated procedures, which will be published in the 18th edition of ECMA-74, are described. The updated procedures comprise new operating conditions: 1) web browsing, 2) office productivity, 3) media content creation, and 4) power user/gaming, in addition to the idle condition, and how computer system power and performance settings, which affect computer noise, are to be set and reported.

Software simulators play a critical role in the development of new algorithms and system architectures in any field of engineering. Neuromorphic computing, which has shown potential in building brain-inspired energy-efficient hardware, suffers a slow-down in the development cycle due to a lack of flexible and easy-to-use simulators of either neuromorphic hardware itself or of spiking neural networks (SNNs), the type of neural network computation executed on most neuromorphic systems. While there are several openly available neuromorphic or SNN simulation packages developed by a variety of research groups, they have mostly targeted computational neuroscience simulations, and only a few have targeted small-scale machine learning tasks with SNNs. Evaluations or comparisons of these simulators have often targeted computational neuroscience-style workloads. In this work, we seek to evaluate the performance of several publicly available SNN simulators with respect to non-computational neuroscience workloads, in terms of speed, flexibility, and scalability. We evaluate the performance of the NEST, Brian2, Brian2GeNN, BindsNET and Nengo packages under a common front-end neuromorphic framework. Our evaluation tasks include a variety of different network architectures and workload types to mimic the computation common in different algorithms, including feed-forward network inference, genetic algorithms, and reservoir computing. We also study the scalability of each of these simulators when running on different computing hardware, from single core CPU workstations to multi-node supercomputers. Our results show that the BindsNET simulator has the best speed and scalability for most of the SNN workloads (sparse, dense, and layered SNN architectures) on a single core CPU. However, when comparing the simulators leveraging the GPU capabilities, Brian2GeNN outperforms the others for these workloads in terms of scalability. NEST performs the best for small sparse networks and is also the most flexible simulator in terms of reconfiguration capability NEST shows a speedup of at least 2 × compared to the other packages when running evolutionary algorithms for SNNs. The multi-node and multi-thread capabilities of NEST show at least 2 × speedup compared to the rest of the simulators (single core CPU or GPU based simulators) for large and sparse networks. We conclude our work by providing a set of recommendations on the suitability of employing these simulators for different tasks and scales of operations. We also present the characteristics for a future generic ideal SNN simulator for different neuromorphic computing workloads.

Advanced visualization of medical imaging has been a motive for research due to its value for disease analysis, surgical planning, and academical training. More recently, attention has been turning toward mixed reality as a means to deliver more interactive and realistic medical experiences. However, there are still many limitations to the use of virtual reality for specific scenarios. Our intent is to study the current usage of this technology and assess the potential of related development tools for clinical contexts. This paper focuses on virtual reality as an alternative to today’s majority of slice-based medical analysis workstations, bringing more immersive three-dimensional experiences that could help in cross-slice analysis. We determine the key features a virtual reality software should support and present today’s software tools and frameworks for researchers that intend to work on immersive medical imaging visualization. Such solutions are assessed to understand their ability to address existing challenges of the field. It was understood that most development frameworks rely on well-established toolkits specialized for healthcare and standard data formats such as DICOM. Also, game engines prove to be adequate means of combining software modules for improved results. Virtual reality seems to remain a promising technology for medical analysis but has not yet achieved its true potential. Our results suggest that prerequisites such as real-time performance and minimum latency pose the greatest limitations for clinical adoption and need to be addressed. There is also a need for further research comparing mixed realities and currently used technologies.

PurposeDue to the market trend of low-volume and high-variety, the manufacturing industry is paying close attention to improve the ability to hedge against variability. Therefore, in this paper the assembly line with limited resources is balanced in a robust way that has good performance under all possible scenarios. The proposed model allows decision makers to minimize a posteriori regret of the selected choice and hedge against the high cost caused by variability.Design/methodology/approachA generalized resource-constrained assembly line balancing problem (GRCALBP) with an interval data of task times is modeled and the objective is to find an assignment of tasks and resources to the workstations such that the maximum regret among all the possible scenarios is minimized. To properly solve the problem, the regret evaluation, an exact solution method and an enhanced meta-heuristic algorithm, Whale Optimization Algorithm, are proposed and analyzed. A problem-specific coding scheme and search mechanisms are incorporated.FindingsTheory analysis and computational experiments are conducted to evaluated the proposed methods and their superiority. Satisfactory results show that the constraint generation technique-based exact method can efficiently solve instances of moderate size to optimality, and the performance of WOA is enhanced due to the modified searching strategy.Originality/valueFor the first time a minmax regret model is considered in a resource-constrained assembly line balancing problem. The traditional Whale Optimization Algorithm is modified to overcome the inferior capability and applied in discrete and constrained assembly line balancing problems.

Industry 4.0 paradigm has introduced a set of technological advances into the productive means. However, the training of the operators is somehow neglected. An operator without the necessary skills will take risks or will provoke problems that might appear at any point of the productive process. Therefore, training the operators is required to acquire the necessary skills to interact with the machines in the most productive and safest way possible. Virtual Reality (VR) is a good option to train people. However, the development of a VR system is usually expensive and slow due to the 3D design process and the creation and edition of VR training sessions. This paper presents a methodology to develop VR tutorials and training courses for professional preparation in industrial jobs, providing usable virtual tools to solve the following problems: i) how to create of the virtual model of workstations by its 3D reconstruction, ii) how to apply the expected behavior to the 3D models, and iii) how to prepare online tutorials and train workers in the virtual environment.

This study addresses a dynamic lot-sizing problem for remanufacturing systems in which end-of-use/life products are disassembled into their parts on a single disassembly workstation and then each p...

To reduce the disassembly costs to enterprises and improve the disassembly efficiency of waste products, this study proposed a partial sequence-dependent disassembly line balancing problem (PSD-DLBP) and established a multi-objective mathematical model to simultaneously minimize the number of workstations, total disassembly time, idle balance index and the number of disassembly tools. Then, a Pareto-discrete hummingbird algorithm (PDHA) was proposed to address PSD-DLBP effectively. The PDHA includes two stages: self-searching stage and information-interacting stage. With these two stages, the exploration and exploitation abilities of PDHA can be balanced. Later, the effectiveness and superiority of the PDHA were verified by comparing it with the other four algorithms for two different-scale examples. Finally, the model and PDHA were applied to the optimization of a partial sequence-dependent disassembly line of waste laptops. The optimization results show that the partial disassembly can make the line smoother and the utilization efficiency of workstations higher than full disassembly, and PDHA is superior in solving the PSD-DLBP.

A partir del avance de las nuevas tecnologías, las redes de computadoras han mantenido una tendencia al desarrollo ascendente a nivel global. De manera general las organizaciones cada vez se benefician en mayor medida con la implementación de estas redes en sus entornos, debido a la probada eficiencia y mejoras en la comunicación y el flujo de desarrollo de los procesos que llevan a cabo. En la empresa TECNOIMPORT, se ha definido diseñar e implementar una red LAN, que posibilite conectar las estaciones de trabajo de la institución. En el presente trabajo se realiza una propuesta de diseño a partir del análisis de las características y necesidades particulares de la entidad. Para llevar a cabo esta propuesta se definen los diferentes elementos a tener en cuenta, de acuerdo a metodologías ampliamente utilizadas en el diseño e implementación de redes de computadoras.

We consider the problem of low-rank approximation of massive dense nonnegative tensor data, for example, to discover latent patterns in video and imaging applications. As the size of data sets grows, single workstations are hitting bottlenecks in both computation time and available memory. We propose a distributed-memory parallel computing solution to handle massive data sets, loading the input data across the memories of multiple nodes, and performing efficient and scalable parallel algorithms to compute the low-rank approximation. We present a software package called Parallel Low-rank Approximation with Nonnegativity Constraints, which implements our solution and allows for extension in terms of data (dense or sparse, matrices or tensors of any order), algorithm (e.g., from multiplicative updating techniques to alternating direction method of multipliers), and architecture (we exploit GPUs to accelerate the computation in this work). We describe our parallel distributions and algorithms, which are careful to avoid unnecessary communication and computation, show how to extend the software to include new algorithms and/or constraints, and report efficiency and scalability results for both synthetic and real-world data sets.

This work proposes a Value Stream Mapping (VSM) to be used in manufacturing industry that combines Lean, Energy and Six-Sigma methodologies. Lean's VSM tool is amended to energy VSM so that the value-added and non-value-added approach can be used to determine the energy use and waste. In order to identify the maximum rejection or rework at a workstation, an entropy-based mathematical model is developed and a Lean-Energy-Six Sigma Value Stream Mapping (LESSVSM) is presented. The model can be used in manufacturing at product level where temperature and energy can be measured from input to output. The model has been implemented on a manufacturing system containing four workstations. The proposed LESSVSM model will help to industry to become more sustainable as it can minimize energy and waste in the case of rework and rejection. This study presents a systematic approach which researchers and practitioners can apply for sustainable manufacturing.

Flexible Manufacturing System (FMS) is one of the modern production systems that support the implementation of Industry 4.0. An educational institution plans to build an FMS model for learning the modern production systems. The FMS is a manufacturing system consisting of a set of automatic workstations connected to a material handling system where all activities are controlled by a computer system. The material handling system consists of a material storage system and a transportation system, one example of a transportation system is the stacker crane. In this research, the stacker crane model has been built which consists of three main components, which are the bottom frame, the mast, and the carriage. This component is equipped with stepper motors, leadscrews that are controlled by the micro controller and an application on Android. The stacker crane model is tested to retrieve and deliver the stereofoam material model to the destination which is controlled by the user using an application on Android. The characteristics of the stacker crane model can move the workpiece with a maximum error of 2 mm in the positive x-axis direction, 2 mm in the negative x-axis movement, up to 2 mm positive y-axis, downward at negative y-axis direction 2 mm.

Goal: This research aims to examine the trade-off behaviour between productivity, quality and maintenance performance and evaluate the efficiency of the framework integrated to a time variability in operational management. Design / Methodology / Approach: The proposed framework integrates a stochastic analysis of process and TVM to manage process variability and analyse the trade-off behaviour between quality, productivity, and maintenance efficiency. The framework generates a control chart for each workstation and analyses the operator's time to execute an assembly process for six workstations. The processes are characterised and evaluated via stochastic simulation, resulting in a trade-off analysis with a multicriteria approach. Results: A relational graphic of performance dimensions shows that productivity and maintenance performance have a high dependency on time variability management, whereas quality has a minor impact over trade-off decisions. The proposed framework has a huge significance to operational management which allow to apply complex models to time variability analysis and organisation performance. Limitations of the investigation: The trade-off analysis in this study is limited to a constant trade-off model to validate the framework. Practical implications: This framework, used in association with traditional management philosophies, is a powerful tool that permits managers to develop a trade-off analysis and make decisions on workstations. Thus, a research field that correlates time variability with performance dimensions may be validated by this framework. Originality / Value: A framework that allows the use of MCDM to analyse the trade-off behaviour on organization performance and a trade-off analysis between performance dimensions and time variability management in operational performance.

A flexible manufacturing system (FMS) is the model used for the system produced in the manufacturing industry, and it consists of the number of interconnected workstation. Inflexible manufacturing system scheduling of jobs has become a serious problem, even for a short breakdown of the machine and for the unexpected arrival of the product. To overcome this problem, a flexible manufacturing system using fuzzy rules is proposed. In this proposed model, four input variables are considered: (1) machine allocated processing time; (2) priority of the machine; (3) priority of the due date; and (4) priority of the setup time. The priority based on the job is the fuzzy variable, which shows the status of the job, based on which the next job will be selected for the processing in the machine. In this model, the machine will be selected first, and then, the scheduling is done based on the multi-criteria scheduling system. The obtained results are compared with the existing system and from the results. The improved scheduling strategy provides better results for the scheduling problem.

Diagnosis on the basis of a computerized acoustic examination may play an incredibly important role in early diagnosis and in monitoring and even improving effective pathological speech diagnostics. Various acoustic metrics test the health of the voice. The precision of these parameters also has to do with algorithms for the detection of speech noise. The idea is to detect the disease pathology from the voice. First, we apply the feature extraction on the SVD dataset. After the feature extraction, the system input goes into the 27 neuronal layer neural networks that are convolutional and recurrent neural network. We divided the dataset into training and testing, and after 10 k-fold validation, the reported accuracies of CNN and RNN are 87.11% and 86.52%, respectively. A 10-fold cross-validation is used to evaluate the performance of the classifier. On a Linux workstation with one NVidia Titan X GPU, program code was written in Python using the TensorFlow package.

The obligation to use resources in an optimal way in production lines requires industrials to use the tools and methods of operational research and to mathematically model their resource allocation problems in order to find optimal configurations of their assembly lines. The objective of this paper is the implementation of a decision support tool to help manage and optimize the allocation of material resources of companies during the product launch phase. This tool must be able to be used at several levels: strategic and operational. The assembly lines balancing problem, which we study in this article, is distinguished by its configuration (constraint and hypothesis) related to the business environment studied, finally, for the resolution of the problem we made an analogy with the bin packing problem and then proposed a solution adapted to our case study.

In today's manufacturing settings, a sudden increase in the customer demand may enforce manufacturers to alter their manufacturing systems either by adding new resources or changing the layout within a restricted time frame. Without an appropriate strategy to handle this transition to higher volume, manufacturers risk losing their market competitiveness. The subjective experience-based ad-hoc procedures existing in the industrial domain are insufficient to support the transition to a higher volume, thereby necessitating a new approach where the scale-up can be realised in a timely, systematic manner. This research study aims to fulfill this gap by proposing a novel Data-Driven Scale-up Model, known as DDSM, that builds upon kinematic and Discrete-Event Simulation (DES) models. These models are further enhanced by historical production data and knowledge representation techniques. The DDSM approach identifies the near-optimal production system configurations that meet the new customer demand using an iterative design process across two distinct levels, namely the workstation and system levels. At the workstation level, a set of potential workstation configurations are identified by utilising the knowledge mapping between product, process, resource and resource attribute domains. Workstation design data of selected configurations are streamlined into a common data model that is accessed at the system level where DES software and a multi-objective Genetic Algorithm (GA) are used to support decision-making activities by identifying potential system configurations that provide optimum scale-up Key Performance Indicators (KPIs). For the optimisation study, two conflicting objectives: scale-up cost and production throughput are considered. The approach is employed in a battery module assembly pilot line that requires structural modifications to meet the surge in the demand of electric vehicle powertrains. The pilot line is located at the Warwick Manufacturing Group, University of Warwick, where the production data is captured to initiate and validate the workstation models. Conclusively, it is ascertained by experts that the approach is found useful to support the selection of suitable system configuration and design with significant savings in time, cost and effort.

BACKGROUND: Robots communicate with the physical world program with the mechanic’s simulations. They recommend that people-to-people robotics will prepare for cognitive models. Presently, there is a considerable concern for greater flexibility and efficiency in the scope of human-robot interfacing collaboration across hospitals. Nevertheless, interfacing is still in its infancy in manufacturing; industrial practitioners have many questions and doubts about the efficiency of the device and the health of human operators. OBJECTIVES: Therefore, research on processes and methods of design is required to ensure that the intended human-computer interaction-based workstations effectively meet system performance, human safety, and ergonomics standards for realistic applications. This study provides a design process for a workstation appropriate for occupational health and safety. This article outlines the perspectives learned from incorporation into the preparation and operation of robotics of digital cognitive models. RESULTS: This ends with an overarching game-theoretical model of contact and analyses how different approaches contribute to effective communicating activities for the robot in its interaction with people. CONCLUSION: The new feature of this design process is the approach for testing alternative workstation designs, taking into account efficiency and safety features with computer simulations.

In the manufacturing company, an efficient production floor affects the productivity of the company. Thus, a well design production floor layout assists the company to achieve its objectives. In this regard, this study aims to design a new alternative production floor layout for the XYZ manufacturing company. The company facing the facility layout problem (FLP) where their workstation on the production floor was not located based on the activity-relationship. Thus, the company struggles to reduce the distance travel of their workers from one station to another by re-layout their production floor. The Systematic Layout Planning (SLP) method was used to determine the best new alternative layout for the company. Subsequently, the AnyLogic simulation software was utilized to test the effectiveness of the layout by using the number of steps as the parameter. As a result, it is found that the total number of steps of workers in the production floor can be reduced from 16,554 steps (in existing layout) to 15,956 steps (in new alternative layout).

Facing the increasingly competitive market environment, assembly lines are gained attention because of the assembly process expenditure consumes more than 20 % of the manufacturing cost, and also improve its products to meet demand. In this paper, an attempt has been made to develop worker-task assigned to workstation heuristic (W-TAWH) approach for solving mixed-model assembly line balancing problem (M-MALBP), in which the assembly tasks have to be assigned to workstations, and each workstation needs to select only one of the available operators to perform the assigned tasks corresponding to the straight and U-shaped assembly lines with the objective minimum cycle time. The performance of the developed approach was evaluated and validated through applying the practical case in the Dayla State Company for Electrical Industries (DSCEI) particularly in the electric transformer factory (ETF). Taguchi method was used to evaluate the contribution of each one of the considerations in the assembly line are solution approach, layout, sequence vector (SV), and workstation numbers. All results proved the stated considerations have impact significant in any trying to re-balance the assembly line.

Industrial collaborative robotics is an enabling technology and one of the main drivers of Industry 4.0 in industrial assembly. It allows a safe physical and human-machine interaction with the aim of improving flexibility, operator’s work conditions, and process performance at the same time. In this regard, collaborative assembly is one of the most interesting and useful applications of human-robot collaboration. Most of these systems arise from the re-design of existing manual assembly workstations. As a consequence, manufacturing companies need support for an efficient implementation of these systems. This work presents a systematical methodology for the design of human-centered and collaborative assembly systems starting from manual assembly workstations. In particular, it proposes a method for task scheduling identifying the optimal assembly cycle by considering the product and process main features as well as a given task allocation between the human and the robot. The use of the proposed methodology has been tested and validated in an industrial case study related to the assembly of a touch-screen cash register. Results show how the new assembly cycle allows a remarkable time reduction with respect to the manual cycle and a promising value in terms of payback period.

This work studies a two-stage hybrid flowshop problem with secondary resources (workers). The goal is to minimise the average tardiness. The workers are assigned to the workstations by time buckets...