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Collaborative robots, or cobots, offer a unique combination of productivity and flexibility that has led to significant growth in adoption over the past decade. Moreover, recently, there has been a shift towards a human-centered design of the workspace, known as one of the drivers of Industry 5.0, which prioritizes the well-being of operators. To achieve this, various human factors such as ergonomics, mental workload, personal skills, and capabilities need to be considered in the workspace design, and their impact on system productivity must be evaluated. The integration of a human and a cobot in the same workplace can affect the performance of the human operator, as the perception of the cobot can impact their work. This highlights the importance of taking human factors into account, as a lack of consideration in these aspects has contributed to the failure of many implementations. To link the objectives of productivity, flexibility, and human factors consideration, a dynamic real-time multi-objective task allocation strategy for collaborative assembly systems is developed. This approach considers the different characteristics of the resources and optimizes for two objectives, makespan, and energy expenditure of the operator. By using this approach, it is possible to modify the behavior of the cobot by reallocating tasks between the two resources based on the operator's current needs. In other words, if the operator appears too stressed due to time constraints or their energy rate level is too high, some of their assigned tasks can be transferred to the cobot. This helps to maintain a balanced system while reducing the operator's stress. [ABSTRACT FROM AUTHOR]

New technologies, such as collaborative robots, are an option to improve productivity and flexibility in assembly systems. Task allocation is fundamental to properly assign the available resources. However, safety is usually not considered in the task allocation for assembly systems, even if it is fundamental to ensure the safety of human operator when he/she is working with the cobot. Hence, a model that considers safety as a constraint is here presented, with the aim to both maximize the productivity in a collaborative workcell and to promote a secure human robot collaboration. Indexes that consider both process and product characteristics are considered to evaluate the quality of the proposed model, which is also compared with one without the safety constraint. The results confirm the validity and necessity of the newly proposed method, which ensures the safety of the operator while improving the performance of the system. [ABSTRACT FROM AUTHOR]

Industry 4.0 focuses on the realization of smart manufacturing based on cyber-physical systems (CPS). However, emerging Industry 5.0 and Society 5.0 reaches beyond CPS and covers the entire value chain of manufacturing, and faces economic, environmental, and social challenges. To meet such challenges, we regard Industry 5.0 as a socio-technical revolution based on the socio-cyber-physical system (SCPS), and propose a socio-technically enhanced wisdom manufacturing architecture and framework beyond CPS-based Industry 4.0/smart manufacturing with especially concerning transition enabling technologies such as artificial intelligence, social Internet of Things (SIoT), big data, machine learning, edge computing, social computing, 3D printing, blockchains, digital twins, and cobots. Finally we address the roadmap to blockchainized value-added SCPS-based Industrial Metaverse for Industry/Society 5.0, which will achieve high utilization of resources and provide products and services to satisfy experience-driven individual needs via metamanufacturing cloud services towards smart, resilient, sustainable, and human-centric solutions. [ABSTRACT FROM AUTHOR]

This document is a summary of a special issue in the Journal of Intelligent Manufacturing titled "Intelligent cobot systems: human-cobot collaboration in manufacturing." The special issue includes 10 papers that cover various aspects of cobot systems design and management from a human perspective. Topics covered include adaptive safety constraints, augmented reality programming, task allocation, human-robot collaboration disassembly, role transitions and adaptation, intelligent assistance systems, fault detection and diagnostics, automated visual inspection, and intelligent digital twins. The papers highlight the advantages and challenges of cobot systems in manufacturing and provide insights for future research. The authors of the document are Maurizio Faccio and Yuval Cohen. [Extracted from the article]

The migration from Industry 4.0 to Industry 5.0 is becoming more relevant nowadays, with a consequent increase in interest in the operators' wellness in their working environment. In modern industry, there are different activities that require the flexibility of human operators in performing different tasks, while some others can be performed by collaborative robots (cobots), which promote a fair division of the tasks among the resources in industrial applications. Initially, these robots were used to increase productivity, in particular in assembly systems; currently, new goals have been introduced, such as reducing operator's fatigue, so that he/she can be more effective in the tasks that require his/her flexibility. For this purpose, a model that aims to realize a multi-objective optimization for task allocation is here proposed. It includes makespan minimization, but also the operator's energy expenditure and average mental workload reduction. The first objective is to reach the required high productivity standards, while the latter is to realize a human-centered workplace, as required by the Industry 5.0 paradigms. A method for average mental workload evaluation in the entire assembly process and a new constraint, related to resources' idleness, are here suggested, together with the evaluation of the methodology in a real case study. The results show that it is possible to combine all these elements finding a procedure to define the optimal task allocation that improves the performance of the systems, both for efficiency and for workers' well-being. [ABSTRACT FROM AUTHOR]

Collaborative robots are increasingly common in modern production systems, since they allow to merge the productivity of automated systems with the flexibility and dexterity of manual ones. The direct interaction between the human and the robot can be the greatest advantage and the greatest limit of collaborative systems at the same time, depending on how it affects human factors like ergonomics and mental stress. This work presents an overview of collaborative robotics considering three main dimensions: robot features, modern production systems characteristics and human factors. A literature review on how such dimensions interact is addressed and a discussion on the current state of the art is presented, showing the topics that have been already widely explored and the research gaps that should be fulfilled in the future. [ABSTRACT FROM AUTHOR]

Collaborative robots can be a proper solution to improve the throughput of manual systems without reducing their flexibility. To effectively use cobots in productive systems, it is fundamental to develop a suitable task allocation model that considers collaboration. Hence, we present a model for collaborative assembly line balancing (C-ALB) which considers paralleling tasks and collaboration in the balancing resolution. Indexes that take into account both the product and process characteristics are defined to evaluate the quality of the proposed task allocation model and comparing it to others. The results confirm the influence of the product characteristics on the system performance, leading to the definition of a new paradigm for product design. [ABSTRACT FROM AUTHOR]

In this article, an experimental study of a wind turbine in a wind tunnel is performed. The objective has been to present a novel analytical computational fluid dynamics (CFD)-based approach through considering the residual levels of the mass and momentum parameters under effect of different air flow characteristics surrounding the wind turbine, which have an effect on the power losses, turbine's performance and the economic viability. The involved decision variables are considered to be the wind velocity, the pressure and the turbulence. Evaluation of the convergence showed that the residual level for the maximum method is estimated to be approximately 10–1 to 10–3 times higher than the root mean square. Results also concluded that between two studied turbulence models, the turbulence eddy frequency is found to be more efficient compared with turbulence kinetic energy. In higher iterations compared with the initial iterations, a significant difference between the pressure and the Cartesian velocity components has occurred and the residual level of the velocity components indicated a more efficient convergence compared with the pressure. The overall environmental analysis concluded that on the basis of the CFD residual values, it would be possible to adequately determine the CFD efficiency of the wind energy system in a wind tunnel. It has been demonstrated that, among different decision variables, velocity components of the mass and momentum parameters and the turbulence eddy frequency were determined to produce further accurate results in comparison with the pressure and the turbulence kinetic energy. [ABSTRACT FROM AUTHOR]

In the last decade, collaborative assembly systems (CAS) are becoming increasingly common due to their ability to merge the flexibility of a manual assembly system with the performance of traditional robotics. Technical constraints, e.g., dedicated tools or resources, or performance requirements, e.g., throughput, could encourage the use of a CAS built around a multi-robot and multi-operator layout, i.e., with a number of resources greater than 2. Starting from the development of a prototype multi-robot multi-operator collaborative workcell, a simulation environment was developed to evaluate the makespan and the degree of collaboration in multi-robot multi-operator CAS. From the simulation environment, a mathematical model was conceptualized. The presented model allows estimating, with a certain degree of accuracy, the performances of the system. The results have investigated how several process characteristics, i.e. the number and type of resources, the resources layout, the task allocation method, and the number of feeding devices, influence the degree of collaboration between the resources. Lastly, the authors propose a compact analytic formulation, based on an exponential function, and define the methods and the influence factors to determine its parameters. [ABSTRACT FROM AUTHOR]

Recently, the need for assembly systems of better following the market demand has led to the spread of alternative solutions with respect to the traditional fixed worker strategy. Walking worker systems, where operators move across the line to produce the finished product, are gaining always more interest. In this paper, a comparison between the fixed worker (FW) and the walking worker (WW) assembly strategies is provided, by taking into account their differences both in terms of performed activities during assembly and of material exposure at the assembly workstations. The evaluation is carried out through the proposal of a mathematical model, to understand the impact on assembly time and on operators' energy expenditure. The behavior of the model is investigated both with a parametric analysis and a real case study. The results show that the FW is the best one when the system is working at its maximum throughput, while the WW strategy turns out to be preferable for the lower values of market demand, both from a time and an energy expenditure perspective. [ABSTRACT FROM AUTHOR]

Collaborative assembly systems (CAS) are an increasingly important solution to the requests of the current market since they present the flexibility and dexterity of the human operator and the repeatability of the robot. For a CAS to be effective, both agents should carry out the tasks in the workspace without any physical interference. This paper aims to evaluate how the product characteristics influence the interference between the human operator and the robot. To reach the goal, we developed an algorithm that simulates product assembly in the considered workspace. The model also allowed to estimate the makespan achievable for different scenarios, showing a reduction, and thus an increase in the throughput. The makespan depends on several variables, related to the product characteristics and the process ones. Given specific conditions, we have observed that increasing the collaboration parameter from 21.06 to 48.98% led to a reduction in the makespan of about 20%. Lastly, the results obtained by the simulation were verified through a validation test, showing an error of − 2.39%. [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]

The novel generation of production facilities fostered by the fourth industrial revolution widely adopts different technologies to digitalise the manufacturing and assembly processes. In this context, work measurement techniques are one of the main candidates for the application of these new technologies because of the time, cost, and competences required to analyse manual production activities and considering the limited precision of the traditional approaches. This paper proposes a new hardware/software architecture devoted to the motion and time analysis of the activities performed by human operators within whatsoever industrial workplace. This architecture, called Human Factor Analyser (HFA), is constituted by a network of ad hoc depth cameras able to track the worker movements during the task execution without any interference with the monitored process. The data provided by these cameras are then elaborated in a post-process phase by the HFA to automatically and quantitatively measure the work content of the considered activities through an accurate motion and time analysis. The developed architecture evaluates the worker in a 3D environment considering his interaction with the industrial workplace through the definition of appropriate control volumes within the layout. To test the accuracy of HFA, an extensive experimental campaign is performed at the Bologna University Laboratory for Industrial Production adopting several realistic industrial configurations (different workplaces, operators and tasks). Finally, the HFA is applied to a real manufacturing case study of an Italian company producing refrigerator metal grates. A wide and deep analysis of the obtained key results is presented and discussed. [ABSTRACT FROM AUTHOR]

In the last decade, robot manufacturers have started to produce collaborative industrial robots, that can work while safely sharing the workspace with a human operator. In this way, robot repeatability, combined with human dexterity, can move automated assembly to a new level of flexibility. The aim of this paper is to investigate the conditions at which such systems, called collaborative assembly systems (CAS), can be better performing than the traditional manual or automated assembly systems. Throughput and unit direct production cost are considered for the comparison. The estimation of such performance figures, which is straightforward in traditional automated assembly systems, becomes more complex in the case of collaborative systems. In fact, both task allocation between the human and the robot, and the way they collaborate/interfere with each other during assembly, affect the throughput of CAS. With the aim of taking into account such parameters, we introduce a set of system variables and a mathematical model which allow to estimate the real convenience of the implementation of CAS in the industrial scenario. In the paper, the model is applied to compare CAS to manual assembly and to noncollaborative automated assembly, both with parameters derived from the literature and in a case study. Finally, a set of implementation conditions is derived, related to the task allocation that maximises CAS performance. [ABSTRACT FROM AUTHOR]

Non-traditional warehouses shorten the travelled paths to store and retrieve (S/R) the loads, thanks to additional aisles crossing the parallel racks. This paper provides the analytic model to best design a non-traditional warehouse for unit-load (UL) with diagonal cross-aisles and storage policy according to the class-based storage (CBS) strategy. The model minimizes the average single-command cycle time to S/R the loads, best sizing the classes, their shape, and the position/numbers of additional aisles. The focus is on both 2- and 3-CBS optimizing the number of diagonal cross-aisles to best balance the travel time reduction and the loss of storage space due to the aisles. Furthermore, benchmarking toward standard warehouses with no diagonal cross-aisles and random assignment strategy allows quantifying the positive impact of the proposed design configuration on the daily warehouse operations. [ABSTRACT FROM AUTHOR]

The current research aims to present an inclusive review of latest research works performed with the aim of improving the efficiency of the hybrid renewable energy systems (HRESs) by employing diverse ranges of the optimization techniques, which aid the designers to achieve the minimum expected total cost, while satisfying the power demand and the reliability. For this purpose, a detailed analysis of the different classification drivers considering the design factors such as the optimization goals, utilized optimization methods, grid type as well as the investigated technology has been conducted. Initial results have indicated that among all optimization goals, load demand parameters including loss of power supply probability (LPSP) and loss of load probability (LLP), cost, sizing (configuration), energy production, and environmental emissions are the most frequent design variables which have been cited the most. Another result of this paper indicates that almost 70% of the research projects have been dedicated towards the optimization of the off-grid applications of the HRESs. Furthermore, it has been demonstrated that, integration of the PV, wind and battery is the most frequent configuration. In the next stage of the paper, a review concerning the sizing methods is also carried out to outline the most common techniques which are used to configure the components of the HRESs. In this regard, an analysis covering the optimized indicators such as the cost drivers, energy index parameters, load indicators, battery's state of charge, PV generator area, design parameters such as the LPSP, and the wind power generation to load ratio, is also performed. [ABSTRACT FROM AUTHOR]

Automation is a powerful way to reduce production costs. The growing market demand for a wide set of models and small batch production make flexible automated production systems an emerging need in several industries. The aim of this paper is to analyze and to maximize the performance of robotized flexible production systems consisting of a robot, feeder, working station, and unloading station, where the operations of the working cycle are scheduled using a sequencing algorithm based on priority rules. Since the working cycle is not predefined, the cycle time is strongly influenced by the parameters characterizing the workcell such as the workcell layout, the robot transfer movements, the feeder, the working operations, and the presence of a buffer between stations. In this work, we modeled the working cycle of a simple but representative layout of an industrial robotized flexible production system with and without buffer, and we implemented a recursive algorithm to estimate the cycle time. The analytical model derived was compared to the experimental results, obtained by using a prototype of the flexible production workcell. The results show that the analytical model is a powerful tool to estimate the performance of the workcell and to identify the design variables or their combinations that maximize the throughput. [ABSTRACT FROM AUTHOR]

Automation can be a valid way to reduce production costs. Considering medium/low volumes and a wide set of different models, a mixed model assembly work cell is a proper automated production system. The authors have recently introduced a new class of flexible assembly systems (FAS), the F-FAS, in which highly flexible feeding systems are used to improve the flexibility and reduce the set-up times at batch change. Such systems, guaranteeing a higher level of flexibility than traditional automated FAS, show some limitations in terms of productivity, due to the stochastic process of feeding and reorientation of parts and to the time spent for image acquisition and processing. The aim of this paper is to introduce an innovative automated assembly work cell, called the hybrid flexible assembly system (H-FAS), that merges the traditional FAS bowl feeder utilisation with the innovative F-FAS feeding concepts. The paper analyses the main factors influencing the H-FAS design, productivity and cost. Moreover, through a comparative analysis between the different single cell assembly systems, it defines the working conditions in which they can be preferable. [ABSTRACT FROM AUTHOR]

One of the significant challenges in operating a mix-model assembly system is the feeding of parts to the productive units. In order to avoid production loss, assembly systems require uninterrupted availability of components to feed workstations. On the other hand, the feeding of assembly components has to be performed in a way that minimises the related costs. In the past, the feeding system most widely used was so-called 'line storage' in which the components were stored along the assembly stations in large quantities and were periodically refilled by the central warehouse. Following just-in-time principles, nowadays, assembly system feeding is undertaken by supermarkets, as in decentralised storage areas close to the assembly lines. From such kinds of warehousing, a growing number of manufacturers are adopting two other feeding strategies: the kanban system, which continuously refills the assembly stations through the pull kanban system, or the kitting system, in which kits of components are prepared and delivered following the product through the assembly stations. This paper aims to quantitatively analyse and compare these two recent feeding strategies, considering the production mix variation and the assembled models variety influence. Moreover, kanban-kitting feeding policy and the related optimization issues are considered as hybrid. The findings from an industrial case study and a simulation analysis are also reported. Finally, a decision-making tool that defines a series of 'convenience areas' for the different feeding policies is provided. [ABSTRACT FROM AUTHOR]

A growing number of manufacturers are adopting the so-called supermarket strategy to supply components to the production system. Supermarkets are decentralized storage areas used as intermediate warehouses for parts required by the production system (typically assembly lines). Such a feeding system is widely used in the automotive industry where assembly stations in multiple mixed-model assembly lines are usually refilled by means of a systematic part replenishment driven by Kanban systems, adopting small trucking vehicles towing some wagons (tow trains). The aim of this paper is to provide a simple but robust framework in order to design the supermarket/feeding system dedicated to complex multiple mixed-model assembly lines. This framework proposes an integrated approach both for long-term (static analytical model) and short-term (dynamic simulation) problems dealing with Kanban and Supermarket systems dedicated to assembly lines, and the tow train fleet sizing and management. This proposed methodology is applied to a case study derived from the Italian automotive industry, and the results highlight the high interrelation between the long and the short term variables that can be evaluated only by an integrated approach that considers both static and dynamic aspects of the problem. The results of this study are then presented and widely discussed. [ABSTRACT FROM AUTHOR]

The general definition of the hybrid flow shop (HFS) environment is a set of S ≥ 2 production stages where at least one of these stages includes more than one machine, which can process one job at a time. A job can be defined as several operations to be performed by none, one, or more machines at each stage. Usually, these jobs are completed in some sequence between the different production stages, and in the case of setup activities, products are grouped in batches with buffers of work in progress between different production stages. Today, flexible production systems permit in some instances to relax job precedence constrains with alternative process cycles and to group together different batches of similar products in order to reduce setup activity incidence. On the other hand, the availability of multiple parallel machines in a single production stage makes it possible to split the lot size between different resources. This paper aims to solve the HFS scheduling problem in a flexible multistage batch production system, offering a heuristic procedure, to minimize the production makespan and increase the productive capacity utilization using a batch aggregation/splitting strategy while introducing the 'workload leveling function' concept. The results are compared with other important scheduling rules widely accepted in the industry and made part of an industrial application. The company used as a test sample is an Italian rotor shaft manufacturer. The final result is illustrated to validate the proposed heuristics. [ABSTRACT FROM AUTHOR]

In modern assembly-to-order systems, sub-assemblies warehouse locations, dimensions, and supply are critical decisional variables. Persona et al. (Int J Prod Econ 110(1–2):147–159, ) affirm the structural diversity between assembly parts can largely influence the stocking policies. On the other hand, Zhang et al. () and Hsu et al. (Nav Res Logist 54(5):510–523, ) substantiate that the problem gets more complex when it comes to choosing the correct physical locations for common assembly parts. The study at hand concentrates on components warehouse centralization/decentralization choices in an assembly-to-order (ATO) environment, which typically supplies the assembly systems with components’ kits through decentralized warehouses called “Supermarkets”. Specifically, this paper applies an innovative step-by-step procedure to support materials management decision-making policies in order to define when, how, and where it is convenient to install a supermarket warehouse, considering the typical aspect of an ATO environment: number, type, position of the assembly systems, demand rate and commonality degree of components used, internal transportation equipment and transportation costs, load unit capacity, space cost for stocking, space availability in the plant, inventory costs, and safety stock dimension. [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]