Factory Context Research Articles

Multi-layer edge resource placement optimization for factories

Introducing distributed computing paradigms to the manufacturing domain increases the difficulty of designing and planning an appropriate IT infrastructure. This paper proposes a model and solution approach addressing the conjoint application and IT resource placement problem in a factory context. Instead of aiming to create an exact model, resource requirements and capabilities are simplified, focusing on usability in the planning and design phase for industrial use cases. Three objective functions are implemented: minimizing overall cost, environmental impact, and the number of devices. The implications of edge and fog computing are considered in a multi-layer model by introducing five resource placement levels ranging from on-device, within the production system, within the production section, within the factory (on-premise), to the cloud (off-premise). The model is implemented using the open-source modeling language Pyomo. The solver SCIP is used to solve the NP-hard integer programming problem. For the evaluation of the optimization implementation a benchmark is created using a sample set of scenarios varying the number of possible placement locations, applications, and the distribution of assigned edge recommendations. The resulting execution times demonstrate the viability of the proposed approach for small (100 applications; 100 locations) and large (1000 applications, 1000 scenarios) instances. A case study for a section of a factory producing electronic components demonstrates the practical application of the proposed approach.

Smart Interactive Technologies in the Human-Centric Factory 5.0: A Survey

In this survey paper, we focus on smart interactive technologies and providing a picture of the current state of the art, exploring the way new discoveries and recent technologies changed workers’ operations and activities on the factory floor. We focus in particular on the Industry 4.0 and 5.0 visions, wherein smart interactive technologies can bring benefits to the intelligent behavior machines can expose in a human-centric AI perspective. We consider smart technologies wherein the intelligence may be in and/or behind the user interfaces, and for both groups we try to highlight the importance of designing them with a human-centric approach, framed in the smart factory context. We review relevant work in the field with the aim of highlighting the pros and cons of each technology and its adoption in the industry. Furthermore, we try to collect guidelines for the human-centric integration of smart interactive technologies in the smart factory. In this wa y, we hope to provide the future designers and adopters of such technologies with concrete help in choosing among different options and implementing them in a user-centric manner. To this aim, surveyed works have been also classified based on the supported task(s) and production process phases/activities: access to knowledge, logistics, maintenance, planning, production, security, workers’ wellbeing, and warehousing.

Augmented Reality Authoring of Digital Twins: Design, Implementation and Evaluation in an Industry 4.0 Context

This paper deals with Digital Twins (DTs) for Industry 4.0 factories, and their implementation in the context of a reconfigurable factory. This context implies a modification of the layout of the workstations during production, and thus requires a live update of the digital twins according to these modifications. We needed this update done by the operators directly on the workstations using an AR authoring tool. A literature review helped us to determine the criteria that a tool should fulfill in order to achieve this goal. The most important criteria are that the tool should be suitable for use by operators not trained in AR, that the learning curve should be short, and that it should be usable in a reconfigurable factory context. We created a DT containing all the necessary factory data and 3D models of the workstation interaction zones of a real assembly line. We then developed a tool enabling operators to match the DTs with their physical twin (PT) in AR, as well as to update their position in case of a reconfiguration. The experimentation we carried out confirms our analysis and shows us that it is possible to deploy a DT in a factory quite simply if the positioning of the DTs is done by direct manipulation (the 3D objects are co-located with the operator’s hand) with the help of an AR display device.

Design Factory – Supporting technology students’ learning of general competences through university-industry collaboration

Many studies emphasise the need for supporting higher education students to develop general competences. In this study, we report on the first cycle of a design-based research project conducted in the Design Factory context. The aim of the project is to understand how general competences can be integrated into course modules and within university-industry collaboration in a successful way. In this study, we report on a theoretical problem analysis and describe the design solution, namely the Design Factory implementation. We then move on to an empirical problem analysis and investigate how students reported developing general competences in the implementation. When discussing the implications for further developing the design solution, we conclude that communication has a vital role in university-industry collaboration; it is essential in clarifying the multilevel learning opportunities (e.g., the subject content, development of general competences) for students, and in aligning industry interests with educational learning objectives. We also reflect on the first development cycle as a whole and provide implications for refining the design process. Finally, we draw conclusions from the whole DBR project and provide a new theoretical perspective (cf. Edelson, 2002), namely design-based education in the co-creation contexts, that can be utilised when investigating the development of general competences in the Design Factory context.

Value Configurations for Data and Connectivity Solutions in Digitalized Future Factories

The ongoing Industry 4.0 transformation places significant pressures on how businesses create and capture value. Technological advancements such as next-generation mobile communications are reshaping the business ecosystem of Industry 4.0, resulting in emerging business opportunities for new players, such as local operators, to collaborate and compete with mobile communications companies that are implementing I4.0. These changes raise the need to explore emerging business opportunities concerning the digitalization of future factories. New data and connectivity services are introduced to serve the needs of rapidly increasing machine-type communications that rely on connectivity, primarily through the fifth generation (5G) mobile solutions provided by local operators. Thus, this paper outlines the potential value configurations for data and connectivity solutions by identifying, matching, and bridging the utilizable resources and addressable needs within the factory processes. The research applies an exploratory approach and uses the Gioia method to analyze qualitative data of a single case. The study follows the connectivity-content-context-commerce typology (4C) of Internet business models to structure, analyze, and classify the identified needs and resources in future factories from the perspective of the local operator. The findings show that the content layer of 4C business model typology is the most dominant among data and connectivity-based needs and resources of future factories. The paper contributes by presenting four alternative value configurations for digitalization for local operators in the future factory context: the product, component, platform, and complementary businesses. The results suggest content- and context-specific businesses carries foremost business potential for local operators, however quantitative validation will bring fruitful research avenues. Multiple case studies and different data collection methods may also be considered in future studies.

Data Quality Affecting Big Data Analytics in Smart Factories: Research Themes, Issues and Methods

Recent years have seen a growing call for use of big data analytics techniques to support the realisation of symmetries and simulations in digital twins and smart factories, in which data quality plays an important role in determining the quality of big data analytics products. Although data quality affecting big data analytics has received attention in the smart factory research field, to date a systematic review of the topic of interest for understanding the present state of the art is not available, which could help reveal the trends and gaps in this area. This paper therefore presents a systematic literature review of research articles about data quality affecting big data analytics in smart factories that have been published up to 2020. We examined 31 empirical studies from our selection of papers to identify the research themes in this field. The analysis of these studies links data quality issues toward big data analytics with data quality dimensions and methods used to address these issues in the smart factory context. The findings of this systematic review also provide implications for practitioners in addressing data quality issues to better use big data analytics products to support digital symmetry in the context of smart factory.

Added value of a virtual approach to simulation-based learning in a manufacturing learning factory

More and more learning factories (LF) are set up supporting the vision of Industry 4.0 connectivity and automation levels; thus, digital twins, virtual and augmented reality are emerging tools. Literature review is the basis for the discourse on possible constraints and opportunities these tools have for the cognitive learning processes in a simulation. State of the art give insight in the lack of research on value of digital learning activities in learning factory setting. This paper is a concept description, giving input to the community on aspects to be considered regarding the use VR/AR/digital twins in a learning factory context.

Yearning for Care? Rethinking Paternalism in Contemporary China from Migrant Worker’s Perspective

A great deal of research work available on the situation of migrant workers in post-Mao China focuses on how the working conditions generate anger among the migrant workers, which causes strengthening of their 'horizontal' networks and their informal protection organizations. This paper shifts the attention from 'horizontal' to 'vertical' networks in factory and attempts to figure out what are the mostly likely ways to change China's state-society relationship. I argue that the factory context has strongly been shaped by parental absence and dysfunctional families following mass migration. When migrant workers' family experiences are about unrequited yearning for care and intimacy, it appears that 'fatherizing' of authorities of various kinds which are seen as (being able to be) caregivers and effective allocators of resources may be the proper response to the near constant absence of close family. Under such circumstance, the rise of individualism could paradoxically fuel paternalism.

Empowerment, Work and Ethics: Lessons from Heidegger

This brief note is about the intrigue connection between empowerment, work and ethics. The paper looks at empowerment from Heidegger's perspective. Empowerment is the crux of Heidegger’s 1943 treatise on “the essence of truth”. For Heidegger, empowerment is the active aspect of truth. In other words, truth is the activity of empowerment. Truth, work, freedom and empowerment for Heidegger belongs to the same family of words, each representing the aspect of the other. Empowerment and work are closely related ideas. The link is now being rediscovered in empowerment literature. However, in early 19th century and 20th century, though it was called an era of the industrial revolution, it had a different understanding of work as labour. Work as labour in Taylor’s scientific management, for instance, was conceptualized as work bereft of workmanship in the factory context. Taylor looked at work as physical labour, especially the labour of loading and unloading and the labour in which workers are treated as human animals meant to use the body obeying the will of the manager. He insisted that workers should not bring workmanship in factory work. Work was treated as a divine commandment along with dictates of work ethics, distracting from which is a grievous sin for Calvinists. Work as ethics in this sense was taught to erstwhile slaves throughout the world in ‘slave schools’ to trigger transformation from slave dependent capitalism to labour oriented capitalism. On the contrary, the essence of work is empowerment, claims Heidegger. It is opening up one’s comportment to the power of being qua being human. It is liberation itself. Heidegger looks at being as an activity and not as an entity. Being is an activity in time that goes under the experience of self-revelation into truth, the truth of freedom. Being works out its freedom through empowerment and resoluteness: this is the thesis Heidegger presented before us. The paper explored the connection from the Heideggerian perspective.

Barriers of embedding big data solutions in smart factories: insights from SAP consultants

PurposeBig data is a key component to realise the vision of smart factories, but the implementation and usage of big data analytical tools in the smart factory context can be fraught with challenges and difficulties. The purpose of this paper is to identify potential barriers that hinder organisations from applying big data solutions in their smart factory initiatives, as well as to explore causal relationships between these barriers.Design/methodology/approachThe study followed an inductive and exploratory nature. Ten in-depth semi-structured interviews were conducted with a group of highly experienced SAP consultants and project managers. The qualitative data collected were then systematically analysed by using a thematic analysis approach.FindingsA comprehensive set of barriers affecting the implementation of big data solutions in smart factories had been identified and divided into individual, organisational and technological categories. An empirical framework was also developed to highlight the emerged inter-relationships between these barriers.Originality/valueThis study built on and extended existing knowledge and theories on smart factory, big data and information systems research. Its findings can also raise awareness of business managers regarding the complexity and difficulties for embedding big data tools in smart factories, and so assist them in strategic planning and decision making.

Assessing the operational and economic efficiency benefits of dynamic manufacturing networks through fuzzy cognitive maps: a case study

The formation and effective end-to-end management of manufacturing networks is touted as a top priority for manufacturing enterprises that strive to improve the efficiency, adaptability and sustainability of their production systems. Due to their potential benefits, Dynamic Manufacturing Networks (DMNs), a knowledge-enhanced, model-based production management approach enabling seamless communication and cooperation among individual network members’ manufacturing systems, are gradually becoming a focal point of attention. Nevertheless, current understanding around the DMN concept remains fuzzy, whereas the way in which it can benefit manufacturing enterprises lacks proper articulation. This paper clarifies the management approach of Dynamic Manufacturing Networks on the basis of the DMN lifecycle and the respective information model used, while it further develops a model for their evaluation. In this respect, it employs the soft computing methodology of Fuzzy Cognitive Maps to capture industry laypeople perceptions on the factors that affect their operation, and to reveal insights on prospective benefits. Application of this model in a real-world, multi-site, single factory context in the semi-conductor industry provides good approximations of the experts’ estimations. The results, found in the directions of reduced cycle times, decreased costs and improved quality are quite promising and highlight the key role of the DMN information model. The assessment model designed enables to reason on and identify DMN gains. Thereby, it provides a basis for communication as well as a decision aid that offers evidence on the outcomes of establishing DMNs, ultimately creating a sense of confidence, before an enterprise commits its resources to it.

Adapting an agile manufacturing concept to the reference architecture model industry 4.0: A survey and case study

Abstract Industry 4.0 architecture has been studied in a large number of publications in the fields of Industrial Internet of Things, Cyber Physical Production Systems, Enterprise Architectures, Enterprise Integration and Cloud Manufacturing. A large number of architectures have been proposed, but none of them has been adopted by a large number of research groups. Two major Industry 4.0 reference architectures have been developed by industry-driven initiatives, namely the German Industry 4.0 and the US-led Industrial Internet Consortium. These are the Reference Architecture Model Industry 4.0 and Industrial Internet Reference Architecture, which are being standardized by the International Electrotechnical Commission and the Object Management Group, respectively. The first research goal of this article is to survey the literature on Industry 4.0 architectures in a factory context and assess awareness and compatibility with Reference Architecture Model Industry 4.0 and Industrial Internet Reference Architecture. The second research goal is to adapt a previously proposed advanced manufacturing concept to Reference Architecture Model Industry 4.0. With respect to the first research goal, it was discovered that only a minority of researchers were aware of the said reference architectures and that in general authors offered no discussion about the compatibility of their proposals with any internationally standardized reference architecture for Industry 4.0. With respect to the second research goal, it was discovered that Reference Architecture Model Industry 4.0 was mature with respect to communication and information sharing in the scope of the connected world, that further standardization enabling interoperability of different vendors’ technology is still under development and that technology standardization enabling executable business processes between networked enterprises was lacking.

Smart operators in industry 4.0: A human-centered approach to enhance operators’ capabilities and competencies within the new smart factory context

As the Industry 4.0 takes shape, human operators experience an increased complexity of their daily tasks: they are required to be highly flexible and to demonstrate adaptive capabilities in a very dynamic working environment. It calls for tools and approaches that could be easily embedded into everyday practices and able to combine complex methodologies with high usability requirements. In this perspective, the proposed research work is focused on the design and development of a practical solution, called Sophos-MS, able to integrate augmented reality contents and intelligent tutoring systems with cutting-edge fruition technologies for operators’ support in complex man-machine interactions. After establishing a reference methodological framework for the smart operator concept within the Industry 4.0 paradigm, the proposed solution is presented, along with its functional and non-function requirements. Such requirements are fulfilled through a structured design strategy whose main outcomes include a multi-layered modular solution, Sophos-MS, that relies on Augmented Reality contents and on an intelligent personal digital assistant with vocal interaction capabilities. The proposed approach has been deployed and its training potentials have been investigated with field experiments. The experimental campaign results have been firstly checked to ensure their statistical relevance and then analytically assessed in order to show that the proposed solution has a real impact on operators’ learning curves and can make the difference between who uses it and who does not.

KSim: An information system for knowledge management in Digital Factory

The key of successful industry is to satisfy the customer requirements at the perfect delay with improved quality and cheaper price. In this context, Digital Factory is known to test and validate the couple product-production system during the product development process, with the usage of production system simulations. Therefore, we can use an information system to integrate and manage all information related to product, process and simulation in this context. But with this huge amount of information, an actor of product development process may be confused about making a good decision at this particular stage. Thus, there is a lack of knowledge capitalization and sharing between product development process actors. On the basis of previous research works that contribute to the definition of a Digital Factory information system, we propose a new module, named KSim, dedicated to the capitalization and management of knowledge and experiences coming from previous projects in the Digital Factory context.

A framework to design a human-centred adaptive manufacturing system for aging workers

The so-called smart manufacturing systems (SMS) combine smart manufacturing technologies, cyber-physical infrastructures, and data control to realize predictive and adaptive behaviours. In this context, industrial research focused mainly on improving the manufacturing system performance, almost neglecting human factors (HF) and their relation to the production systems. However, in order to create an effective smart factory context, human performance should be included to drive smart system adaptation in efficient and effective way, also by exploiting the linkages between tangible and intangible entities offered by Industry 4.0. Furthermore, modern companies are facing another interesting trend: aging workers. The age of workers is generally growing up and, consequently, the percentage of working 45–64years old population with different needs, capabilities, and reactions, is increasing. This research focuses on the design of human-centred adaptive manufacturing systems (AMS) for the modern companies, where aging workers are more and more common. In particular, it defines a methodology to design AMS able to adapt to the aging workers’ needs considering their reduced workability, due to both physical and cognitive functional decrease, with the final aim to improve the human-machine interaction and the workers’ wellbeing. The paper finally presents an industrial case study focusing on the woodworking sector, where an existing machine has been re-designed to define a new human-centred AMS. The new machine has been engineered and prototyped by adopting cyber-physical systems (CPS) and pervasive technologies to smartly adapt the machine behaviour to the working conditions and the specific workers’ skills, tasks, and cognitive-physical abilities, with the final aim to support aging workers. The achieved benefits were expressed in terms of system usability, focusing on human-interaction quality.

First Application of Robot Teaching in an Existing Industry 4.0 Environment: Does It Really Work?

This article reports three case studies on the usability and acceptance of an industrial robotic prototype in the context of human-robot cooperation. The three case studies were conducted in the framework of a two-year project named AssistMe, which aims at developing different means of interaction for programming and using collaborative robots in a user-centered manner. Together with two industrial partners and a technological partner, two different application scenarios were implemented and studied with an off-the-shelf robotic system. The operators worked with the robotic prototype in laboratory conditions (two days), in a factory context (one day) and in an automotive assembly line (three weeks). In the article, the project and procedures are described in detail, including the quantitative and qualitative methodology. Our results show that close human-robot cooperation in the industrial context needs adaptive pacing mechanisms in order to avoid a change of working routines for the operators and that an off-the-shelf robotic system is still limited in terms of usability and acceptance. The touch panel, which is needed for controlling the robot, had a negative impact on the overall user experience. It creates a further intermediate layer between the user, the robot and the work piece and potentially leads to a decrease in productivity. Finally, the fear of the worker of being replaced by an improved robotic system was regularly expressed and adds an additional anthropocentric dimension to the discussion of human-robot cooperation, smart factories and the upcoming Industry 4.0.

Cross-disciplinary Design Based on the Digital Factory as a Boundary Object

In the domain of developing production systems, the design of a good factory is typically distributed over many disciplines and organizations to cover all involved technologies and levels of detail (process, logistics, machinery etc.). Modelling and simulation used to support the design process within each of the disciplines typically represent different contexts and perspectives. To cross the discipline borders and share experiences, to encourage innovation and make holistic decisions, one challenge is to interrelate various digital models and to reach a mutual system understanding between stakeholders.This paper presents a study based on principles from Social Science, Production Engineering, Computer Science and Information Design to address cross-disciplinary collaboration. Principles concerning visual communication and theories in regard to tangible boundary objects are used to clarify how to describe production system interdependencies in a digital factory context. Work in process of implementing a digital factory framework based on the principles is described, with a use case demonstrating the development of a digital factory for a new type of automotive vehicle.

Software Evaluation Criteria for Rapid Factory Layout Planning, Design and Simulation

The objective of this paper is to specify functional requirements on software for rapid factory planning and design in a digital factory context. In comparison with other studies that focus on particular aspects of layout development, this work deploys a comprehensive approach, based on industrial needs, to determine main functionalities for factory layout software. The research considers integration of different layouts where original equipment manufacturer and other stakeholders involved in factory layout design collaborate with each other to develop, or extend a factory. Therefore; engineering change management and data exchange in a system neutral format are taken into account as main pillars.

Multiscale modelling of postharvest storage of fruit and vegetables in a plant factory context

AbstractAfter harvest, fruit and vegetables produced in plant factories need to be stored under refrigerated conditions. There has been an interest in the use of mathematical models for optimising the operation, design and control of postharvest refrigeration systems. These mathematical models are applied to predict the physical and chemical phenomena that take place during postharvest handling of horticultural products. Nowadays, with the availability of more powerful computers at a reasonable price, it is feasible to investigate the details of the flow behaviour in large-scale refrigeration systems at a very small spatial and temporal scale. In this presentation an overview will be given of advances in the application of mathematical models for predicting and optimising fluid flow, heat and mass transfer and associated phenomena during postharvest refrigeration of horticultural products. Special attention will be paid to the multiscale formalism to describe heat and mass transfer phenomena over a wide range of spatial scales.