Ebook: Transdisciplinary Engineering for Complex Socio-technical Systems – Real-life Applications
Transdisciplinary engineering transcends other inter- and multi-disciplinary ways of working, such as Concurrent Engineering (CE). In particular, transdisciplinary processes are aimed at solving complex, ill-defined problems, or problems for which the solution is not immediately obvious. No one discipline or single person can provide sufficient knowledge to solve such problems, so collaboration is essential.
This book presents the proceedings of the 27th ISTE International Conference on Transdisciplinary Engineering, organized by Warsaw University of Technology, Poland, from 1-10 July 2020. ISTE2020 was the first of this conference series to be held virtually, due to the COVID-19 restrictions. Entitled Transdisciplinary Engineering for Complex Socio-technical Systems - Real-life Applications, the book includes 71 peer-reviewed papers presented at the conference by authors from 17 countries. These range from theoretical and conceptual to strongly pragmatic and addressing industrial best practice and, together with invited talks, they have been collated into 9 sections: Transdisciplinary Engineering (7 papers); Transdisciplinary Engineering Education (4 papers); Industry 4.0, Methods and Tools (7 papers); Human-centered Design (8 papers); Methods and Tools for Design and Production (14 papers); Product and Process Development (9 papers); Knowledge and Data Modeling (13 papers); Business Process and Supply Chain Management (7 papers); and Sustainability (2 papers).
The book provides an overview of new approaches, methods, tools and their applications, as well as current research and development, and will be of interest to researchers, design practitioners, and educators working in the field.
This book of proceedings contains papers that have been peer-reviewed and accepted for the 27th ISTE International Conference on Transdisciplinary Engineering, organized by Warsaw University of Technology, Poland, July 1 – 10, 2020. TE2020 has been the first conference in the series that was organized in a virtual manner due to the COVID-19 world-wide crisis. The papers published in this book of proceedings, as well as video presentations, were accessible during July 2020 in Webex Teams, while questions and answers were being exchanged.
This is the eleventh issue of the series “Advances in Transdisciplinary Engineering”, which publishes the proceedings of the TE (formerly: CE) conference series and accompanying events. The TE conference series is organized annually by the International Society of Transdisciplinary Engineering, in short ISTE (www.intsoctransde.org), formerly called International Society of Productivity Enhancement (ISPE, Inc.) and constitutes an important forum for international scientific exchange on transdisciplinary engineering. These international conferences attract a significant number of researchers, industry experts and students, as well as government representatives, who are interested in recent advances in transdisciplinary engineering research, advancements and applications.
The concept of Transdisciplinary Engineering includes Concurrent Engineering (CE), but also transcends it. The concept of CE, developed in the 80’s, implies that different phases of a product life cycle are conducted concurrently and initiated as early as possible within the Product Creation Process (PCP), including the implications of this approach within the extended enterprise and networks. The main goal of CE is to increase the efficiency and effectiveness of the PCP and to reduce errors in the later phases, as well as to incorporate considerations for the full lifecycle, through-life operations, and environmental issues. In the past decades, CE has become the substantive basic methodology in many industries (e.g., automotive, aerospace, machinery, shipbuilding, consumer goods, process industry, environmental engineering) and is also adopted in the development of new services and service support. Collaboration between different disciplines is key to successful CE.
While for several decades CE proved its value in many industries and still continues to do so, many current engineering problems require a more encompassing approach. Many engineering problems have a large impact on society. For example, the development of self-driving cars requires taking into account changes in regulations for managing responsibilities, adaptation of road networks, political decisions, infrastructures for energy supply, etc. The impacted society may also be the business environment of networks of companies and supply chains. For example, the adoption and implementation of Industry 4.0 requires taking into account the changes to be expected in the business environment, the people, their jobs, the knowledge needed, technology, organizational rules and behaviours. These kind of engineering problems also require collaboration, but not only between technical disciplines. Disciplines from other scientific fields need to be incorporated in the engineering process, like disciplines from social sciences (governance, psychology, etc.), law, medicine, or other fields, relevant for the problem at hand.
The concept of transdisciplinary engineering transcends inter- and multi-disciplinary ways of working, like in CE. In particular, transdisciplinary processes are aimed at solving complex ill-defined problems or problems for which the solution is not obvious from the beginning. While such problems, including their solutions, have a large impact on society and the context in which the problems exist, it is important that people from society and practice collaborate with people from different relevant scientific communities. Neither one discipline nor one person can bring sufficient knowledge for solving such problems. Collaboration again is essential but has become even more demanding. Disciplines should be open to other disciplines to be able to share and exchange the knowledge necessary for solving the problem.
Any engineering problem can be put is a context in which the problem is to be solved or in which the solution for the problem is expected to be used. For researchers and engineers, it is important to take into account this context. This could be done, for example, by collaborating with researchers who can study user acceptance of the envisioned solution or with researchers who can apply suitable methods to acquire user preferences in the respective context and translate them into the necessary requirements for the solution to be developed. Validation of a proposed engineering solution will benefit also by incorporating people from other scientific fields.
The conference is entitled: “Transdisciplinary Engineering for Complex Socio-technical Systems in perspective of Real-life Application”. The TE2020 Organizing Committee has identified 36 thematic areas grouped into nine themes within TE and launched a Call for Papers accordingly. More than 80 papers have been submitted from all continents of the world. The submissions as well as invited talks have been collated into nine themes.
The Proceedings contains 71 peer-reviewed papers presented at the conference by authors from 17 countries. These papers range from the theoretical, conceptual to strongly pragmatic addressing industrial best practice. The involvement of industry in many of the presented papers gives additional importance to this conference.
This book on “Transdisciplinary Engineering for Complex Socio-technical Systems in perspective of Real-life Application” is directed at three constituencies: researchers, design practitioners, and educators. Researchers will benefit from the latest research results and knowledge of product creation processes and related methodologies. Engineering professionals and practitioners will learn from the current state of the art in transdisciplinary engineering practice, new approaches, methods, tools and their applications. The educators in the TE community gather the latest advances and methodologies for dissemination in engineering curricula, to prepare students for transdisciplinary collaboration in complex engineering processes, while the community also encourages educators to bring new ideas into the field. With the annual contributions of many researchers and practitioners the book series will contribute to the further development of the concept of Transdisciplinary Engineering.
The proceedings are subdivided into several parts, reflecting the themes addressed in the conference programme:
Part 1 is entitled Transdisciplinary Engineering and contains seven papers that address the concept of TE. Some papers contain research into understanding the concept of TE, while others present work in which a transdisciplinary approach is or has been applied in developing a complex system.
Part 2 contains papers in the area of Transdisciplinary Engineering Education, an important field in our conferences. Empowering students with the knowledge to collaborate in complex project like TE projects is very important. Four papers present different ways in which students learn to deal with different types of knowledge.
Part 3, Industry 4.0, Methods and Tools, contains seven papers with subjects like bibliometric analysis for smart farming, information traceability to detect non-conformities in production, design languages for automatic generation of digital twins of CBSs, Enterprise Maturity Levels measurement, the use of IoT in industrial logistics, a design support tool for the development of CPSs, and reference architectures for Industry 4.0.
Part 4 contains eight papers in the theme Human-Centred Design addressing e.g., a transdisciplinary assessment matrix for human-machine interaction, innovative tools for designing ergonomic control dashboards, ergonomics in a university hospital, informal requirements analysis for a prosthetic device, radiographic bone age assessment, technology for the manufacturing of innovative orthopaedic corsets, evaluation of humanoid robot design base on global eye-tracking metrics, and transdisciplinary design of an air mobile stroke unit.
Part 5 is entitled Methods and Tools for Design and Production. It contains 14 papers focusing on engineering and logistic subjects like Berth allocation and quay crane assignment, control and coordination, tools for sheet metal forming, mass customization services through VR-enabled chatbot systems, green flatcar transportation scheduling in shipbuilding, FMEA with a multi-criteria approach, MCDM application in early stages of the PDP, context-sensitive evaluation of PSS solutions, change propagation in product realization, impact assessment of food safety news, automated generation of a digital twin of a manufacturing system, phenomena in safety systems made of hyper-elastic materials, verification of a method for building a very flexible wing generative model, and a thermomechanical model of a crank mechanism.
Part 6 contains nine contributions on Product and Process Development with various contributions like a design methodology for smart PSS development, digital collaboration techniques for interdisciplinary collaboration, energetic autonomy of UAV, a requirements management tool for specification and analysis of product lines, a multi-disciplinary optimisation framework for dual-mode launch vehicle concepts, factory planning by automated generation of a digital twin, design of injection moulding for LED lamp power supply, morphic arrangement of high flexibility and aspect ratio wing, and hierarchical models for vulnerability analysis of road networks.
Part 7 is entitled Knowledge and Data Modelling. It contains 13 papers with a focus on modelling, like a synthetic dataset for deep learning noise filtering, BIM maturity models, issues in semantic interoperability in integrated manufacturing, neural network for forecasting intermittent demand, semantic ontology for identification of trademark case precedents, integrated information for customized product development, reliability prediction for aircraft component behaviour by using textual elements, parametric modelling of steel connectors, knowledge-based assisting tools, agile engineering change management approach, cost modelling of recycling carbon fibre composites, modularity and configuration for IoT, and robust CAD modelling for industrial application.
Part 8 deals with Business Process and Supply Chain Management. This part contains seven contributions on identifying superfluous work in shop floor management digitalisation, conceptual model for process capability, practice-based learning for successful application of supply chain 4.0 technology, foreign direct investment and enterprise ownership, bibliometric analysis of production planning optimization, delivery demand peak levelling based on capability assessment of customer’s acceptance, and an adaption of the internal quality auditing process.
Part 9 contains contributions on Sustainability addressing global transport challenges in reducing emission, and a CAD material skeleton approach for sustainable design.
We acknowledge the high-quality contributions of all authors to this book and the work of the members of the Scientific Committee who assisted with the blind peer-review of the original papers submitted and presented at the conference. Readers are sincerely invited to consider all of the contributions made by this year’s participants through the presentation of TE2020 papers collated into this book of proceedings. We hope that they will be further inspired in their work for disseminating their ideas on transdisciplinary engineering within the ISTE community.
Jerzy Pokojski, Conference Chair
Warsaw University of Technology, Po-land
Maciej Gil, Secretariat
Linda Newnes, Program Chair
University of Bath, UK
Josip Stjepandić, Program Co-Chair
PROSTEP AG, Germany
Nel Wognum, Program Co-Chair
TU Delft, The Netherlands
Since the announcement of Industry 4.0 in 2012, multiple variants of this industry paradigm have emerged and built on the common platform of Internet of Things. Traditional engineering driven industries such as aerospace and automotive are able to align with Industry 4.0 and operate on requirements of the Internet of Things platform. Process driven industries such as water treatment and food processing are more influenced by societal perspectives and evolve into Water 4.0 or Dairy 4.0. In essence, the main outcomes of these X4.0 (where X can be any one of Quality, Water or a combination of) paradigms are facilitating communications between socio-technical systems and accumulating large amount of data. As the X4.0 paradigms are researched, defined, developed and applied, many real examples in industries have demonstrated the lack of system of systems design consideration, e.g. the issue of training together with the use of digital twin to simulate operation scenarios and faults in maintenance may lag behind events triggered in the hostile real world environment. This paper examines, from a high level system of systems perspective, how transdisciplinary engineering can incorporate data quality on the often neglected system elements of people and process while adapting applications to operate within the X4.0 paradigms.
Presented in this paper are the results of a systematic literature review to identify the competencies required by design engineers to work in increasingly complex societal projects. These competencies are then mapped against the four levels of a hierarchical system defined by Jantsch to ascertain the disciplinarity of these competencies. The results from this mapping form the first phase in the creation of a Designer Readiness Level for transdisciplinary engineering. To date current research has identified that to meet these future needs, defined as Grand Challenges for Engineering by the National Academy of Engineering, it will be necessary to adopt transdisciplinary methods of working. However, there is little in the literature that identifies how to assess the transdisciplinarity of people, tools or project teams. Although literature and learned societies do highlight that engineers are crucial to meet these societal needs, how do we determine whether an engineer is able to work in a transdisciplinary manner? A total of 2398 papers were included in the review and twenty-nine papers selected for full-text review. A final seven focussing on practicing design engineers were used to create a current list of competencies. The paper continues by describing the analysis method and results of mapping the competencies identified against Jantsch’s four levels. The paper concludes with a summary of the next stage required to create a Designer Readiness Level for transdisciplinary engineering.
Based on the appearance of the term within the academic literature, it would appear that transdisciplinarity (TD) approaches are receiving increased research attention. However, the literature suggests a lack of consensus over how TD is defined and classified. This could give rise to inconsistency and papers that claim to be TD which are not, and alternatively papers that fail to mention TD but which might be classified as such. This is significant and creates a challenge in identifying the true level of TD research. This work contributes towards understanding the state of TD within engineering. Explicitly, we address the research question: Is the engineering academic literature claiming to be TD, actually TD? Within this study we operationalise the work of Jantsch and use this as a means to classify the disciplinarity of 177 engineering journal papers which reference TD within their abstract. The results show only 24% to be TD. The majority (64%) are classified as interdisciplinary. Conclusions find that to improve consistency, a clear definition and rules for differentiation between TD and ID research are required. Future work calls for: (1) comparative studies which apply different methods for assessing disciplinarity across the dataset used within this study and which use the method employed within this study across different fields. (2) Research to analyse whether TD working is being undertaken in engineering without it being referenced within the paper.
Research literature terminology illustrates that publications claim to pertain to “disciplinary” approaches and researcher’s align themselves to specific, multi-, inter- or trans-disciplinarities. Ambiguity exists in definition and application of disciplinarity, hence there is need to establish a coherent application of disciplinarity. We present results of content analysis of research literature claiming to be inter-, multi-, or transdisciplinary to assist in ascertaining commonalities or differences for those disciplinarities. We analyse the abstracts and keywords of 8834 papers, using n-grams and bi-grams, dating from 1970 until 2018, extracting a list of 76,552 terms for comparison. The top 15 most frequent terms characterise each disciplinarity and Venn diagrams of the top 15 features illustrate differences and overlap. A total of six terms appear common to all approaches in the abstracts, with four shared by multi- and inter-, two between inter- and trans-, and none common to multi- and trans-. The term “social science(s)” appears to be a unique feature in the trans- abstracts and our findings identify common text terms such as the “research” feature, common to all disciplinarities. This supports characterising the nature of transdisciplinarity and its unique differences from other approaches such as inclusion of social science(s).
Manufacturing is undergoing rapid change. Whether through the creation of smart materials and products, or utilising data, information and knowledge, the requirement for different ways of working is increasing. To meet future manufacturing needs, design and manufacturing skills and tools must transcend disciplines and industrial sectors. Transdisciplinary Engineering Design (TREND) aims to enable the rapid uptake of emerging technologies across manufacturing sectors and the constitute disciplines. Within this paper, we provide an overview of the TREND research group and their preliminary research towards a Transdisciplinary Engineering Index.
Transdisciplinary (TD) working offers the potential to bring together potentially disparate elements of engineering projects permitting them to concomitantly be addressed on empirical, pragmatic, normative and purposive levels. Whilst the importance and potential benefits of working in this manner are widely accepted, a key inhibitor to the adoption and embedding of TD working in practice is the variety and diversity of design tools employed and their relative levels of ability to support TD working. To explore what can be thought of as the enabling or inhibiting roles of design tools, this paper appraises common design tools and classifies them according to the level of transdisciplinary working that they permit. This is achieved by considering the capturable level of design rationale for each design tool as per Jantsch and contextualising each within the design process. The discussion considers how these findings are reflected in practice and how chains of particular tools could be employed to support TD working across the different phases of the design process. In total 41 tools are appraised with 6 acting as enablers of interdisciplinary working but none identified as truly TD. Most notably, a much greater proportion of TD enabling design tools are available to support the early phases of design. Further work might consider how education can be used to ensure effective use of current design tools and how knowledge transfer can and should be, applied to enable use of TD tool chains in industry.
Over the last decade, transparency schemes have started to undergo a radical transformation. This transformation is driven by advancements in cloud computing, cryptography and automated measurement technology, which have made it possible to develop shared information management systems (SIMS). These SIMS form the backbone of the latest, state-of-the-art in the transparency space: hyper-transparency schemes. These new transparency schemes and associated SIMS offer companies, both small and large, the opportunity to redesign their supply chains and to establish more direct relationships with their second- and third-tier trading partners, as well as with the consumer. However, the companies also face various challenges in implementing and operating such hyper-transparency schemes. There are legitimate concerns about privacy, ownership and access to data and, related to this, who controls the SIMS. The present paper discusses the ongoing development of a SIMS. The objective of this SIMS is to: (1), help empower smallholders in agri-food supply chains to establish more direct connections with the consumer; and (2), help empower consumers to get more direct insight into the manner in which their food stuff is being produced. The paper presents the design of the SIMS and discusses its transdisciplinary development processes.
Recent decades have seen increased interest in transdisciplinary (TD) research. To deliver on the promise of TD working there has been a call for the expansion of TD education in emerging literature. The challenge with proposed approaches is that they are often difficult to implement requiring significantly changed courses structures, and the coordination of teams of academic and industry experts to deliver. This creates a barrier to the main-streaming of TD education. Our research aims to create a practical approach for Transdisciplinary Engineering (TE) education which can be easily incorporated within existing course designs and in doing so facilitate wider disseminated. This paper presents the design and pilot of a TE session with MRes students from the University of Bath’s, Centre of Doctoral Training in Advanced Automotive Propulsion Systems. The session is evaluated by way of student feedback. The results show broad satisfaction with the session. Six of the eight indicated that they were satisfied with the quality of the session (two students were neutral). All students considered that the course material was presented in a clear and understandable way. All students considered that the course was accessible to their level of understanding. Future work will see the session delivered within additional engineering MSc courses at Bath and internationally with informal agreements in place with Universities in Colombia, Korea and Poland.
Industry 4.0 is causing a lot of changes related to the way people work, bringing a demand for a new worker profile, mainly for engineers, that need to have not only technical skills but also methodological, social and personal skills. So, there is a need to study and identify how the university prepares engineering students for Industry 4.0 jobs. To achieve this objective a literature review was made, twenty-nine skills of Industry 4.0 jobs were identified, and eight active learning methodologies were selected like paths that universities can use to develop skills for the Industry 4.0. To analyze how a university can use active learning methodologies to develop Industry 4.0 skills in engineering students, a questionnaire was applied in four engineering classes of the University of Brasilia, where the professors answered about the active learning methodology used and what skills were developed in the students, and the students answer the questionnaire with what skills they developed. A correlation analysis was applied to detect the different points of view between professors and students. Then, a decision tree was used to identify what skills were most developed by the active learning methodology used by the professor. The results show that are some divergences between the two points of view, and the questionnaire needs to be adaptable to measure with more reliability the skills that the professor wants to develop in each engineering class.
Commonly-known for their sophisticated and robust results, and some lack of time-to-market orientation, the universities are reviewing their roles to be more competitive in the innovation ecosystems. The actual context is large growing of acceleration programs to promote Open Innovation in startups, as well as traditional corporations, interested in the development of innovation across organisational boundaries. Although recent studies emphasise that startups developed or supported by universities have more expectations of success than non-academic startups, the movement of acceleration programs with an emphasis on open innovation is not always connected to universities and supported for research and development. This fact indicates that there are opportunities to encourage the work of universities with companies and other actors for the development of market-oriented proposals and innovative solutions that cover different fields of knowledge through transdisciplinary research. This study has as main objective to identify practices and impacts of acceleration programs for open innovation and its relationship with Research and Development in universities. This study is conducted in two phases in order to analyse the impacts: the first is a systematic review of the literature to identify state of the art of the studied themes in a combined manner. The second phase of the article consists in study two application cases of acceleration programs at the Pontifical Catholic University of Paraná. The work aims to analyse the impacts of the open innovation and acceleration programs found in the literature and in the case study in order to identify opportunities for improvement for the programs of acceleration of open innovation which universities propose or participate. The expected result is to provide subsidies for universities to increase their participation and contribution in programs, to accelerate innovation and open innovation, supported by transdisciplinary and excellent research.
In the wake of environmental disasters and accelerating climate change the challenges facing humanity seem bigger than ever. In the public eye private transport and mobility are two of the most apparent fields in need of a sustainable evolution. Around the globe car manufacturers and developers of innovative mobility solutions are hard at work in shaping the future of transport and travel. Like many modern problems these fields require a transdisciplinary approach and collaboration of disciplines in order to design a solution. At Trier University of Applied Sciences, the student team proTRon has been building highly efficient mobility concepts since 2005 and developing the prototype for a law- and safety-compliant urban vehicle concept since 2015. In this industry-oriented collaboration project the students get the chance to work in a realistic environment emulating a vehicle development process, preparing them for a job in the mobility industry as the next generation of system developers and engineers with a transdisciplinary attitude. Within the framework of this project students acquire competencies in communication and cooperation as well as gain expertise in areas like sustainability, efficiency, and organization. This paper introduces “evoDash”, a human-vehicle interface prototype for the urban vehicle concept proTRon EVOLUTION with a focus on usability and modularity. Designed and developed by students it is a software architecture based on Android and central part of a vision for a transdisciplinary education platform, which provides the foundation for future software and hardware development projects working towards an innovative and sustainable human-vehicle interface. The modular architecture of the platform provides the necessary interfaces and layout options for the functionalities that result from innovative ideas and student projects, embedding them into a usable and individually adjustable framework that will be subject to continuous iterations in order to optimize usability, safety and security. This paper proposes a simulation-based process model focused on rapid prototyping. It aims at providing a possible framework for transdisciplinary engineering projects and education.
Agriculture has always had a great significance in the civilization development. However, modern agriculture is facing increasing challenges due to population growth and environmental degradation. Commercially, farmers are looking for ways to improve profitability and agricultural efficiency to reduce costs. Smart Farming is enabling the use of detailed digital information to guide decisions along the agricultural value chain. Thus, better decisions and efficient management control are required through generated information and knowledge at any farm. New technologies and solutions have been applied to provide alternatives to assist in information gathering and processing, and thereby contribute to increased agricultural productivity. Therefore, this article aims to gain state-of-art insight and identify proposed solutions, trends and unfilled gaps regarding digitalization and Big Data applications in Smart Farming, through a literature review. The current study accomplished these goals through analyses based on ProKnow-C (Knowledge Development Process – Constructivist) methodology. A total of 2401 articles were found. Then, a quantitative analysis identified the most relevant ones among a total of 39 articles were included in a bibliometric and text mining analysis, which was performed to identify the most relevant journals and authors that stand out in the research area. A systemic analysis was also accomplished from these articles. Finally, research problems, solutions, opportunities, and new trends to be explored were identified.
For a company to compete in today’s market, it needs to invest in developing project management tools to help improve its materials, products and production processes, reducing costs and continually improving its activities. This article aims to present the preliminary study performed to implement a custom semantic model in a technology company, which will enable the analysis and diagnosis of the production model to check nonconformities and to track information and materials, aiming at improving its production process and thereby raising its level of competition in the market. The preliminary study corresponds to the first of two phases of project development, which consists of the study carried out in the company to identify improvement needs for implementation of the analysis and diagnosis tool in the production process. For this, a tool development model is being developed with the mapping and the proposal of the model with its implementation strategy. Thus, it was verified that there is a disconnected traceability between the company sectors, information lost at the end of each process step, which eventually increases the time spent in each process phase. To solve this problem, resources were selected that, when integrated, will allow the integration of resources that were not previously connected in the company, in addition to reducing the time spent to close the cycle: connect, collect, analyze and act, making the response of production process activities in real time, seeking the optimization of production.
The interdisciplinary development of smart factories and cyber-physical systems CPS shows the weaknesses of classical development methods. For example, the communication of the interdisciplinary participants in the development process of CPS is difficult due to a lack of cross-domain language comprehension. At the same time, the functional complexity of the systems to be developed increases and they act operationally as independent CPSs. And it is not only the product that needs to be developed, but also the manufacturing processes are complex. The use of graph-based design languages offers a technical solution to these challenges. The UML-based structures offer a cross-domain language understanding for all those involved in the interdisciplinary development process. Simulations are required for the rapid and successful development of new products. Depending on the functional scope, graphical simulations of the production equipment are used to simulate the manufacturing processes as a digital factory or a virtual commissioning simulation. Due to the high number of functional changes during the development process, it makes sense to automatically generate the simulation modelling as digital twins of the products or means of production from the graph-based design languages. The paper describes how digital twins are automatically generated using AutomationML according to the Reference Architecture Model Industry 4.0 (RAMI 4.0) or the Industrial Internet Reference Architecture (IIRA).
Many organizations have redesigned their measurement systems to ensure that they reflect their current environment and strategies. Thus, it is extremely important that the responsible manager knows all the strengths and weaknesses of his organization, having all the maturity axes mapped, highlighting his strengths and weaknesses, to anticipate problems, becoming a company with greater potential competitiveness, because the failure is not to ignore the problem, but to ignore it. Given this, when measuring the Maturity Level Index, you can get an overview of the organization, becoming a radar to know the strengths and weaknesses, thus providing a basis for formulating a decision making and strategy to implement actions to improve performance and organizational maturity. The Acatech Industrie 4.0 (AI4MI) + AHP maturity index has the principle of providing companies with a guide for this transformation, based on the assessment of weaknesses or disagreements with the objective in the action plans, thus obtaining a continuous improvement in the evaluated stages, generating knowledge from the data, to transform the company into an agile organization, with quick decision making and adaptation in multiple business scenarios and different areas of the company. This article presents a preliminary discussion on the benefits of this proposed model for analyzing the measurement of the ACATECH + AHP Maturity Level Index, as to its advantages, results, added value.
In the globalized economic scenario, the ability to adapt to the flexibility of demand is crucial for the longevity of companies. In this context, industrial logistics has a key function in production flexibility. To meet this urging need, the concept of industry 4.0 brings along the use of IoT (Internet of things). Considering the importance of industrial logistics on the flexibilization of production lines, this present research presents a systematic literature review through the application of the PROKNOW-C method (Knowledge Development Process – Constructivist) aiming to understand the use of IoT (Internet of Things) in industrial logistics. The findings can be summarized by four strategical elements that should be leveraged in the decision making process by any company willing to implement IoT in industrial logistics as key factors for implementation success: clear process definition, implementation planning, people training and standardization.
Cyber-Physical Systems (CPS) are systems that link cyberspace with the physical world by means of a network of interrelated elements (sensors and actuators) and computational engines. These different assets make it difficult to design properly and effectively with them all. Additionally, the designing of CPS requires multi-disciplinary project teams and the investigation of all activities which CPS should perform. The cooperation of specialists in only one area is often difficult. One can easily imagine what problems arise when designers from totally different fields have to cooperate. The designers have to share their knowledge and experiences, and to identify assets and activities which are necessary for the proper CPS functioning. Attention has to be paid not only to the process itself, product models, requirements and constraints, aspects of analysis and synthesis, automation tools, and the wider contexts of particular issues but also to the identification of design activities (performed by human designers) and requirements related to them. The proper identification process of the CPS activities allows to improve the design process through more precise and problem-activity-dedicated knowledge and activity-design models management.
Currently, production systems are receiving the application of more advanced, integrated and connected technologies to optimize the performance of their manufacturing processes. The new technological solutions demand architectures that support intelligent solutions for a new digitalized industry. However, production systems already in operation have difficulty in implementing these technologies. The existing barriers limit the availability of the direct integration of different systems contemplated in an automation system architecture. This article systematically reviews the existing literature to portray the characteristics of each architecture and that can guide the adoption of new technologies. Through this review, emerging reference architectures were identified, such as RAMI4.0, IIRA, IBM Industry 4.0 and NIST Smart Manufacturing. In conclusion, the article presents a framework for considering which model best fits with the new technological solutions.
Successful interaction with complex systems is based on the system ability to satisfy the user needs during interaction tasks, mainly related to performances, physical comfort, usability, accessibility, visibility, and mental workload. However, the “real” user experience (UX) is hidden and usually difficult to detect. The paper proposes a Transdisciplinary Assessment Matrix (TAS) based on collection of physiological, postural and visibility data during interaction analysis, and calculation of a consolidated User eXperience Index (UXI). Physiological data are based on heart rate parameters and eye pupil dilation parameters; postural data consists of analysis of main anthropometrical parameters; and interaction data from the system CAN-bus. Such a method can be adopted to assess interaction on field, during real task execution, or within simulated environments. It has been applied to a simulated case study focusing on agricultural machinery control systems, involving users with a different level of expertise. Results showed that TAS is able to validly objectify UX and can be used for industrial cases.
Designing highly usable and ergonomic control dashboards is fundamental to support the user in managing and properly setting complex machines, like trains, airplanes, trucks and tractors. Contrarily, control dashboards are usually big, intrusive, full of controls and not really usable for different users. This paper focuses on the re-design of an ergonomic and compact dashboard for tractor control, proposing an innovative methodology in line with human-centered design and ergonomics principles. The study started by shifting the focus from how a machine works to how a task has to be performed and how the user interacts with the machine. It uses virtual simulations and human performance analysis tools to support the concept generation and the detailed design, and to test the new idea with users in the virtual lab. Indeed, within the virtual environment, different configurations of controls can be tested, checking which controls are mostly used and measuring human performance indexes (i.e., postural comfort and mental workload) for each configuration. Virtual mannequins can be used to as “digital twins” to interact with virtual items and to calculate robust comfort indicators during task execution. The study adopted the proposed methodology to an industrial use case to develop a usable and compact armrest for a new tractor platform. The new armrest is smaller than the previous one (-30% in dimensions), more usable (keeping on board only frequent controls, better positioned), and more comfortable (it satisfies 95% of the population size). This new approach could be used also for the design of new products.