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The dissemination of emerging electronic devices increases considerably alongside with the Internet of Things (IoT) paradigm. Some key elements considered in these devices (e.g. rare-earth) are becoming critical materials and are associated with serious environmental concerns. Therefore, there is a major requirement for designing differently our electronic technologies at the early stages of the research process. Many reports present the promising properties of paper-based electronics as meant to address this challenge. Through technical and life cycle assessments, this article discusses the main design levers in terms of material and fabrication process choices for the eco-design of paper-electronics water quality sensors. Our results suggest conscientious choices of conductive nanomaterials and additive fabrication techniques.

Digitalisation provides many opportunities for process improvements by using smart devices such as Augmented-reality (AR) displays in production. Nevertheless, in-depth studies about the effects of these applications on key performance process indicators are sparse. The goal of this study is to evaluate AR-based remote maintenance processes supported by cutting edge optical head-mounted display technology. A total of 12 test runs conducted with real-world maintenance engineers in a real-world industry setting were analysed based on video recordings and semi-structured interviews. The study identified both case-specific and general issues, and the inherent potential of the technology.

Widespread use of carbon fibre across various industry sectors remains limited due to the high costs of the raw materials and energy demands during production. Furthermore, the environmental impacts associated with its manufacturing process, may significantly reduce the potential benefits of weight reduction or material savings in the end products. Despite the excellent mechanical and chemical properties, which would make the material a viable substitute in a wide range of applications, further production and cost improvements are necessary to raise interest and demand. The scarcity of available carbon fibre production related data and the confidentiality of the few commercial carbon fibre suppliers hinders further research efforts towards these improvements. This paper proposes a dynamic, modular Life Cycle Assessment (LCA) and Life Cycle Costing (LCC) concept tailored for carbon fibre production and is based on a pilot production set-up (120t/year). The model is intended to accelerate the assessment of carbon fibre production and serves as a tool for the exploration of various scenarios, including alternative precursor material, different carbon fibre grades or varying production parameters. In this paper the model is specified, embedded in the environment it is intended to be used and applied to a production setup based on data collected using the pilot scale carbonisation line at Carbon Nexus, a unique, open-access carbon fibre/composite research facility in Victoria, Australia.

Although the increasing use of automation in industry, manual assembly stations are still common and, in some situations, even inevitable. Current practice in manual assembly lines is to balance them using the takt-time of each workstation and harmonize it. However, this approach mostly does not include ergonomic aspects and thus it may lead to workforce musculoskeletal disorders, extended leaves, and demotivation. This paper presents a holistic human-centric optimization method for line balancing using a novel indicator the ErgoTakt. ErgoTakt improves the legacy takt-time and helps to find an optimum between the ergonomic evaluation of an assembly station and its balance in time. The authors used a custom version of the ErgoSentinel Software and a Microsoft Kinect depth camera to perform online and real-time ergonomic assessment. An optimization algorithm is developed to find the best-fitting solution by minimizing a function of the ergonomic RULA-value and the cycle time of each assembly workstation with respect to the worker's ability. The paper presents the concept, the system-setup and preliminary evaluation of an assembly scenario. The results demonstrate that the new approach is feasible and able to optimize an entire manual assembly process chain in terms of both, economic aspects of a well-balanced production line as well as the ergonomic issue of long term human healthy work.

During the last decade, the European manufacturing industry has experienced a growing trend towards customization and personalization. As a response to increasing global competition and changing customer needs, there has been increasing attention to achieving shorter time-to-market, and manufacturing products for smaller market segments. Throughout this paper, the term ‘high variety products’ will be used to describe products that contain at least one product part with a customized geometry. There are two primary aims of this study. First, to illustrate the current challenges that Small- and Medium-sized manufacturers face with high variety products. Second, to explore how these challenges can be addressed systematically. Assembly tasks within existing manufacturing systems for high variety products typically involve a combination of manual labor and automatization. As geometrical variation is considered complex for automation, cost considerations can hinder increasing the level of automation in assembling high variety products. However, this objection might not be legitimate. Hence, this paper proposes a new design method to improve decision making for cost-effectively realizing high variety products. Two core findings of this study include: First, the achievable product variability of a production process depends on the process step least robust to geometrical variation. Second, the adjustability of product design is regarded as an enabler for customization and increased automatization of the production process.

Changes during the product development process pose a high risk of unexpected high implementation effort. To reduce this risk, the impact of engineering changes have to be estimated in advance before their implementation. However, in large systems, the numerous interdependencies often create challenges to the approximation of the implementation effort by inducing complex interdependencies which are often not easy to identify from the start. This paper therefore proposes a method to quickly determine change efforts of complex systems. To be able to estimate change efforts, the dependencies between system components have to be mapped together with their corresponding modeling effort (e.g. modeling time). The SysML (System Modeling Language) system model is a powerful tool to support this process as it offers the possibility of a very individual and versatile data storage. Furthermore, specific data (e.g. calculation time) can quickly be identified with algorithm such as “metachain navigation”. We propose in this paper to use a SysML system model for an advanced documentation of the product and construction structure to be carried out in parallel to the modeling process of a system simulation model (in this case finite-element- and multi-body-simulation). Assemblies and associated components are represented by the product structure, while the construction structure represents the force flow between two components. Furthermore, in SysML individual data, e.g. modeling time and calculation time, is stored in an instance that is connected to a specific component or assembly. As a demonstration example, the approach is shown on a structural dynamic analysis of a powertrain with seven subassemblies and over 100 components. Following the proposed method, the effort of a specific component change of the powertrain can be estimated quickly due to the stored data in the system model.

The efficient execution of process planning activities requires the knowledge from several distinct domains. However, in this context, a common issue is the existence of collective knowledge in the one domain with a lack of networked expertise with other domains. Motivated by this, the paper proposes an approach to support process planning by comparing the generated part design with older, validated products. The utilization of this earlier CAD part models has the potential to reduce development costs, shorten the production start-up time and improve the product quality. The new concept provides the manufacturing personnel with a method for comparing the newly designed part with a pool of validated models to identify the most similar one. Each previous CAD part model is linked with the necessary manufacturing information, so that the initial values for the manufacturing process are available without a time consuming testing phase. The method is divided in three main steps: the global similarity comparison, the segmentation of the part and the local similarity comparison. In the first step, the geometry is projected onto a sphere and then transformed to a matrix. Afterwards these matrices are compared and clustered into corresponding groups. In the following step, a Machine Learning algorithm segments the objects into specific, manufacturing relevant groups. In every cluster, the segmented geometries are again compared for similarity. The combination of the first and the second ranking results in a global similarity hierarchy for the newly designed part. In this paper, the entire procedure is shown with the example of sheet-bulk metal formed parts. This new manufacturing process particularly benefits from this method, as the amount of data is still limited and therefore little expert knowledge exists.

Product variety is a growing trend of offering highly configurable products at the cost of inducing complexity in manufacturing. Joining is a key manufacturing process and historically was a paper-based process with incomplete variety documentation. Nowadays, digital joining element design is a substitution of paper for 3D space. Nonetheless, it remains an ambiguous manual task with limited automation, resulting in time-consuming iterative error-prone development trajectories and costly reworks. This contribution addresses the state of the art in joining element design in both research and industry practice. It reviews product variety and its impact on joining processes. The paper identifies a need for integrating product variety into joining element design and it proposes a solution pathway using artificial intelligence methods.

With digital transformation changing industrial labor drastically, the aim of this paper is to conceptualize a new methodical framework for the production system of the future. For this, mega trends for the industrial work of the future are considered. Existing concepts and tools for production systems are analyzed with regard to the identified challenges of digitalization and future work. The result of this paper is an academically relevant and practically applicable approach for the development of a framework for the digital transformation of the production system. The approach consists of a development process and eleven design principles. The theoretical developments are accompanied by practical applications within the environment of the “Future Work Lab”, an innovation lab for technical, social and organizational changes in industrial labor.

With the introduction of Health 4.0 we face a new era in healthcare and notice the disruption of delivery, adoption and use through newly introduced technology. Wearables have become increasingly important in the medical sector and their remote application and widespread use are significant to the development of technology in healthcare today and the future. The implementation of wearables requires regulations and clinical approval when intended to use for health tracking and monitoring. Within this process designers play a crucial role. Design methodologies are the guideline to accomplish a successful path towards the creation of a new product. In this paper the authors explore and draw from established design methodologies to support the creation of a framework for design of wearables in a health 4.0 context. Identifying the positions of design practices and analyzing the correlations in the context of Health 4.0 is therefore presented within this paper.

Part design is the most important enabler to automate assembly processes. Design work done in companies’ development departments determines most of the product and production costs through material selection and number of components. Part design mostly focuses on functionality but there is still high potential in production processes. To optimize part design for manufacturing and assembly processes first approaches were made between 1960 and 1980. Nowadays, these systematic procedures for optimized component development with respect to production processes are known as ‘Design for Manufacturing and Assembly’ and ‘Design for Automatic Assembly’. Existing part design rules mainly focus on rigid parts. Limp components are avoided in automatic assembly processes, due to limp material characteristics such as strong deformations due to external force or momentum and shape change during manipulation. However, many products, for example automotive wire harnesses, consist of a considerable amount of limp components. A better design for limp components and their joining-partners might be a solution to simplify subsequent automated production processes. The first step therefore is limp component classification. This paper introduces a new scheme of limp component classification oriented towards an abstraction of automated assembly processes. Different limp material characteristics influence several stages of this process. Therefore, relevant limp material characteristics are assigned to the affecting stages. With this classification, the specific challenges in the automated assembly process become clear. This serves as a basis to define challenges for future automated assembly. In addition, the definition of general design rules for limp components concerning automatic assembly becomes feasible. This paper highlights challenges in limp part assembly automation, abstracts automated assembly processes, reviews and discusses first approaches in limp part classification, and introduces a new scheme for limp component classification. The paper concludes with necessary future research based on the proposed limp component classification.

The virtual reality technology (VR) has undergone a rapid development in recent years. The VR software and hardware have become powerful and affordable. Therefore, the VR counts to the key technologies for enabling the digital transformation. However, this significant technology has not achieved the expected breakthrough in the industrial engineering area yet. The potential of the VR to digitize and to improve the engineering process of industrial companies especially for SMEs is still undiscovered. This has led to a poor implementation and use of the VR applications with an engineering scope compared with other business sectors e.g. gaming, entertainments. This paper presents and discusses two case studies achieved within cooperation project between the University of Applied Sciences Karlsruhe and German manufacturers for fire trucks and systems for firefighting and disaster protection. The aim of the case studies is the implementation of VR applications and their evaluation in terms of using in the business processes of the involved industrial partner. Based on the experiences gathered during this cooperation project a CAD Data transformation process for an industrial VR application as best-practice approach will be outlined and discussed in this paper. © 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/3.0/ ). Peer-review under responsibility of the scientific committee of the 27th CIRP Life Cycle Engineering (LCE) Conference.

Product development (PD) faces uncertainties caused by rapidly developing technologies, shifting market demands and the changes occasioned by these developments, including new requirements for products being developed and increased difficulty for companies to reliably execute state-of-the-art processes. In this paper, we argue that classic PD risk management methods and tools are based on the ‘predict and plan’ paradigm, which assumes that organisation members involved in PD have sufficient time and resources to identify, analyse and mitigating technology risks and organisational risks. However, the reality of product development is that time and resources are rarely sufficient, and uncertainty is currently being introduced to the development process at an accelerated rate by trends such as pervasive digitalisation. This paper therefore investigates a resilience-inspired approach to PD risk management that abandons the predict and plan paradigm in favour of a ‘monitor and adapt’ approach. We argue that, in industrial practice, predict and plan approach is the de facto risk management baseline, and suggest deliberately tailoring risk management and PD processes to incorporate resilience-based practices. To that end, we provide suggestions for process frameworks and tools organisations may adopt and discuss how resilience and risk management are complementary approaches to traditional PD. Our arguments are supported by a case study of an engineering organisation and additional interviews conducted with members of similar organisations for purposes of validation. © 2019 The Author(s). Published by Elsevier B.V.

Industry 4.0 and the Smart Manufacturing paradigm are rapidly transforming the way business is conducted in the manufacturing industry. The underlying core technologies of the emerging digital transformation include the Internet of Things (IoT) and data analytics. While the shop floor is the main focus of these paradigms in the narrow sense, it is becoming more prevalent for other companies or business units along the digital supply network to investigate the potential to improve their processes by leveraging these technologies as well. One area that is traditionally reliant on human operators and optimization is the trucking industry. In recent years, this industry has started to explore how the above-mentioned technologies can be utilized to improve their operations, and new policies are further amplifying this process, e.g., by mandating Electronic Logging Device (ELD) to be used by commercial drivers in the USA. This development forces companies to collect digital, high-resolution data – and the question emerges how to utilize this data in the most value-adding way. In this paper, we analyze the current state of the art of digital transformation in the trucking industry by conducting a bibliometric study of recently published papers to identify the main research areas and themes in this field, the leading authors, countries, and journals in this domain. This work will provide the basis for further in-depth studies on optimization techniques and available case studies to provide theoretical input for practitioners and scholars.

Current developments in production systems and production control will lead to a significant change of their connection to product development. A representative example of these developments is the concept of self-organizing production systems. This paper focuses on appropriate changes of the development process evoked through recent developments in production. The paper summarizes process changes and opportunities for the development process, which include the vision of self-organizing production systems, its challenges and opportunities. Consequences are estimated for established development methodologies like the V-model and aspects of Systems Engineering.

There has been a great deal of research interest in applying industrial symbiosis in the food manufacturing industry as part of the industry-wide shift towards sustainable manufacturing. However, an evaluation of its participation rates first requires an in-depth understanding of the factors that influence the manufacturers’ waste management behaviours and decision-making process. This paper attempts to propose a comprehensive waste management behavioural framework for the food manufacturing industry by building on the works of previous waste management behavioural studies, most notably Young et al.’s work on employee pro-environmental behaviour. The proposed framework was validated through an exploratory survey conducted on a representative group of waste managers from Singapore’s food manufacturing industry. Using exploratory factor analysis, we identified Intention, Perceived Moral Obligation, Company Structure, and Situational Barriers to be the most significant factors influencing the waste manager’s waste management decisions. Based on these results, several policy recommendations were proposed which focus on the education of industrial symbiosis to the leaders of the organisation. The findings from this paper will provide valuable insights into the manufacturer’s waste management decision-making process, as well as a more human-centric framework for the conduct of future industrial symbiosis studies in the food manufacturing industry.

Industry is continuously searching for solutions to increase flexibility and quality in parallel with cost reductions. This paper presents a case study of using set-based design method to develop a gripping system for an innovative three-dimensional bending and forming technology of extruded aluminium profiles. Traditionally, profiles are formed by mandrel-based stretch-bending to improve cross-sectional stability and spring-back, sometimes combined with subsequent calibration e.g. by hydroforming. However, in the highly competitive automotive industry, where light-weighting is high on the agenda, design and process flexibility, tooling cost and dimensional accuracy are important factors to increase value at a reasonable cost. In this paper, a set-based concurrent engineering approach is used to identify, evaluate and prioritize gripping methods to enable three-dimensional bending meeting automotive requirements for dimensional accuracy. The results demonstrate a multitude of options, providing trade-offs between flexibility and function. Further work will be to build a physical demonstrator to validate output from the set-based method used to systematically narrow down the solution space.

This paper presents a methodology and the associated tool for enhancing decision making in shop floor layout using collaborative virtual reality, associated to real-time performance indicators in Industry 4.0. It first describes the collaborative architecture of the application. Subsequently, application features like: visualization at scale one (machines, industrial environment’s top view, product flow path), 3D model interaction (setting layout), physical process flow evaluation (spaghetti diagrams, Key Performance Indicators-KPI), testing multiple configurations (via save and load). Finally, paper illustrates possible usages and benefits of how VR tool helps improve ergonomics and safety; helps reduce deliberation time and bottlenecks through machine spatial footprint, visualization, scale one experience and referring KPIs.

Since the first industrial revolution manufacturing systems have been considered well-defined socio-technological entities that extract resources from the natural environment in order to create goods for the satisfaction of human needs. Productivity gains stimulated by technological innovations such as electricity and computers are inherent to the system. Whilst digitization depicts the latest paradigm, other technology leaps have virtually been neglected in traditional manufacturing science: biomimetics and biotechnology. In this context, we present the concept of a biointelligent industry outlining the vision of a naturally consistent subsistence strategy. Future industrial activities are expected to no longer extract resources from the environment but apply nature as a manufacturing utility. From a scientific point of view many issues, however, remain unanswered. In this paper we thus present fundamentals of a biological transformation from a manufacturing standpoint based on recent research. Thereby we define this novel field of research, discuss its impact on traditional patterns of thought, provide a selection of technology, process and system examples, and present 10 fields action in terms of future research, industrial investment, policy initiatives, and societal involvement. The paper sets the basis for extensive further research and discussion within the manufacturing community.

Due to the increasing demand for flexible and low-cost production, manufacturing solutions involving human robot interaction have become much sought-after. Robotic manufacturers meet the demand with a rising number of low cost robots specifically designed around safety and usability. However, the programming is still based on a tool centric teach-in. This paper discusses an affordance based approach for process programming in industrial manufacturing. Using low level feature detection and a consecutive evaluation, a fast programming method for industrial applications is presented. The paper presents the concept and a prototypic implementation for a welding process. Using the affordance detection, the system is able to identify relevant seams based on an image of the work space. The identified seams are then presented to the user for review with the means of augmented reality. Lastly, the system derives a welding program based on the detected seams. First experiments show promising results concerning programming speed and path accuracy for different work piece shapes and task definitions. Finally, based on the experience gained with the prototype, the outlook discusses the possibilities and further fields for future work.

Even though Industrie 4.0 is a popular topic in the manufacturing industry, many enterprises especially small and medium sized ones are not aware of the scopes of this topic. As a result, they do not know how to evolve towards Industrie 4.0. Often the first advancement attempts fail due to a lack of knowledge of the interdependencies between the three dimensions of the sociotechnical approach (technology, organization, employees). Therefore, this paper introduces a concept for an evolutionary maturity based migration model, which guides enterprises on their way to Industrie 4.0 in due consideration of the dimension‘s technology, organization and employees. The migration model uses a set of maturity levels which are designed in distinct quantities of characteristics for different criteria. In total the model contains more than forty of these criteria. With the assistance of this model enterprises are able to first locate their current state in the different production related criteria and afterwards perceive and set their next objectives. In this context, the model also considers dependencies of assorted characteristics of the criteria, and thereby reveals potentially next steps for the enterprises on their way to Industrie 4.0 and further necessary steps that have to be accomplished beforehand. The main goal is to enable especially small and medium sized enterprises to evolve towards Industrie 4.0 without utilizing external consulting. Hence the paper will begin with a description of the underlying holistic perspective consisting of the sociotechnical approach, the consideration of the individual situation and the strategic goals. Subsequently the development process of the model will be set out. Afterwards the developed migration model will be presented and the different parts as well as their purposes will be described. The paper will finish with a short report on the validation of the model in practical applications within real enterprises.

Increasing product variety and the shortening of product lifecycles require a fast and inexpensive reconfiguration of existing manufacturing automation systems. To face this challenge one solution is a Digital Twin, which can be used to reduce the complexity and time of reconfiguration by early detection of design or process sequence errors of the system with a cross-domain simulation. For engineering the Digital Twin and systemically synchronizing the data of mechatronic components in the interdisciplinary engineering models of a Digital Twin during the life cycle of manufacturing automation systems, this paper presents a concept for the engineering of a Digital Twin based on model integration in a PLM IT-Platform and an Anchor-Point method to systematically detect variances of the mechatronic data structure between the digital models and the physical system. The data of a mechatronic component from interdisciplinary domains, developed by the corresponding engineering tools are referred to as anchor points. This paper analyses domain-specific challenges in automation software-code to develop an assistance system for rule-based consistency check and for synchronizing the engineering models of the Digital Twin of the manufacturing automation system based on the Anchor-Point method.

The paper discusses experiences from a concurrent product- and automated assembly process-development in a manufacturing company from early design to design freeze. The product is a compact product consisting of a plastic casing housing electronic components which is currently entering production. The company is a high-tech manufacturer operating in a high-cost country delivering safety products in a business to business market. The case study is based on project documentation, analyses of product and assembly concept, lab tests as well as dialogue with the manufacturer and the product designer. The main author was involved in the automated assembly process development and Design for Automatic Assembly (DFAA). The product and the automated assembly line were designed in parallel, throughout the entire product development process; from idea and concept development until the pre-production stages. In the early stages of the project the product was redesigned on a frequent basis, and each new design was evaluated for its automated manufacturability. In this process several DFAA methods were applied. The product designers also produced several prototypes by a plastic additive technology (3D printers) that were assembled in a prototype automated cell to assess product design and assembly solutions, and to reveal weaknesses that were not detected in the analysis. This paper compares the different DFAA methods used such as DFA2, as well as a custom DFAA review spreadsheet. Additionally, the paper discusses the interaction between product design and production process design, and effects on the outcome. Finally, the paper suggests design process improvements and guidelines.

Within their lifetime, products and processes pass through characteristic periods, which can be divided into distinct phases, such as design, production, use, and disposal. Specially, the production phase of products consumes a great amount of energy, non-renewable materials, renewable materials, ancillary inputs, and fossil fuels. Moreover, significant amounts of emissions (wastes, effluents, and greenhouse gases) are generated, which lead to sustainable impacts, such as extra costs, environmental damages, social issues. Through a systematic overview of resources and emissions during the production planning process, potential sustainable impacts can be identified and possibly avoided. The paper presents a concept for a fuzzy inference model to evaluate production programs for short- and mid-term production planning according to sustainable indicators. For this approach, the paper presents criteria to select applicable measurements for sustainable production planning, three categories of sustainable indicators to evaluate production programs, a procedure to develop the fuzzy inference model, and possible actions for optimizing production programs to increase the degree of sustainability. In future works, the fuzzy inference model will be implemented in enterprises to demonstrate the benefits of sustainable production planning.

The development of assembly manufacturing systems of complex products, such as automotive vehicles, needs systematic approaches. This paper proposes a new development method based on hierarchical modeling of a complex product and its assembly processes. The method integrates product and process for assembly system development by decomposing a complex product according to its hierarchical architecture in a product domain and creating the respective assembly flows in a process domain. Based on the integrated product-process hierarchical model, this paper presents three steps of manufacturing system development: 1) to plan overall assembly system flow, 2) to configure subassembly lines, and 3) to design the functionality and processes of main assembly workstations. The paper demonstrates and discusses the first two steps of assembly system development with examples. This method can make assembly manufacturing development more systematic, standardized, and efficient. The method also promotes product design variety and modularity for DFM.

Augmented Reality (AR) technology for maintenance aims to improve human performances by providing relevant information regarding both corrective and preventive maintenance. The development of an AR system involves the choice of a hardware, a development software and a visualisation method. These selections are challenging due to the wide choice of services and options available which result in fragmentation: different development processes and different user experiences. In order to ease the selection of an AR system for supporting maintenance operations, this paper proposes an innovative process. It guides the reader to identify the requirements and the constraints for any specific application through a number of questions developed in this study to help with the selection. This results in suggestions for the selection of the hardware, the development software and the visualisation method. The process is built based on a literature study, grey documents and experts interviews. Future works includes the validation of the selection process proposed in this project. It could be done by comparing the choices made using the proposed process with the choices made by experts for the same case study. Moreover, the decisional process could be extended to face the economical and ergonomics aspects related with the selection of an AR system. It could be done expanding the literature research including studies which investigate into the economical and ergonomics consequences of the application or AR for maintenance. Paper presented at The 5th International Conference on Through-life Engineering Services (TESConf 2016)

The life cycle of complex products is subject to multiple uncertainties. Designers include margins into the product to cater for these uncertainties: safety margins, which is typically included in the requirements against the uncertainties of use and design margins against the uncertainties of design, such as changing requirements or engineering change. In practise the terms design margins and safety margins are sometimes used interchangeably. At the end of the design process, a product might include considerable overdesign, which can increase the initial cost as well as the running cost of many complex systems. Late discovery of both overdesign and lack of safety margins are also expensive to deal with in late phases. This paper explore the role of safety margins and design margins in the design process based on two case studies in truck design and jet engine component design. The paper shows that margins are added both to the requirements and the design parameters, so that companies run the risk of duplicating margins throughout the process without different teams being aware of it. This paper argues that a clearer and common description of design margins can reduce undesired iteration in development processes arising from misconceptions and aggregation effects in the development of complex systems.

The Set-Based Concurrent Engineering (SBCE) is the methodology that can improve the efficiencies and effectiveness of product development. It is found that the SBCE approach provided a suitable knowledge environment to support decision making throughout the development process. This paper presents the potential tangible benefits gained from the application of the SBCE in an industrial case study of a Surface Jet Pump (SJP) that is used to revive the production of oil/gas from the dead wells. The well-structured SBCE process model and the process of identifying the potential benefits proposed in this paper will clarify the gap in the development of the SBCE in the company. The potential tangible benefits are established in a few key areas such as product innovation, product performance, manufacturing cost, and project success rate.

This paper presents and briefly describes the methodology used to get the systems and conceptual design of a train cab front cleaning robot. While the sides of the trains are cleaned by a mechanised washer, the cab fronts are cleaned manually which imply a number of health and safety issues. The aim of this project is first to carry out an analysis of the current procedures in order to detect the possible gaps in the process, generating a list of requirements that will make possible the conceptual design of a cleaning system that fulfil those requirements. The proposed solution includes the division of the system in various subsystems where different solutions for each subsystem will be considered, analysed and selected as a final option to develop a prototype. This paper focuses in the main structure of the robot that holds the end-effector; different conceptual designs are shown that comply with the requirements set in the systems design.

In Germany the growing demand for customized systems and integrated solutions in machinery enhance the importance of special machinery. Within this industry, the commissioning process represents a significant part in the product engineering process and forms the base for reliability and performance during future operation. However, there is little research focusing on this process for special machinery. In particular, there has been little discussion on methods to evaluate alternative test processes or arranging test processes along the commissioning process. Therefore, this paper develops an application-oriented simulation tool that allows an evaluation of test alternatives and an arrangement of test processes during the commissioning process in special machinery. The authors decided to use Bayesian Networks to model the commissioning process as they enable the connectivity of multiple modules and integrate the stochastic dependencies along the processes. In addition the paper reveals two concepts to deal with unknown processes and the lack of data. Applying the simulation tool in a laser system manufacturer reveals that the simulation tool allows an evaluation as well as the identification of risks and need for countermeasures.

It has become common practice to apply simulation during product development and production planning. The increasing demand for individualized goods requires the ability to produce in small lot sizes and therefore more flexible resources, which leads to the use of cyber-physical systems (CPS) in manufacturing. This papers aims to look at the changing requirements, pitfalls and possible solutions when applying simulation to CPS. The research is based on a case study of a large car manufacturing company that has already implemented CPS in one production line. The paper will also provide an overview of simulation types and discuss their fitness.

Modern aircraft are more integrated with advanced systems functionalities, which result in ever-increasing aircraft complexity, further development difficulties and development delays. These system complexities are mostly in the form of system interactions that make it difficult to understand the overall system characteristics. At the early stages of final assembly line (FAL) design, one of the most important objectives is to arrange the installation and test tasks from components to sub-systems and systems in the proper sequence to meet the designed functions and prevent hazards from the integration process. Improper sequencing of the final assembly process will cause rework, time delays, cost and potential safety risk in development. In the field of final assembly line design, previous research has mostly focused on assembly line balancing or supply chain design based on structural parts assembly. However, these approaches do not consider the early final assembly line definition or test allocation for system functions. In this paper, the research proposes a method based on a systems engineering view and integrated computer aided design (CAD) to help better understand system interactions and generate viable final assembly process sequencing. This research aims to develop a concept of unified master data for final assembly design, which contains 3D geometrical CAD, system functions and interaction characteristics. The paper will present the methodology framework, key concepts and associated industrial software packages for implementation. The paper concludes with further discussion of an initial case study.

This paper presents an approach for a model-based planning process for the early phases of manufacturing system planning (MSP). The goals are a better integration of MSP with product development (PD) in the early design phases and an improvement of the coordination of the MSP-related planning disciplines. The presented approach is based on model-based systems engineering (MBSE) and is supported by a modeling scheme which uses the systems modeling language (SysML). The approach consists of a process description of the MSP and of different so called SysML views which describe the information artifacts of each MSP step. It is divided into four different modeling levels that describe the manufacturing system's structure and behavior from different points of view. In order to validate the approach, an exemplary cylinder head production was modeled. Extractions from this example are shown as SysML-diagrams. To conclude the paper, the advantages and disadvantages of using a model-based planning approach with SysML for MSP are discussed.

Implementation of lean manufacturing in any type of organizations can bring many benefits, such as reducing waste and improving operating efficiency. However, lean implementation is not a straightforward process. Although a number of frameworks have been presented, still many companies find it difficult to implement lean. Furthermore, most of these roadmaps are for large manufacturing companies, and not for small and medium enterprises. Unfortunately, there is not a recipe that if used can guarantee a successful implementation. Furthermore, unsuccessful implementation can have a great impact on organization's resources, but even more importantly, affect employees and their confidence in lean philosophy. In the present paper, the most prominent lean implementation frameworks will be discussed, under the prism of the needs of SMEs. The challenges for the SMEs in their lean journey are discussed. Paper originally presented at Manufacturing Systems 4.0 – Proceedings of the 50th CIRP Conference on Manufacturing Systems, held 3 – 5 May, 2017, Taichung City, Taiwan.

The paper addresses intelligent and sustainable production in the sense of combining and integrating online predictive maintenance and continuous quality control. The rationale for combining and integrating them is that continuous quality control can provide input to the online predictive maintenance in cases where no signs of maintenance issues have been indicated and inadequate output is produced (and the process parameters cannot be adjusted in order to meet the output specifications). The paper outlines the first part of an action research effort at Gestamp HardTech AB in Sweden, whose objective is to keep its position as a world-leading provider of press-hardened vehicle parts. The first initial design criteria concerned with simplicity and low-cost was changed after learning more details and what can be accomplished, and the updated first design criteria focused instead on robustness, high-quality output and future-proofing. The intermediary result is an action plan for the technical change, whereas the organizational change will be addressed later during the action research effort.

In response to diversified needs in the market, the manufacturing industry is required to provide more user-oriented products and services than ever. In order to satisfy such needs, much attention has been paid to personalization, which, in this paper, refers to the process of designing, manufacturing, and providing different products and services for each individual user. There are key enablers to foster personalization because of technological advancement. Since personalization is considered an approach to prolonging the value lifetime of a product and minimizing resource input, it should be further discussed in the field of lifecycle engineering. To realize personalization, a methodology to design such products is essential. We call such design as “Personalization design.” The goal of this research is to develop a theory for personalized design. In this paper, we propose the concept of personalization in the context of product and service design including a life cycle perspective. We firstly show examples of personalization and their characteristics as context, target phase and participation. This is followed by a presentation of the concept of personalization. Then, we show how the actual personalized design system was designed through a case study on designing equipment for rehabilitation hospital. In this case, participation of multi-stakeholder has a great influence on a design solution. Finally, we discuss the future direction of design research for personalization.

The application of cloud storage and Case-Based Reasoning (CBR) technology in bending process is researched in this paper. Firstly, some of the essential features of cloud computing are briefly discussed with the end-users. Enterprises use the cloud as a platform to store data and support the Case-Based Reasoning technology, for which the core parts are case retrieval and case revise (reuse). Next, the difficulty of evaluating weights of condition attributes in case retrieval and the insufficiency of case revise strategies are stated in the paper. A new instance of the similarity and instance attribute weight calculation algorithm is introduced to solve the problems of similarity measurement and weights assignment in Case-Based Reasoning. Finally, the workflow for Case-Based Reasoning of database is analyzed, and the effectiveness of using this method to determine the recommended in the bending process parameters is demonstrated. Also the importance of knowledge reuse is reflected.

Current trends in manufacturing focus on the use of Information and Communication Technologies (ICT). The physical world and its virtual representation are increasingly converging, which leads to Cyber-Physical Production Systems (CPPS) in the manufacturing environment. CPPS synergize conventional production technology as well as ICT, allowing machines and products to exchange information, trigger actions and control other components autonomously. Therefore, seamless communication between physical objects of the shop floor and various computer systems is required. The Reference Architecture Model Industrie 4.0 (RAMI4.0) provided by the Plattform Industrie 4.0 specifies requirements for CPPS consisting of Industrie 4.0-components. In such systems, a major goal is to enable communication of I4.0 components among each other via industrial networks. For this purpose, RAMI4.0 suggests that each component has a virtual representation and uses Service-Oriented Architecture (SOA) based communication with I4.0-semantics. This paper describes a systematic approach to OPC Unified Architecture (OPC UA) information model for representing the static and dynamic behavior of manufacturing systems. Moreover, the approach is generic in the sense that it can be used to define information models for multiple target technologies, such as OPC UA, MTConnect and others. It even allows to reuse large parts of the generated models for similar manufacturing utilities and various target technologies. Therefore, we first present a concept for system analysis and design by using the Unified Modeling Language (UML), which is widely accepted for interdisciplinary work. The information gathered is then transformed to OPC UA information models which serves as target technology in this paper. The purpose of this approach is to simplify the process of defining virtual representations of manufacturing systems. Applying the presented concept allows transformation of classic manufacturing systems into CPPS with SOA-based communication and semantically rich virtual representations of individual components. It is therefore well suited to meet the requirements specified by RAMI4.0.

Over the last decades, one of the steadiest challenges for manufacturing companies is the need for reduction of time-to-market and for enhancement of the efficiency of their product engineering process (PEP). Triggering factors are changing customer demands, shorter technology cycles that enforce product changes and a noticeable market saturation. Hence, companies need to increase the efficiency of the PEP despite considerable improvements in this field such as concepts of simultaneous engineering and digital factory. Today, the three main phases of the PEP (product development (PD), manufacturing system planning (MSP) and manufacturing) are still performed sequentially. Due to already existing improvements in parallelizing steps of the PEP, efforts for further improvements should concentrate on the interface between MSP and PD. Traditionally, MSP starts after PD is completed. Thus, on one side, information regarding the product's manufacturing is withheld from product developers. As a result, decision making assistance for selection between design alternatives is not available. On the other side, MSP is not able to influence the product design. This leads to more expensive or not manufacturable products. This paper presents an innovative approach for an integrated MSP based on fuzzy information from early phases of PD. It solely uses information from specification phase and conceptual design phase of PD within the first steps of MSP. The approach aims at noticeable improvements e. g. more frequent feedback loops, reduction of expensive correction loops after product development, and a smooth manufacturing ramp-up. The paper summarizes the theoretical foundations for PD and MSP, highlights the need for research, and outlines further steps for the concept development. Additionally, early phases of PD and MSP are described and investigated in more detail with regard to links between the two domains. The basis for the development of a concept is given which aims at an early start of MSP and more efficiency within the PEP.

“Additive Manufacturing” (AM) is an emerging, highly promising and disruptive technology which is catching the attention of the Defence sector due to the versatility it is offering. Through the combination of design freedom, technology compactness and high deposition rates, technology stakeholders can potentially exploit rapid, delocalized and flexible production. Having the capability to produce highly tailored, fully dense, potentially optimized products, on demand and next to the point of use makes this emerging and immature technology a game changer in the “Defence Support Service” (DS2) sector. Furthermore, if the technology is exploited for the Royal Navy, featured with extended and disrupted supply chains, the benefits are very promising. While most of the AM research and efforts are focusing on the manufacturing/process and design opportunities/topology optimization, this paper aims to provide a creative but educated and validated forecast on what AM can do for the Royal Navy in the future. This paper aims to define the most promising next generation Additive Manufacturing applications for the Royal Navy in the 2025 – 2035 decade. A multidisciplinary methodology has been developed to structure this exploratory applied research study. Moreover, different experts of the UK Defence Value Chain have been involved for primary research and for verification/validation purposes. While major concerns have been raised on process/product qualification and current AM capabilities, the results show that there is a strong confidence on the disruptive potential of AM to be applied in front-end of DS2 systems to support “Complex Engineering Systems” in the future. While this paper provides only next-generation AM applications for RN, substantial conceptual development work has to be carried out to define an AM based system which is able to, firstly satisfy the “spares demands” of a platform and secondly is able to perform in critical environments such as at sea.

Manufacturing Complexity has been extensively reported in the literature in the ways it can be classified, modelled, assessed and measured. However, the use of complexity measures for shop floor decision making has not been studied exhaustively. The paper demonstrates the use of a complexity measure for shop floor decision making. Knowledge of the transition of shop floor complexity into undesirability can give a correct indicative for any decision maker to intervene and take the necessary corrective actions to bring the system back to its desirable state. The current paper presents an information-theoretic approach based model which considers production scheduling, maintenance and quality functions simultaneously to come up with a complexity quantifier for a shop floor. At any point in time, various environmental factors like machine failures, corrective maintenance time variability, due date alteration, process shifts etc. are simulated into the future and their effect on the job states both in terms of schedule and quality are observed. The probability of these state occurrences is then quantified as complexity of situation which is subsequently scaled to a penalty based “undesirability index”. The complexity is re-evaluated every time a fresh event occurs, thus enabling the decision maker to be more predictive about the future state of the system and in turn, the performance of each of the manufacturing functions. Thus, the model so developed, deploys a complexity based look-ahead mechanism for identifying undesirable state transitions. The novelty of the work lies in the way it has been developed keeping the perspective of a shop floor manager in view and also in the way it can be readily used for decision making.

Constraint stimulates creativity and is the key to understanding complexity. The benefit of the constraint-based problem is that it can spark ideas for new knowledge, new possibilities, and new opportunities. In every design, boundaries, controls and restraints exist. The constraint model in this paper shows the relationship among Form-Fit-Function (F3), Functional Analysis Model (FAM) and Su-Field. The constraint-based techniques improve problem solving in the preliminary design and satisfy ideal conceptual design. Constraints lift and improve creativity by reframing problems in a creative way. The best way to visualize constraints is by adopting design parameters and embedding them in the conceptual design stage, and continuously diagnosing them to ensure that the design does not violate the constraint requirements. This paper aims to model design constraints as a criterion for generating creative ideas and solutions, and suggest as a systematic entity in the conceptual design process. The model will be useful as a guide for developing an understanding of constraints in the conceptual design process.

This paper describes development of a novel ambulance simulator implemented at the Nursing department at NTNU Gjøvik and effects of its use for educational purposes. Cultural aspects of the simulator implementation are also discussed. The article covers peculiarities of the simulator development process and also description of relation of modern educational techniques (learning factories) to the application of similar novelties within the learning process. The construction, purpose and educational effects gained after implementation of simulator are described. The paper can serve as further research basis on topics of the simulators creation and modern educational techniques use. © 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC-BY-NC-ND 4.0 license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

For many years there has been considerable research from both an academic and industrial perspective into the monitoring and control of CNC machining processes, and progress has been well documented. It is widely acknowledged within the CIRP community that collection of information into the performance of material cutting processes is a worthwhile research topic, and this is mirrored in the work of the Scientific Technical Committee-Cutting (STC-C) and other Scientific Technical Committees. This work has been continued by the consortium engaged in the REALISM project, an EU-FP7 funded project which is investigating the use of sensor fusion in a real time production environment, to monitor CNC tool wear through the use of three sensor technologies- Force, Acoustic Emission and Vibration. However, the real work of the project consortium will be in the analysis and interpretation of the data from the collated fusion of the deployed sensors- and the intelligent interrogation of this sensor information. The sensor deployment strategy of this project was outlined in a presentation, poster and paper presented at the 2014 CIRP ICME conference and this current paper provides an update on the ongoing work. An overview is provided in this paper of the challenges that have been overcome as part of the REALISM project, and a brief overview of the initial verification trials that were undertaken on the deployment of the sensors. Further results will also be presented that show promising initial sensor data, which shows conditions leading to Catastrophic Tool Failure (CTF).

With the increase in demand for biopharmaceutical products, industries have realised the need to scale up their manufacturing from laboratory-based processes to financially viable production processes. In this context, biopharmaceutical manufacturers are increasingly using simulation-based approaches to gain transparency of their current production system and to assist with designing improved systems. This paper discusses the application of Discrete Event Simulation (DES) and its ability to model the various scenarios for dynamic decision making in biopharmaceutical manufacturing sector. This paper further illustrates a methodology used to develop a simulation model for a biopharmaceutical company, which is considering several capital investments to improve its manufacturing processes. A simulation model for a subset of manufacturing activities was developed that facilitated ‘what-if’ scenario planning for a proposed process alternative. The simulation model of the proposed manufacturing process has shown significant improvement over the current process in terms of throughout time reduction, better resource utilisation, operating cost reduction, reduced bottlenecks etc. This visibility of the existing and proposed production system assisted the company in identifying the potential capital and efficiency gains from the investments therefore demonstrating that DES can be an effective tool for making more informed decisions. Furthermore, the paper also discusses the utilisation of DES models to develop a number of bespoke productivity improvement tools for the company.

Manufacturing companies face high demand for products that fulfil individual customer desires. Recent improvements in additive manufacturing (AM) enable the fabrication of customer-specific components of a product. This paper presents a categorisation of design processes for customised and personalised products through the use of AM in three process types: special design, specific adaptation, and standardised individualisation. The characteristics of design processes are examined in medical development of vascular models integrated into a modular neurovascular training setup. The paper considers how initial customer involvement and preplanning of customer-specification influence the design process for varying degrees of individualisation enabled by additive manufacturing.

From the absence of standardization regarding components of battery systems for electric vehicles results a large number of theoretically applicable battery configurations for a given application. This leads to decision making problems and expenditure of time during development processes. This paper presents a method that automates the electrical and mechanical design process of battery systems to identify applicable battery variants. The design automation is coupled to an evaluation tool that allows variant selection regarding product and process characteristics such as power, energy or ease of assembly. The paper closes with a use case of a medium sized electric vehicle.

A comprehensive, systematic planning method to design mobile Augmented Reality (AR)-applications in the range of production planning is not available. A target driven development process to match mobile AR-applications to the methodical needs of production planners is therefore proposed in this paper. The development process will be presented with special focus on the user integration. The incorporation of production planners, their intrinsic knowledge and engineering methods needs to be considered. Therefore, the paper will introduce how user relevant aspects will be identified and considered during the application development. Video abstract Download : Download video (3MB)

Life cycle engineering (LCE) methods are essential in the development of next generation energy storage systems in order to avoid harmful unintended environmental consequences. Moreover, the integration of life cycle knowledge early in the development stage of such technologies can lead to improved performance in regard to their environmental impact. Extensive information from all stages is needed to understand interdependencies along the life cycle, e.g. between required raw materials, applied processing parameters and lifetime behaviour of the battery. From an LCE perspective, the development of detailed and representative inventories for the assessment of traction batteries is a time and resource intensive process, which requires a difficult synchronization with product development activities. A cyber and physical integration of Life Cycle Technologies in a product system offers the potential to reduce data collection efforts while enhancing its robustness and reliability. Life Cycle Technologies can refer to any product- or process- integrated data acquisition technology, e.g. sensors, which can be leveraged to provide knowledge about a product’s life cycle performance. In this paper, we introduce the concept of Life Cycle Technologies and their potential to maximize the functionality of traction batteries while reducing their life cycle environmental impact. Furthermore, we present a reference architecture aiming at the development and integration of such technologies. Finally, we illustrate its application in a case study of All Solid State Batteries and discuss its usability in the development of new generation battery systems.

Various triggers in manufacturing operations lead to engineering changes, such as the conversion of a machine or changes in the factory layout. In companies, the priority is often to avoid engineering changes as they are time-intensive and lead to change costs. If changes cannot be avoided, the implementation must be simplified and accelerated as much as possible. This can be achieved through structured, efficient change processes, which are specifically supported by methods and tools. Augmented Reality (AR) and Virtual Reality (VR) show great potential to facilitate processes and to improve collaboration in the context of engineering changes. By combining these methods and tools, the implementation time of engineering changes can be shortened, and the likelihood of cost-intense planning errors can be reduced. Therefore, the objective of this paper is to present an approach which identifies whether AR and VR are suitable to support the engineering change process steps. The goal is to support the process of recording the current layout, identifying machines, determining the material flow, and visualizing this information and thereby simplify and accelerate the engineering change process. Furthermore, potential collaborations between AR and VR in each engineering change process are identified and described.