An Engineering Process model for managing a digitalised life-cycle of products in the Industry 4.0

The Internet of Things (IoT), and more specifically the industrial IoT, is revolutionising industry. This technology has catalyzed the fourth industrial revolution and inspired movements such as Industry 4.0, the Industrial Internet Consortium and Society 5.0. Morphing an industrial process or assembly line to aggregate Internet-connected devices and systems does not complete the picture. The concept penetrates all aspects of the engineering process (EP) which encompasses the full lifecycle of the product/solution. Phases of the EP traditionally tended to be sequential but, with the IoT, can now evolve and influence other phases throughout the product/solution lifecycle. The EU-funded Arrowhead Tools project aims to promote a service-oriented architecture (SOA) to allow tools within each phase of the engineering process to interact with each other. This paper, applies the proposed EP model to a real value chain composed of multiple stakeholders adopting different EPs for the life-cycle management of a Smart Boiler System

Facilitating the Implementation of Smart Maintenance

Innovations and rapid advancements in digital technologies in the manufacturing industry are setting high expectations of highly automated, intelligent and interconnected production systems. To bring these expectations to realisation and secure productive and sustainable production systems, maintenance organisations must develop accordingly. Thus, there is a need for organisational innovation in maintenance.The way in which maintenance is organised in digitalised manufacturing is called “Smart Maintenance”, and industrial companies need evidence‐based guidance in pursuing such an implementation. Thus, the purpose of this thesis is to facilitate Smart Maintenance implementation. To this end, the thesis aims to support organisational innovation in maintenance, with organisations and all targeted employees becoming increasingly skilful, consistent and committed to working with Smart Maintenance. This aim was achieved through a mixed‐methods approach comprising six studies.Firstly, digitalisation in general and Smart Maintenance in particular, will require investment. This thesis reviews 24 maintenance models which can be used as support in calculating and describing the effects of maintenance. It also demonstrates an example of how to evaluate new technology (the impact of 5G technology on manufacturing performance). The thesis also identifies 11 factors influencing the investment process.Secondly, to benefit from the technology, an organisation must develop accordingly. This means that development initiatives need to be managed. This thesis presents an overall consideration model for leading maintenance in digitalised manufacturing. In short, the role of a maintenance manager is changing from that of a technical manager into a leader of people and organisations in change. Further, the effects of Smart Maintenance can be followed up using maintenance performance indicators (PIs). This thesis analyses 170 PIs and structures them into 13 categories.Thirdly, a strategic approach to Smart Maintenance helps in structuring such an implementation. This thesis proposes a strategy development process for Smart Maintenance implementation. The process is cyclical and continuously assesses the maintenance organisation to find new improvement areas. It thus continuously develops maintenance organisations and their way of working with Smart Maintenance.All studies are related to the diffusion of innovations (DOI) theory, to structure the findings into a framework that supports organisational innovation in maintenance. This is a novel perspective in both research and practice. The framework provided in this thesis can be used as guidance by industry practitioners as they implement Smart Maintenance. Thus, industrial companies can continue their development towards digitalisation and move towards increasingly competitive and sustainable production systems

Smart Maintenance - maintenance in digitalised manufacturing

What does digitalised manufacturing entail for maintenance organizations? This is a pressing question for practitioners and scholars within industrial maintenance management who are trying to figure out the best ways for responding to the rapid advancement of digital technologies. As technology moves faster than ever before, this is an urgent matter of uttermost importance. Specifically, in order to secure the success of highly automated, intelligent, connected and responsive production systems, industrial maintenance organizations need to transform to become leading enablers of high performance manufacturing in digitalised environments. In this thesis, this transformation is referred to as “Smart Maintenance”. The purpose of this thesis is to ensure high performance manufacturing in digitalised environments by enabling the adoption of Smart Maintenance. In order to stimulate adoption, a holistic understanding of Smart Maintenance is needed. Therefore, the aim of this thesis is to describe future scenarios for maintenance in digitalised manufacturing as well as to conceptualize and operationalize Smart Maintenance. The holistic understanding has been achieved through a phenomenon-driven research approach consisting of three empirical studies using multiple methods. Potential changes for maintenance organizations in digitalised manufacturing are described in 34 projections for the year 2030. From these projections, eight probable scenarios are developed that describe the most probable future for maintenance organizations. In addition, three wildcard scenarios describe eventualities that are less probable, but which could have large impacts. These scenarios serve as input to the long-term strategic development of maintenance organizations.Smart Maintenance is defined as “an organizational design for managing maintenance of manufacturing plants in environments with pervasive digital technologies” and has four core dimensions: data-driven decision-making, human capital resource, internal integration and external integration. Manufacturing plants adopting Smart Maintenance are likely to face implementation issues related to change, investments and interfaces, but the rewards are improved performance along multiple dimensions when internal and external fit have been achieved. Smart Maintenance is operationalized by means of an empirical measurement instrument. The instrument consists of a set of questionnaire items that measure the four dimensions of Smart Maintenance. It can be used by practitioners to assess, benchmark and longitudinally evaluate Smart Maintenance in their organization, and it can be used by researchers to study how Smart Maintenance impacts performance. This thesis has the potential to have a profound impact on the practice of industrial maintenance management. The scenarios described allow managers to see the bigger picture of digitalisation and consider changes that they might otherwise ignore. The rich, understandable, and action-inspiring conceptualization of Smart Maintenance brings clarity to practitioners and policy-makers, supporting them in developing implementation strategies and initiatives to elevate the use of Smart Maintenance. The measurement instrument makes it possible to measure the adoption of Smart Maintenance in manufacturing plants, which serves to develop evidence-based strategies for successful implementation. Taken together, the holistic understanding achieved in this thesis enables the adoption of Smart Maintenance, thereby ensuring high performance manufacturing in digitalised environments

A framework to support a simulation-based understanding of digitalisation in remanufacturing operations

This is the author accepted manuscript.Modelling and simulations are important in predicting the response and behavior of manufacturing shop-floor operations such as predictive maintenance in relation to the real-life operations. Thus, remanufacturing operations, an end-of-life operation focused on returning a “disassemble-able” product to a condition which is at least as new as the original specification, can be influenced by modelling and simulation. While simulations have a limitation in their ability to enable real-time business decisions in environments of complexity due to costs and time required to build these models, remanufacturing operations in particular will benefit from the application of simulations. As remanufacturing is characterized by an uncertain nature of product returns, simulation modelling can be used to support the understanding of different methods from a real-time scenario context. With manufacturing digitalization, complexity in remanufacturing is further increased with more data produced as sensor-enabled products enter the remanufacturing shop-floor. This paper investigates how modelling and simulation could be used to provide clarity to the digitalization of remanufacturing operations and proposes a framework to support simulation modelling for remanufacturing sensor-enabled products. Findings from the synthesis of a systematic literature review and five remanufacturing case studies reveal that system dynamics modelling has greater application to remanufacturing over other modelling techniques. Additionally, the importance of digitalisation across the six stages ofremanufacturing is expected to be similar and, as such, reduces medium term cost implications for remanufacturers looking to digitalise

Essential Ingredients for the Implementation of Quality 4.0: A narrative review of literature and future directions for research

Purpose Quality 4.0 is concerned with managing quality in the Industry 4.0 era. Specifically, its focus is on which digital tools are used to enhance an organization’s ability to reliably give customers high-quality products. The purpose of this paper is to investigate the key ingredients for the effective implementation of Quality 4.0. Design/methodology/approach A narrative literature review was conducted on the extant works to collate and analyse previous studies in this relatively new field. Findings The study revealed eight key ingredients for the effective implementation of Quality 4.0 in organizations, namely: (1) handling big data, (2) improving prescriptive analytics, (3) using Quality 4.0 for effective vertical, horizontal and end-to-end integration, (4) using Quality 4.0 for strategic advantage, (5) leadership in Quality 4.0, (6) training in Quality 4.0, (7) organizational culture for Quality 4.0 and, lastly, (8) top management support for Quality 4.0. These findings have provided a steer for the future research agenda of Quality 4.0. Practical implications Organizations can use the eight ingredients to perform a self-assessment on the current state of each element within their own organization. When implementing Quality 4.0, each ingredient should be effectively analysed, and measures taken so that the implementation of Quality 4.0 is effective. Originality/value The paper makes the first attempt to present the key ingredients an organization should possess to effectively implement Quality 4.0

Digitalisation and Business Model Innovation: Exploring the Microfoundations of Dynamic Consistency

The Industry 4.0 paradigm (I4.0) as the digitalisation of manufacturing firms denotes the exploitation of real-time data originating from a ubiquitous interconnection of objects, machines and humans (via the internet) across the entire value network. I4.0 not only serves as a catalyst to improve value-adding activities or to design new product and service solutions but also, more fundamentally, enables manufacturing firms to innovate their established business models (BMs). Against this rapid socio-technological shift, manufacturers face the challenge of holistically innovating their BMs. This requires the individualisation of the value proposition alongside the flexibilisation of their value creating and capturing activities, as well as a continuous adaptation and alignment of these activities with the firm’s organisational systems and the resource and competence base. Adopting the view of a BMI (business model innovation) as a system of interdependent activities, the continuous alignment of activities across the BMI is called dynamic consistency. However, it is not clear what mechanisms denote the notion of dynamic consistency. This thesis operationalises the microfoundations of dynamic consistency in an I4.0-driven BMI by empirically investigating six European manufacturing firms. Following the design themes of BMI, it argues that the notion of dynamic consistency comprises three main aspects: (1) a value focus on data and software; (2) a flexi-directional interlinkage to facilitate the exchange of information and materials; (3) agile working ensembles governing changes to the activity system. Moreover, it proposes open-mindedness and integrity of behaviour as a cognitive foundation that facilitates changes to the activity system. Taken together, these microfoundations provide reasoning for manufacturing firms to transform their traditional make-and-sell BM into a sense-and-act BM, yielding higher profits and profitability. The results demonstrate that the notion of BMI as an activity system must be complemented by the cognitive perspective of BMI to sufficiently operationalise the concept of dynamic consistency. This thesis is anticipated to be a starting point for further studies to achieve consistency during I4.0-driven BMI to generate superior and sustained value appropriation for manufacturing firms.Ford Britain Trust, Queens' Colleg

Digitalisation of Development and Supply Networks: Sequential and Platform-Driven Innovations

We draw from an eight-year dataset of 98 organisational entities involved in pre-competitive innovation networks across the UK pharmaceutical sector. These data map into three networks that are representative of: (i) a product development-led sequential pathway that begins with digitalised product development, followed by digitalisation of supply networks, (ii) a supply network-led sequential pathway that starts with digitalised supply networks, followed by digitalisation of product development, and (iii) a parallel — platform-driven — pathway that enables simultaneous digitalisation of development, production, and supply networks. We draw upon extant literature to assess these network structures along three dimensions — strategic intent, the integrative roles of nodes with high centrality, and innovation performance. We conduct within-case and cross-case analyses to postulate 10 research propositions that compare and contrast modalities for sequential and platform-based digitalisation involving collaborative innovation networks. With sequential development, our propositions are congruent with conventional pathways for mitigating innovation risks through modular moves. On the other hand, we posit that platform-based design rules, rather than modular moves, mitigate the risks for parallel development pathways, and lead to novel development and delivery mechanisms