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Industry 4.0 derived technologies have the potential to enable a new wave of digital manufacturing solutions for semi and fully automated production. In addition, this paradigm encompasses the use of communication technologies to transmit data to processing stations as well as the utilization of cloud based computational resources for data mining. Despite the rise in automation, future manufacturing systems will initially still require humans in the loop to provide supervisory level mediation for even the most autonomous production scenarios. Through a structured review, this paper details a number of key technologies that are most likely to shape this future and describes a range of scenarios for their use in delivering human mediated automated and autonomous production. This paper argues that in all cases of future manufacturing management it is key that the human has oversight of critical information flows and remains an active participant in the delivery of the next generation of production systems.
Christopher J. Turner; Ruidong Ma; Jingyu Chen; John Oyekan. Human in the Loop: Industry 4.0 technologies and scenarios for worker mediation of automated manufacturing. IEEE Access 2021, 9, 1 -1.
AMA StyleChristopher J. Turner, Ruidong Ma, Jingyu Chen, John Oyekan. Human in the Loop: Industry 4.0 technologies and scenarios for worker mediation of automated manufacturing. IEEE Access. 2021; 9 ():1-1.
Chicago/Turabian StyleChristopher J. Turner; Ruidong Ma; Jingyu Chen; John Oyekan. 2021. "Human in the Loop: Industry 4.0 technologies and scenarios for worker mediation of automated manufacturing." IEEE Access 9, no. : 1-1.
Cyber–physical systems such as satellite telecommunications networks generate vast amounts of data and currently, very crude data processing is used to extract salient information. Only a small subset of data is used reactively by operators for troubleshooting and finding problems. Sometimes, problematic events in the network may go undetected for weeks before they are reported. This becomes even more challenging as the size of the network grows due to the continuous proliferation of Internet of Things type devices. To overcome these challenges, this research proposes a knowledge-based cognitive architecture supported by machine learning algorithms for monitoring satellite network traffic. The architecture is capable of supporting and augmenting infrastructure engineers in finding and understanding the causes of faults in network through the fusion of the results of machine learning models and rules derived from human domain experience. The system is characterised by (1) the flexibility to add new or extend existing machine learning algorithms to meet the user needs, (2) an enhanced pattern recognition and prediction through the support of machine learning algorithms and the expert knowledge on satellite infrastructure, (3) the ability to adapt to changing conditions of the satellite network, and (4) the ability to augment satellite engineers through interpretable results. An industrial real-life satellite case study is provided to demonstrate how the architecture could be used. A single blind experimental methodology was used to validate the results generated by our approach.
John Oyekan; Windo Hutabarat; Christopher Turner; Ashutosh Tiwari; Hongmei He; Raymon Gompelman. A Knowledge-Based Cognitive Architecture Supported by Machine Learning Algorithms for Interpretable Monitoring of Large-Scale Satellite Networks. Sensors 2021, 21, 4267 .
AMA StyleJohn Oyekan, Windo Hutabarat, Christopher Turner, Ashutosh Tiwari, Hongmei He, Raymon Gompelman. A Knowledge-Based Cognitive Architecture Supported by Machine Learning Algorithms for Interpretable Monitoring of Large-Scale Satellite Networks. Sensors. 2021; 21 (13):4267.
Chicago/Turabian StyleJohn Oyekan; Windo Hutabarat; Christopher Turner; Ashutosh Tiwari; Hongmei He; Raymon Gompelman. 2021. "A Knowledge-Based Cognitive Architecture Supported by Machine Learning Algorithms for Interpretable Monitoring of Large-Scale Satellite Networks." Sensors 21, no. 13: 4267.
This paper explores the notion of the modular building construction site as an applied instance of redistributed manufacturing; in so doing, this research seeks to reduce the environmental footprint of building sites, treating them as small digitally connected subunits. In seeking to provide a whole lifecycle appreciation of a construction project, it is noted that the presence of a framework to provide guidance on the consideration of Internet of Things (IoT) data streams and connected construction objects is currently lacking. This paper proposes use of embedded IoT enabled sensing technology within all stages of a modular building lifecycle. An expanded four-phase model of intelligent assets use in construction is proposed along with an outline of the required data flows between the stages of a given building’s entire lifecycle that need to be facilitated for a BIM (Buildings Information Modelling) representation to begin to describe a building project as a sustainable asset within the circular economy. This paper also describes the use of concrete as a modular sensing structure; proposing that health monitoring of the material in situ along with the recoding of environmental factors over time could help to extend the longevity of such structures.
Chris Turner; John Oyekan; Lampros Stergioulas. Distributed Manufacturing: A New Digital Framework for Sustainable Modular Construction. Sustainability 2021, 13, 1515 .
AMA StyleChris Turner, John Oyekan, Lampros Stergioulas. Distributed Manufacturing: A New Digital Framework for Sustainable Modular Construction. Sustainability. 2021; 13 (3):1515.
Chicago/Turabian StyleChris Turner; John Oyekan; Lampros Stergioulas. 2021. "Distributed Manufacturing: A New Digital Framework for Sustainable Modular Construction." Sustainability 13, no. 3: 1515.
The adoption of the Circular Economy paradigm by industry leads to increased responsibility of manufacturing to ensure a holistic awareness of the environmental impact of its operations. In mitigating negative effects in the environment, current maintenance practice must be considered, not just for the reduction of its own direct impact but also for its potential contribution to a more sustainable lifecycle for the manufacturing operation, its products and related services. Focusing on the matching of digital technologies to maintenance practice in the automotive sector, this paper outlines a framework for organisations pursuing the integration of environmentally aware solutions in their production systems. This research acts as a primer for digital maintenance practice within the Circular Economy and the utilisation of Industry 4.0 technologies for this purpose.
C. Turner; O. Okorie; C. Emmanouilidis; J. Oyekan. A Digital Maintenance Practice Framework for Circular Production of Automotive Parts. IFAC-PapersOnLine 2020, 53, 19 -24.
AMA StyleC. Turner, O. Okorie, C. Emmanouilidis, J. Oyekan. A Digital Maintenance Practice Framework for Circular Production of Automotive Parts. IFAC-PapersOnLine. 2020; 53 (3):19-24.
Chicago/Turabian StyleC. Turner; O. Okorie; C. Emmanouilidis; J. Oyekan. 2020. "A Digital Maintenance Practice Framework for Circular Production of Automotive Parts." IFAC-PapersOnLine 53, no. 3: 19-24.
This paper explores the use of discrete event simulation (DES) for decision making in real time based on the potential for data streamed from production line sensors. Technological innovations for data collection and an increasingly competitive global market have led to an increase in the application of discrete event simulation by manufacturing companies in recent years. Scenario analysis and optimisation methods are often applied to these simulation models to improve objectives such as cost, profit and throughput. The literature review has identified key research gaps as the lack of example cases where multi-objective optimisation methods have been applied to simulation models and the need for a framework to visualise the relationship between inputs and outputs of simulation models. A framework is presented to enable the optimisation DES simulation models and optimise multiple objectives simultaneously using design of experiments and meta-models to create a Pareto front of solutions. The results show that the resource allocation meta-model provides acceptable prediction accuracy whilst the lead time meta-model was not able to provide accurate prediction. Regression trees have been proposed to assist stakeholders with understanding the relationships between input and output variables. The framework uses regression and classification trees with overlaid values for multiple objectives and random forests to improve prediction accuracy for new points. A real-life test case involving a turbine assembly process is presented to illustrate the use and validity of the framework. The generated regression tree expressed a general trend by demonstrating relationships between input variables and two conflicting objectives. Random forests were implemented for creating higher accuracy predictions and they produced a mean square error of ~ 0.066 on the training data and ~ 0.081 on test data.
N. Prajapat; C. Turner; A. Tiwari; D. Tiwari; W. Hutabarat. Real-time discrete event simulation: a framework for an intelligent expert system approach utilising decision trees. The International Journal of Advanced Manufacturing Technology 2020, 110, 2893 -2911.
AMA StyleN. Prajapat, C. Turner, A. Tiwari, D. Tiwari, W. Hutabarat. Real-time discrete event simulation: a framework for an intelligent expert system approach utilising decision trees. The International Journal of Advanced Manufacturing Technology. 2020; 110 (11-12):2893-2911.
Chicago/Turabian StyleN. Prajapat; C. Turner; A. Tiwari; D. Tiwari; W. Hutabarat. 2020. "Real-time discrete event simulation: a framework for an intelligent expert system approach utilising decision trees." The International Journal of Advanced Manufacturing Technology 110, no. 11-12: 2893-2911.
The changing nature of manufacturing, in recent years, is evident in industries willingness to adopt network connected intelligent machines in their factory development plans. While advances in sensors and sensor fusion techniques have been significant in recent years, the possibilities brought by Internet of Things create new challenges in the scale of data and its analysis. The development of audit trail style practice for the collection of data and the provision of comprehensive framework for its processing, analysis and use should be an important goal in addressing the new data analytics challenges for maintenance created by internet connected devices. This paper proposes that further research should be conducted into audit trail collection of maintenance data and the provision of a comprehensive framework for its processing analysis and use. The concept of ‘Human in the loop’ is also reinforced with the use of audit trails, allowing streamlined access to decision making and providing the ability to mine decisions.
Chris J. Turner; Christos Emmanouilidis; Tetsuo Tomiyama; Ashutosh Tiwari; Rajkumar Roy. Intelligent Decision Support for Maintenance: A New Role for Audit Trails. Recent Advances in Computational Mechanics and Simulations 2020, 396 -403.
AMA StyleChris J. Turner, Christos Emmanouilidis, Tetsuo Tomiyama, Ashutosh Tiwari, Rajkumar Roy. Intelligent Decision Support for Maintenance: A New Role for Audit Trails. Recent Advances in Computational Mechanics and Simulations. 2020; ():396-403.
Chicago/Turabian StyleChris J. Turner; Christos Emmanouilidis; Tetsuo Tomiyama; Ashutosh Tiwari; Rajkumar Roy. 2020. "Intelligent Decision Support for Maintenance: A New Role for Audit Trails." Recent Advances in Computational Mechanics and Simulations , no. : 396-403.
In recent years a step change has been seen in the rate of adoption of Industry 4.0 technologies by manufacturers and industrial organisations alike. This paper discusses the current state of the art in the adoption of industry 4.0 technologies within the construction industry. Increasing complexity in onsite construction projects coupled with the need for higher productivity is leading to increased interest in the potential use of industry 4.0 technologies. This paper discusses the relevance of the following key industry 4.0 technologies to construction: data analytics and artificial intelligence; robotics and automation; buildings information management; sensors and wearables; digital twin and industrial connectivity. Industrial connectivity is a key aspect as it ensures that all Industry 4.0 technologies are interconnected allowing the full benefits to be realized. This paper also presents a research agenda for the adoption of Industry 4.0 technologies within the construction sector; a three-phase use of intelligent assets from the point of manufacture up to after build and a four staged R&D process for the implementation of smart wearables in a digital enhanced construction site.
Christopher J. Turner; John Oyekan; Lampros Stergioulas; David Griffin. Utilizing Industry 4.0 on the Construction Site: Challenges and Opportunities. IEEE Transactions on Industrial Informatics 2020, 17, 746 -756.
AMA StyleChristopher J. Turner, John Oyekan, Lampros Stergioulas, David Griffin. Utilizing Industry 4.0 on the Construction Site: Challenges and Opportunities. IEEE Transactions on Industrial Informatics. 2020; 17 (2):746-756.
Chicago/Turabian StyleChristopher J. Turner; John Oyekan; Lampros Stergioulas; David Griffin. 2020. "Utilizing Industry 4.0 on the Construction Site: Challenges and Opportunities." IEEE Transactions on Industrial Informatics 17, no. 2: 746-756.
The changing nature of manufacturing, in recent years, is evident in industry’s willingness to adopt network-connected intelligent machines in their factory development plans. A number of joint corporate/government initiatives also describe and encourage the adoption of Artificial Intelligence (AI) in the operation and management of production lines. Machine learning will have a significant role to play in the delivery of automated and intelligently supported maintenance decision-making systems. While e-maintenance practice provides aframework for internet-connected operation of maintenance practice the advent of IoT has changed the scale of internetworking and new architectures and tools are needed. While advances in sensors and sensor fusion techniques have been significant in recent years, the possibilities brought by IoT create new challenges in the scale of data and its analysis. The development of audit trail style practice for the collection of data and the provision of acomprehensive framework for its processing, analysis and use should be avaluable contribution in addressing the new data analytics challenges for maintenance created by internet connected devices. This paper proposes that further research should be conducted into audit trail collection of maintenance data, allowing future systems to enable ‘Human in the loop’ interactions.
C. J. Turner; C. Emmanouilidis; T. Tomiyama; A. Tiwari; R. Roy. Intelligent decision support for maintenance: an overview and future trends. International Journal of Computer Integrated Manufacturing 2019, 32, 936 -959.
AMA StyleC. J. Turner, C. Emmanouilidis, T. Tomiyama, A. Tiwari, R. Roy. Intelligent decision support for maintenance: an overview and future trends. International Journal of Computer Integrated Manufacturing. 2019; 32 (10):936-959.
Chicago/Turabian StyleC. J. Turner; C. Emmanouilidis; T. Tomiyama; A. Tiwari; R. Roy. 2019. "Intelligent decision support for maintenance: an overview and future trends." International Journal of Computer Integrated Manufacturing 32, no. 10: 936-959.
The emergence of new technologies such as the Internet of Things, big data, and advanced robotics, together with risks such as climate change, rising labour costs, and a fluctuating economy, are challenging the current UK manufacturing model. In this paper, business models for re-distributed manufacture (RdM) are developed using anIDEF (Icam DEFinition for Function Modelling) description to serve as a guide for the implementation of the RdM concept in the consumer goods industry. This paper explores the viability of a re-distributed business model for manufacturers employing new manufacturing technologies such as additive manufacturing or three-dimensional (3D) printing, as part of a sustainable and circular production and consumption system. An As-Is value chain model is presented alongside the proposed new business model for a sustainable re-distributed manufacturing system. Both are illustrated via a case study drawn from the shoe manufacturing industry. The case study shows that there is a need for robust facilities in close proximity to the customer. These facilities are store fronts which can also manufacture, remanufacture, and provide services. The reduction in transportation and increase in customer involvement throughout the process are the main benefits that would accrue if a re-distributed model is implemented in the given industry.
Chris Turner; Mariale Moreno; Luigi Mondini; Konstantinos Salonitis; Fiona Charnley; Ashutosh Tiwari; Windo Hutabarat. Sustainable Production in a Circular Economy: A Business Model for Re-Distributed Manufacturing. Sustainability 2019, 11, 4291 .
AMA StyleChris Turner, Mariale Moreno, Luigi Mondini, Konstantinos Salonitis, Fiona Charnley, Ashutosh Tiwari, Windo Hutabarat. Sustainable Production in a Circular Economy: A Business Model for Re-Distributed Manufacturing. Sustainability. 2019; 11 (16):4291.
Chicago/Turabian StyleChris Turner; Mariale Moreno; Luigi Mondini; Konstantinos Salonitis; Fiona Charnley; Ashutosh Tiwari; Windo Hutabarat. 2019. "Sustainable Production in a Circular Economy: A Business Model for Re-Distributed Manufacturing." Sustainability 11, no. 16: 4291.
Current OEM (Original Equipment Manufacturer) facilities tend to be highly integrated and are often situated on one site. While providing scale of production such centralisation may create barriers to the achievement of fully flexible, adaptable, and reconfigurable factories. The advent of Industry 4.0 opens up opportunities to address these barriers by decentralising information and decision-making in manufacturing systems through CPS (Cyber Physical Systems) use. This research presents a qualitative study that investigates the possibility of distributing information and decision-making logic into ‘smart workpieces’ which can actively participate in assembly operations. To validate the concept, a use-case demonstrator, corresponding to the assembly of a ‘flat-pack’ table, was explored. Assembly parts in the demonstrator, were equipped with computation, networking, and interaction capabilities. Ten participants were invited to evaluate the smart assembly method and compare its results to the traditional assembly method. The results showed that in its current configuration the smart assembly was slower. However, it made the assembly process more flexible, adaptable and reconfigurable.
J. Oyekan; W. Hutabarat; C. Turner; C. Arnoult; A. Tiwari. Using Therbligs to embed intelligence in workpieces for digital assistive assembly. Journal of Ambient Intelligence and Humanized Computing 2019, 11, 2489 -2503.
AMA StyleJ. Oyekan, W. Hutabarat, C. Turner, C. Arnoult, A. Tiwari. Using Therbligs to embed intelligence in workpieces for digital assistive assembly. Journal of Ambient Intelligence and Humanized Computing. 2019; 11 (6):2489-2503.
Chicago/Turabian StyleJ. Oyekan; W. Hutabarat; C. Turner; C. Arnoult; A. Tiwari. 2019. "Using Therbligs to embed intelligence in workpieces for digital assistive assembly." Journal of Ambient Intelligence and Humanized Computing 11, no. 6: 2489-2503.
Akshita Gheewala; Christopher Turner; Jean-Rémi De Maistre. Automatic Extraction of Legal Citations using Natural Language Processing. Proceedings of the 15th International Conference on Web Information Systems and Technologies 2019, 202 -209.
AMA StyleAkshita Gheewala, Christopher Turner, Jean-Rémi De Maistre. Automatic Extraction of Legal Citations using Natural Language Processing. Proceedings of the 15th International Conference on Web Information Systems and Technologies. 2019; ():202-209.
Chicago/Turabian StyleAkshita Gheewala; Christopher Turner; Jean-Rémi De Maistre. 2019. "Automatic Extraction of Legal Citations using Natural Language Processing." Proceedings of the 15th International Conference on Web Information Systems and Technologies , no. : 202-209.
Manufacturing industries are experiencing a data-driven paradigm shift that is changing how technical operations are run and changing present business models. Leveraging on manufacturing data from industries and digital intelligence platforms have become important in creating new forms of value. While extending the life of a product through the circular economy 3 R’s of reuse, re-manufacturing and recycling remains a technical and resource challenge for practitioners, optimizing the increasing forms and volumes of data presents a complementary and necessary challenge to the circular economy. This research aims to explore how the manufacturing data can inform remanufacturing parameters for implementing remanufacturing on the Rechargeable Energy Storage System.
Okechukwu Okorie; K. Salonitis; F. Charnley; M. Moreno; C. Turner; A. Tiwari. Manufacturing Data for the Implementation of Data-Driven Remanufacturing for the Rechargeable Energy Storage System in Electric Vehicles. Blockchain Technology and Innovations in Business Processes 2018, 277 -289.
AMA StyleOkechukwu Okorie, K. Salonitis, F. Charnley, M. Moreno, C. Turner, A. Tiwari. Manufacturing Data for the Implementation of Data-Driven Remanufacturing for the Rechargeable Energy Storage System in Electric Vehicles. Blockchain Technology and Innovations in Business Processes. 2018; ():277-289.
Chicago/Turabian StyleOkechukwu Okorie; K. Salonitis; F. Charnley; M. Moreno; C. Turner; A. Tiwari. 2018. "Manufacturing Data for the Implementation of Data-Driven Remanufacturing for the Rechargeable Energy Storage System in Electric Vehicles." Blockchain Technology and Innovations in Business Processes , no. : 277-289.
Remanufacturing is a viable option to extend the useful life of an end-of-use product or its parts, ensuring sustainable competitive advantages under the current global economic climate. Challenges typical to remanufacturing still persist, despite its many benefits. According to the European Remanufacturing Network, a key challenge is the lack of accurate, timely and consistent product knowledge as highlighted in a 2015 survey of 188 European remanufacturers. With more data being produced by electric and hybrid vehicles, this adds to the information complexity challenge already experienced in remanufacturing. Therefore, it is difficult to implement real-time and accurate remanufacturing for the shop floor; there are no papers that focus on this within an electric and hybrid vehicle environment. To address this problem, this paper attempts to: (1) identify the required parameters/variables needed for fuel cell remanufacturing by means of interviews; (2) rank the variables by Pareto analysis; (3) develop a casual loop diagram for the identified parameters/variables to visualise their impact on remanufacturing; and (4) model a simple stock and flow diagram to simulate and understand data and information-driven schemes in remanufacturing.
Okechukwu Okorie; Konstantinos Salonitis; Fiona Charnley; Christopher Turner. A Systems Dynamics Enabled Real-Time Efficiency for Fuel Cell Data-Driven Remanufacturing. Journal of Manufacturing and Materials Processing 2018, 2, 77 .
AMA StyleOkechukwu Okorie, Konstantinos Salonitis, Fiona Charnley, Christopher Turner. A Systems Dynamics Enabled Real-Time Efficiency for Fuel Cell Data-Driven Remanufacturing. Journal of Manufacturing and Materials Processing. 2018; 2 (4):77.
Chicago/Turabian StyleOkechukwu Okorie; Konstantinos Salonitis; Fiona Charnley; Christopher Turner. 2018. "A Systems Dynamics Enabled Real-Time Efficiency for Fuel Cell Data-Driven Remanufacturing." Journal of Manufacturing and Materials Processing 2, no. 4: 77.
Since it first appeared in literature in the early nineties, the Circular Economy (CE) has grown in significance amongst academic, policymaking, and industry groups. The latest developments in the CE field have included the interrogation of CE as a paradigm, and its relationship with sustainability and other concepts, including iterative definitions. Research has also identified a significant opportunity to apply circular approaches to our rapidly changing industrial system, including manufacturing processes and Industry 4.0 (I4.0) which, with data, is enabling the latest advances in digital technologies (DT). Research which fuses these two areas has not been extensively explored. This is the first paper to provide a synergistic and integrative CE-DT framework which offers directions for policymakers and guidance for future research through a review of the integrated fields of CE and I4.0. To achieve this, a Systematic Literature Review (SLR; n = 174) of the empirical literature related to digital technologies, I4.0, and circular approaches is conducted. The SLR is based on peer-reviewed articles published between 2000 and early 2018. This paper also summarizes the current trends in CE research related to manufacturing. The findings confirm that while CE research has been on the increase, research on digital technologies to enable a CE is still relatively untouched. While the “interdisciplinarity” of CE research is well-known, the findings reveal that a substantial percentage is engineering-focused. The paper concludes by proposing a synergistic and integrative CE-DT framework for future research developed from the gaps in the current research landscape.
Okechukwu Okorie; Konstantinos Salonitis; Fiona Charnley; Mariale Moreno; Christopher Turner; Ashutosh Tiwari. Digitisation and the Circular Economy: A Review of Current Research and Future Trends. Energies 2018, 11, 3009 .
AMA StyleOkechukwu Okorie, Konstantinos Salonitis, Fiona Charnley, Mariale Moreno, Christopher Turner, Ashutosh Tiwari. Digitisation and the Circular Economy: A Review of Current Research and Future Trends. Energies. 2018; 11 (11):3009.
Chicago/Turabian StyleOkechukwu Okorie; Konstantinos Salonitis; Fiona Charnley; Mariale Moreno; Christopher Turner; Ashutosh Tiwari. 2018. "Digitisation and the Circular Economy: A Review of Current Research and Future Trends." Energies 11, no. 11: 3009.
Fibre steering is involved in the development of non-conventional variable stiffness laminates (VSL) with curvilinear paths as well as in the lay-up of conventional laminates with complex shapes. Manufacturability is generally overlooked in design and, as a result, industrial applications do not take advantage of the potential of composite materials. This work develops a design for manufacturing (DFM) tool for the introduction in design of the manufacturing requirements and limitations derived from the fibre placement technology. This tool enables the automatic generation of continuous fibre paths for manufacturing. Results from its application to a plate with a central hole and an aircraft structure – a windshield front fairing – are presented, showing good correlation of resulting manufacturable paths to initial fibre trajectories. The effect of manufacturing constraints is assessed to elucidate the extent to which the structurally optimal design can be reached while conforming to existing manufacturing specifications.
G. Gonzalez Lozano; A. Tiwari; C. Turner. A design algorithm to model fibre paths for manufacturing of structurally optimised composite laminates. Composite Structures 2018, 204, 882 -895.
AMA StyleG. Gonzalez Lozano, A. Tiwari, C. Turner. A design algorithm to model fibre paths for manufacturing of structurally optimised composite laminates. Composite Structures. 2018; 204 ():882-895.
Chicago/Turabian StyleG. Gonzalez Lozano; A. Tiwari; C. Turner. 2018. "A design algorithm to model fibre paths for manufacturing of structurally optimised composite laminates." Composite Structures 204, no. : 882-895.
As data from manufacturing and digital intelligence become a pervasive feature of our economy, it becomes increasingly important to leverage on this data in the creation of new forms of value. Within emerging concepts such as Industry 4.0 (I4.0) and the Internet of Things (IoT), understanding decision-making and stakeholders’ interaction is important in optimising manufacturing and post-manufacturing processes. Of interest is the post-manufacturing phase for the Rechargeable Energy Storage system, (RESS), a battery system embedded in hybrid and electric automobiles. This research develops a decision-making framework for the RESS component, employing data-driven remanufacturing as the circular approach for implementation. Findings highlight useful manufacturing data employed in remanufacturing for the RESS technology. This study concludes by giving recommendations on how decisions made by stakeholders and their interaction can inform manufacturers on design for remanufacturing.
O. Okorie; C. Turner; Konstantinos Salonitis; F. Charnley; M. Moreno; A. Tiwari; W. Hutabarat. A Decision-Making Framework for the Implementation of Remanufacturing in Rechargeable Energy Storage System in Hybrid and Electric Vehicles. Procedia Manufacturing 2018, 25, 142 -153.
AMA StyleO. Okorie, C. Turner, Konstantinos Salonitis, F. Charnley, M. Moreno, A. Tiwari, W. Hutabarat. A Decision-Making Framework for the Implementation of Remanufacturing in Rechargeable Energy Storage System in Hybrid and Electric Vehicles. Procedia Manufacturing. 2018; 25 ():142-153.
Chicago/Turabian StyleO. Okorie; C. Turner; Konstantinos Salonitis; F. Charnley; M. Moreno; A. Tiwari; W. Hutabarat. 2018. "A Decision-Making Framework for the Implementation of Remanufacturing in Rechargeable Energy Storage System in Hybrid and Electric Vehicles." Procedia Manufacturing 25, no. : 142-153.
National railways are typically large and complex systems. Their network infrastructure usually includes extended track sections, bridges, stations and other supporting assets. In recent years, railways have also become a data-rich environment. Railway infrastructure assets have a very long life, but inherently degrade. Interventions are necessary but they can cause lateness, damage and hazards. Every day, thousands of discrete maintenance jobs are scheduled according to time and urgency. Service disruption has a direct economic impact. Planning for maintenance can be complex, expensive and uncertain. Autonomous scheduling of maintenance jobs is essential. The design strategy of a novel integrated system for automatic job scheduling is presented; from concept formulation to the examination of the data to information transitional level interface, and at the decision making level. The underlying architecture configures high-level fusion of technical and business drivers; scheduling optimized intervention plans that factor-in cost impact and added value. A proof of concept demonstrator was developed to validate the system principle and to test algorithm functionality. It employs a dashboard for visualization of the system response and to present key information. Real track incident and inspection datasets were analyzed to raise degradation alarms that initiate the automatic scheduling of maintenance tasks. Optimum scheduling was realized through data analytics and job sequencing heuristic and genetic algorithms, taking into account specific cost & value inputs from comprehensive task cost modelling. Formal face validation was conducted with railway infrastructure specialists and stakeholders. The demonstrator structure was found fit for purpose with logical component relationships, offering further scope for research and commercial exploitation.
Isidro Durazo-Cardenas; Andrew Starr; Christopher J. Turner; Ashutosh Tiwari; Leigh Kirkwood; Maurizio Bevilacqua; Antonios Tsourdos; Essam Shehab; Paul Baguley; Yuchun Xu; Christos Emmanouilidis. An autonomous system for maintenance scheduling data-rich complex infrastructure: Fusing the railways’ condition, planning and cost. Transportation Research Part C: Emerging Technologies 2018, 89, 234 -253.
AMA StyleIsidro Durazo-Cardenas, Andrew Starr, Christopher J. Turner, Ashutosh Tiwari, Leigh Kirkwood, Maurizio Bevilacqua, Antonios Tsourdos, Essam Shehab, Paul Baguley, Yuchun Xu, Christos Emmanouilidis. An autonomous system for maintenance scheduling data-rich complex infrastructure: Fusing the railways’ condition, planning and cost. Transportation Research Part C: Emerging Technologies. 2018; 89 ():234-253.
Chicago/Turabian StyleIsidro Durazo-Cardenas; Andrew Starr; Christopher J. Turner; Ashutosh Tiwari; Leigh Kirkwood; Maurizio Bevilacqua; Antonios Tsourdos; Essam Shehab; Paul Baguley; Yuchun Xu; Christos Emmanouilidis. 2018. "An autonomous system for maintenance scheduling data-rich complex infrastructure: Fusing the railways’ condition, planning and cost." Transportation Research Part C: Emerging Technologies 89, no. : 234-253.
E. Simon; J. Oyekan; W. Hutabarat; A. Tiwari; C. J. Turner. Adapting Petri Nets to DES: Stochastic Modelling of Manufacturing Systems. International Journal of Simulation Modelling 2018, 17, 5 -17.
AMA StyleE. Simon, J. Oyekan, W. Hutabarat, A. Tiwari, C. J. Turner. Adapting Petri Nets to DES: Stochastic Modelling of Manufacturing Systems. International Journal of Simulation Modelling. 2018; 17 (1):5-17.
Chicago/Turabian StyleE. Simon; J. Oyekan; W. Hutabarat; A. Tiwari; C. J. Turner. 2018. "Adapting Petri Nets to DES: Stochastic Modelling of Manufacturing Systems." International Journal of Simulation Modelling 17, no. 1: 5-17.
This paper proposes a framework for the facilitation of organisational capability for outsourcing innovation, enabling firms to take advantage of its many benefits (e.g., reduced costs, increased flexibility, access to better expertise and increased business focus), whilst mitigating its risks. In this framework a generic holistic model is developed to aid firms to successfully outsource innovation. The model is realised in two stages using a qualitative theory-building research design. The initial stage develops a preliminary model which is subsequently validated and refined during the second stage. The propositions which form the preliminary model are deductively explored to identify whether they also exist in a second data set. A semi-structured interview survey is executed with the aid of a rich picture survey instrument to gather data for this purpose. The model developed by this study describes innovation outsourcing as an open system of interrelated activities that takes established company strategy (in terms of people, organisational structures, environment, and technology), and transforms it into improved firm performance through innovation. The model achieves this through a three-stage process which enables the alignment of capability to outsourced innovation activity, and makes actual performance outcomes, rather than expected benefits, the focus of innovation outsourcing aims.
Shahwar Rehman; Ashutosh Tiwari; Christopher Turner; Leon Williams. A framework for innovation outsourcing. International Journal of Business Innovation and Research 2018, 16, 79 .
AMA StyleShahwar Rehman, Ashutosh Tiwari, Christopher Turner, Leon Williams. A framework for innovation outsourcing. International Journal of Business Innovation and Research. 2018; 16 (1):79.
Chicago/Turabian StyleShahwar Rehman; Ashutosh Tiwari; Christopher Turner; Leon Williams. 2018. "A framework for innovation outsourcing." International Journal of Business Innovation and Research 16, no. 1: 79.
The validation stage plays a critical role in the development and production of medical devices; it ensures new medical devices meet all the functional, reliability and quality requirements of both customer and regulatory authorities. This paper presents a case study concerning validation and qualification process for medical devices in a UK-based medical device manufacturer. The work aims to develop an efficient and highly reliable procedure for the validation of medical devices. A benchmarking study has been performed to identify the best practices in product validation. The existing practices within the case study manufacturer have been reviewed to identify opportunities for validation improvement. New practices have been proposed for the case study manufacturer, and guidelines for implementing the proposed validation procedures have also been developed.
Yuchun Xu; Ashutosh Tiwari; Hao Chen; Christopher Turner. Development of a validation and qualification process for the manufacturing of medical devices: a case study based on cross-sector benchmarking. International Journal of Process Management and Benchmarking 2018, 8, 79 .
AMA StyleYuchun Xu, Ashutosh Tiwari, Hao Chen, Christopher Turner. Development of a validation and qualification process for the manufacturing of medical devices: a case study based on cross-sector benchmarking. International Journal of Process Management and Benchmarking. 2018; 8 (1):79.
Chicago/Turabian StyleYuchun Xu; Ashutosh Tiwari; Hao Chen; Christopher Turner. 2018. "Development of a validation and qualification process for the manufacturing of medical devices: a case study based on cross-sector benchmarking." International Journal of Process Management and Benchmarking 8, no. 1: 79.