CERES :: Browsing by Author "Turner, Christopher J."

Browsing by Author "Turner, Christopher J."

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Open Access
A 3D immersive discrete event simulator for enabling prototyping of factory layouts
(Elsevier, 2015-10-27) Oyekan, John; Hutabarat, Windo; Turner, Christopher J.; Tiwari, Ashutosh; Prajapat, Neha; Ince, Nadir; Gan, Xiao-Peng; Waller, Tony
There is an increasing need to eliminate wasted time and money during factory layout design and subsequent construction. It is presently difficult for engineers to foresee if a certain layout is optimal for work and material flows. By exploiting modelling, simulation and visualisation techniques, this paper presents a tool concept called immersive WITNESS that combines the modelling strengths of Discrete Event Simulation (DES) with the 3D visualisation strengths of recent 3D low cost gaming technology to enable decision makers make informed design choices for future factories layouts. The tool enables engineers to receive immediate feedback on their design choices. Our results show that this tool has the potential to reduce rework as well as the associated costs of making physical prototypes.
Open Access
Adapting petri nets to DES: stochastic modelling of manufacturing systems
(D A A A M International Vienna, 2018) Simon, E.; Oyekan, John; Hutabarat, Windo; Tiwari, Ashutosh; Turner, Christopher J.
Discrete-Event Simulation (DES) is commonly used for the simulation of manufacturing systems. In many practical cases, DES practitioners have to make simplifications or to use the software in an unconventional or convoluted fashion to meet their needs. Petri nets enable the development of transparent models which conciseness are a synonym of increased flexibility and control for designers. Furthermore, Petri nets take advantage of a solid mathematical ground and constitute a simple language. However, Petri nets lack the software capabilities to realise their full potential. This study investigates the suitability and relevance of Discrete-Event Simulation (DES) software for Petri net modelling in the context of manufacturing systems. A framework is developed for the modelling of different classes of Petri nets on DES. Analytical models of asynchronous flow lines are developed. Initial results show that the analytical models are without closed-form solution and the explosion of the state space is observed, justifying the use of computational methods and simulation for the analysis of manufacturing systems. This study shows that the gain in flexibility provided by Petri nets provides a new insight into the effects of stochasticity on setup and failure times in manufacturing systems.
Open Access
An automated optimisation framework for the development of re-configurable business processes: a web services approach
(Taylor & Francis, 2013-07-23) Vergidis, Kostas; Turner, Christopher J.; Alechnovic, Alex; Tiwari, Ashutosh
The practice of optimising business processes has, until recently, been undertaken mainly as a manual task. This article provides insights into an automated business process optimisation framework by using web services for the development of re-configurable business processes. The research presented here extends the optimisation framework by introducing additional web services as a mechanism for facilitating process interactions, identifying enhancements to support business processes and undertaking three case studies to evaluate the proposed enhancements. The featured case studies demonstrate that an increase in the amount of available web services gives rise to improvements in the business processes generated. This research highlights an increase in the efficiency of the algorithm and the quality of the business process designs that result from the enhancements. Future research directions are proposed for the further improvement of the framework.
Open Access
An autonomous system for maintenance scheduling data-rich complex infrastructure: Fusing the railways' condition, planning and cost
(Elsevier, 2018-02-22) Durazo-Cardenas, Isidro; Starr, Andrew; Turner, Christopher J.; Tiwari, Ashutosh; Kirkwood, Leigh; Bevilacqua, Maurizio; Tsourdos, Antonios; Shehab, Essam; Baguley, Paul; Xu, Yuchun
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.
Open Access
Business process mining for industry: successes and caveats
(2010-06-23T00:00:00Z) Mehnen, Jorn; Turner, Christopher J.; Tiwari, Ashutosh; Teti, R.
Business Process Mining (BPM) is a powerful technique which aims at mapping the complex structure of industrial processes into human interpretable graph structures by analysing business process traces automatically. The transfer of an innovative idea into an industrially viable product is a challenging task in its own rights. First, this paper introduces the concept of business process mining and an innovative Genetic Programming (GP) approach. Second, this paper addresses the principal caveats and solutions that come with transferring new academic solutions into real-world applications. A real BPM transfer project serves a background for this discussion.
Open Access
Business process mining: from theory to practice
(Emerald Group Publishing Limited, 2012-06-01T00:00:00Z) Turner, Christopher J.; Tiwari, Ashutosh; Olaiya, Richard; Xu, Yuchun
Purpose - This paper presents a comparison of a number of business process mining tools currently available in the UK market. An outline of the practice of business process mining is given along with an analysis of the main techniques developed by academia and commercial entities. This paper also acts as a primer for the acceptance and further use of process mining in industry suggesting future directions for this practice. Design/methodology/approach –Secondary research has been completed to establish the main commercial business process mining tool vendors for the market. A literature survey has also been undertaken into the latest theoretical techniques being developed in the field of business process mining. Findings – The authors have identified a number of existing commercially available business process mining tools and have listed their capabilities within a comparative analysis table. All commercially available business process mining tools included in this paper are capable of process comparison and at least 40% of the tools claim to deal with noise in process data. Originality/value - The contribution of this paper is to provide a state of the art review of a number of commercial business process mining tools available within the UK. This paper also presents a summary of the latest research being undertaken in academia in this subject area and future directions for the practice of business process min
Open Access
Combining virtual reality enabled simulation with 3D scanning technologies towards smart manufacturing
(Institute of Electrical and Electronics Engineers, 2017-01-19) Hutabarat, Windo; Oyekan, John; Turner, Christopher J.; Tiwari, Ashutosh; Prajapat, Neha; Gan, Xiao-Peng; Waller, Anthony
Recent introduction of low-cost 3D sensing and affordable immersive virtual reality have lowered the barriers for creating and maintaining 3D virtual worlds. In this paper, we propose a way to combine these technologies with discrete-event simulation to improve the use of simulation in decision making in manufacturing. This work will describe how feedback is possible from real world systems directly into a simulation model to guide smart behaviors. Technologies included in the research include feedback from RGBD images of shop floor motion and human interaction within full immersive virtual reality that includes the latest headset technologies.
Open Access
A decision-making framework for the implementation of remanufacturing in rechargeable energy storage system in hybrid and electric vehicles
(Elsevier, 2018-07-25) Okorie, Okechukwu; Turner, Christopher J.; Salonitis, Konstantinos; Charnley, Fiona; Moreno, Mariale; Tiwari, Ashutosh; Hutabarat, Windo
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.
Open Access
Design practices used in the development of microfluidic devices: a services-based view
(Inderscience, 2016-12-01) Tiwari, Ashutosh; Alcock, Jeffrey R.; Turner, Christopher J.
This paper presents the current state of microfluidic design from a practitioner’s perspective. The capture of microfluidic design practice was facilitated through a combination of industry survey and expert interviews, allowing the authors to draw out models for microfluidic design. Exploration of the current practice of microfluidic design showed that formal design methodologies were not in use. This research has also found that sub-section interactions have been addressed in an inadequate fashion by current design practices. The work presented in this paper outlines the scope for further research in the development of a formal design methodology for microfluidics.
Open Access
A digital maintenance practice framework for circular production of automotive parts
(Elsevier, 2020-12-18) Turner, Christopher J.; Okorie, O.; Emmanouilidis, Christos; Oyekan, J.
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
Open Access
Digitisation and the circular economy: A review of current research and future trends
(MDPI, 2018-11-01) Okorie, Okechukwu; Salonitis, Konstantinos; Charnley, Fiona; Moreno, Moreno; Turner, Christopher J.; Tiwari, Ashutosh
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.
Open Access
Discrete event simulation and virtual reality use in industry: new opportunities and future trends
(Institute of Electrical and Electronics Engineers, 2016-08-18) Turner, Christopher J.; Hutabarat, Windo; Oyekan, John; Tiwari, Ashutosh
This paper reviews the area of combined discrete event simulation (DES) and virtual reality (VR) use within industry. While establishing a state of the art for progress in this area, this paper makes the case for VR DES as the vehicle of choice for complex data analysis through interactive simulation models, highlighting both its advantages and current limitations. This paper reviews active research topics such as VR and DES real-time integration, communication protocols, system design considerations, model validation, and applications of VR and DES. While summarizing future research directions for this technology combination, the case is made for smart factory adoption of VR DES as a new platform for scenario testing and decision making. It is put that in order for VR DES to fully meet the visualization requirements of both Industry 4.0 and Industrial Internet visions of digital manufacturing, further research is required in the areas of lower latency image processing, DES delivery as a service, gesture recognition for VR DES interaction, and linkage of DES to real-time data streams and Big Data sets.
Open Access
Factory eco-efficiency modelling: the impact of data granularity on manufacturing and building asset simulation results quality
(Emerald, 2015) Davé, Aanand; Oates, Michael; Turner, Christopher J.; Ball, Peter D.
Purpose – This paper reports on the experimentation of an integrated manufacturing and building model to improve energy efficiency. Traditionally, manufacturing and building-facilities engineers work independently, with their own performance objectives, methods and software support. However, with progresses in resource reduction, advances have become more challenging. Further opportunities for energy efficiency require an expansion of scope across the functional boundaries of facility, utility and manufacturing assets.
Open Access
A framework for innovation outsourcing
(Inderscience, 2018-04-02) Rehman, Shahwar; Tiwari, Ashutosh; Turner, Christopher J.; Williams, Leon
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.
Open Access
A genetic programming based business process mining approach
(Cranfield University, 2009-05) Turner, Christopher J.; Tiwari, Ashutosh
As business processes become ever more complex there is a need for companies to understand the processes they already have in place. To undertake this manually would be time consuming. The practice of process mining attempts to automatically construct the correct representation of a process based on a set of process execution logs. The aim of this research is to develop a genetic programming based approach for business process mining. The focus of this research is on automated/semi automated business processes within the service industry (by semi automated it is meant that part of the process is manual and likely to be paper based). This is the first time a GP approach has been used in the practice of process mining. The graph based representation and fitness parsing used are also unique to the GP approach. A literature review and an industry survey have been undertaken as part of this research to establish the state-of-the-art in the research and practice of business process modelling and mining. It is observed that process execution logs exist in most service sector companies are not utilised for process mining. The development of a new GP approach is documented along with a set of modifications required to enable accuracy in the mining of complex process constructs, semantics and noisy process execution logs. In the context of process mining accuracy refers to the ability of the mined model to reflect the contents of the event log on which it is based; neither over describing, including features that are not recorded in the log, or under describing, just including the most common features leaving out low frequency task edges, the contents of the event log. The complexity of processes, in terms of this thesis, involves the mining of parallel constructs, processes containing complex semantic constructs (And/XOR split and join points) and processes containing 20 or more tasks. The level of noise mined by the business process mining approach includes event logs which have a small number of randomly selected tasks missing from a third of their structure. A novel graph representation for use with GP in the mining of business processes is presented along with a new way of parsing graph based individuals against process execution logs. The GP process mining approach has been validated with a range of tests drawn from literature and two case studies, provided by the industrial sponsor, utilising live process data. These tests and case studies provide a range of process constructs to fully test and stretch the GP process mining approach. An outlook is given into the future development of the GP process mining approach and process mining as a practice.
Open Access
Impact of model fidelity in factory layout assessment using immersive discrete event simulation
(Operational Research Society, 2016-04-13) Petti, Alessandro; Hutabarat, Windo; Oyekan, John; Turner, Christopher J.; Tiwari, Ashutosh; Prajapat, Neha; Gan, Xiao-Peng
Discrete Event Simulation (DES) can help speed up the layout design process. It offers further benefits when combined with Virtual Reality (VR). The latest technology, Immersive Virtual Reality (IVR), immerses users in virtual prototypes of their manufacturing plants to-be, potentially helping decision-making. This work seeks to evaluate the impact of visual fidelity, which refers to the degree to which objects in VR conforms to the real world, using an IVR visualisation of the DES model of an actual shop floor. User studies are performed using scenarios populated with low- and high-fidelity models. Study participant carried out four tasks representative of layout decision-making. Limitations of existing IVR technology was found to cause motion sickness. The results indicate with the particular group of naïve modellers used that there is no significant difference in benefits between low and high fidelity, suggesting that low fidelity VR models may be more cost-effective for this group.
Open Access
Improving root cause analysis through the integration of PLM systems with cross supply chain maintenance data
(Springer Verlag, 2015-09-21) Madenas, N; Tiwari, Ashutosh; Turner, Christopher J.; Peachey, Sophie; Broome, S
The purpose of this paper is to demonstrate a system architecture for integrating Product Lifecycle Management (PLM) systems with cross supply chain maintenance information to support root-cause analysis. By integrating product-data from PLM systems with warranty claims, vehicle diagnostics and technical publications, engineers were able to improve the root-cause analysis and close the information gaps. Data collection was achieved via in-depth semi-structured interviews and workshops with experts from the automotive sector. Unified Modelling Language (UML) diagrams were used to design the system architecture proposed. A user scenario is also presented to demonstrate the functionality of the system.
Open Access
Integrating product lifecycle management systems with maintenance information across the supply chain for root cause analysis
(Cranfield University, 2014-08) Madenas, Nikolaos; Tiwari, Ashutosh; Ball, Peter; Turner, Christopher J.
Purpose: The purpose of this research is to develop a system architecture for integrating PLM systems with maintenance information to support root cause analysis by allowing engineers to visualise cross supply chain data in a single environment. By integrating product-data from PLM systems with warranty claims, vehicle diagnostics and technical publications, engineers were able to improve the root cause analysis and close the information gaps. Methodology: The methodology was divided in four phases and combined multiple data collection approaches and methods depending on each objective. Data collection was achieved through a combination of semi-structured interviews with experts from the automotive sector, by studying the internal documentation and by testing the systems used. The system architecture was modelled using UML diagrams. Findings: The literature review in the area of information flow in the supply chain and the area of root cause analysis provides an overview of the current state of research and reveals research gaps. In addition, the industry survey conducted, highlighted supply chain issues related to information flow and the use of Product Lifecycle Management (PLM) systems. Prior to developing the system architecture, current state process maps were captured to identify challenges and areas of improvement. The main finding of this research is a novel system architecture for integrating PLM systems with maintenance information across the supply chain to support root cause analysis. This research shows the potential of PLM systems within the maintenance procedures by demonstrating through the integration of PLM systems with warranty information, vehicle diagnostics and technical publications, that both PD engineers and warranty engineers were benefited. The automotive experts who validated the system architecture recognised that the proposed solution provides a standardised approach for root cause analysis across departments and suppliers. To evaluate the applicability of the architecture in a different industry sector, the proposed solution was also tested using a case study from the defence sector. Originality/Value: This research addressed the research gaps by demonstrating that: i) A system architecture can be developed to integrate PLM systems with maintenance information to allow the utilisation of knowledge and data across the product lifecycle; ii) Network can be treated as a virtual warehouse where maintenance data are integrated and shared within the supply chain; iii) Product data can be utilised in conjunction with maintenance information to support warranty and product development engineers; iv) Disparate pieces of data can be integrated where later data mining techniques could potentially be applied.
Open Access
Intelligent decision support for maintenance: An overview and future trends
(Taylor and Francis, 2019-10-03) Turner, Christopher J.; Emmanouilidis, Christos; Tetsuo, Tomiyama
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 a framework 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 a comprehensive framework for its processing, analysis and use should be a valuable 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 and the provision of comprehensive framework for its processing analysis and use, allowing future systems to enable ‘Human in the loop’ interactions.
Open Access
An intelligent framework and prototype for autonomous maintenance planning in the rail industry
(SciTePress, 2015-05) Turner, Christopher J.; Tiwari, Ashutosh; Starr, Andrew G.; Durazo-Cardenas, Isidro; Blacktop, K
This paper details the development of the AUTONOM project, a project that aims to provide an enterprise system tailored to the planning needs of the rail industry. AUTONOM extends research in novel sensing, scheduling, and decision-making strategies customised for the automated planning of maintenance activities within the rail industry. This paper sets out a framework and software prototype and details the current progress of the project. In the continuation of the AUTONOM project it is anticipated that the combination of techniques brought together in this work will be capable of addressing a wider range of problem types, offered by Network rail and organisations in different industries.