Chris Teller

Dr Christopher Turner


Lecturer in Business Analytics
MSc, MSc, PhD
+44 (0)1483 684310
19 MS 02
Wednesday 13:00 -15:00, Thursday 10:00 - 12:00

Biography

Areas of specialism

Business Analytics; Business Process Management; Mixed Reality Visualisation; Industry 4.0; Data Mining; Cloud Manufacturing; Distributed and Sustainable Manufacturing

Previous roles

2009 - 2017
Dr Christopher Turner was a Senior Research Fellow and Project Manager within the Manufacturing and Materials Department at Cranfield University.
Cranfield University

Research

Research interests

My teaching

My publications

Publications

Hutabarat Windo, Oyekan John, Turner Christopher, Tiwari Ashutosh, Prajapat Neha, Gan Xiao-Peng, Waller Anthony (2017) Combining virtual reality enabled simulation with 3D scanning technologies towards smart manufacturing, 2016 Winter Simulation Conference IEEE
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.
Simon E, Oyekan J, Hutabarat W, Tiwari A, Turner C J (2018) Adapting Petri Nets to Discrete Event Simulation for the Stochastic Modelling of Manufacturing Systems, International Journal of Simulation Modelling 17 (1) pp. 5-17 DAAAM Int. Vienna
Discrete
-
Event Simulation (DES) is commonly used for the simulation of manufacturing systems. In
many practical cases,
DES
practitioners ha
ve 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
allow
increased flexibility and control for designers. Furthermore, Petri nets
t
ake 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) soft
ware 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.
Durazo-Cardenas Isidro, Starr Andrew, Turner Christopher J, Tiwari Ashutosh, Kirkwood Leigh, Bevilacqua Maurizio, Tsourdos Antonios, Shehab Essam, Baguley Paul, Xu Yuchun, Emmanouilidis Christos (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 pp. 234-253 Elsevier
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 in-
tegrated system for automatic job scheduling is presented; from concept formulation to the ex-
amination of the data to information transitional level interface, and at the decision making level.
The underlying architecture con
fi
gures 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 de-
gradation alarms that initiate the automatic scheduling of maintenance tasks. Optimum sche-
duling was realized through data analytics and job sequencing heuristic and genetic algorithms,
taking into account speci
fi
c cost & value inputs from comprehensive task cost modelling. Formal
face validation was conducted with railway infrastructure specialists and stakeholders. The de-
monstrator structure was found
fi
t for purpose with logical component relationships, o
ff
ering
further scope for research and commercial exploitation
Turner Christopher J, Hutabarat Windo, Oyekan John, Tiwari Ashutosh (2016) Discrete Event Simulation and Virtual Reality use in Industry: New opportunities and future trends, IEEE Transactions on Human-Machine Systems 46 (6) pp. 882-894 IEEE
This paper reviews the area of combined discrete
event simulation (DES) and virtual reality (VR) use within in-
dustry. 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 pa-
per reviews active research topics such as VR and DES real-time
integration, communication protocols, system design considera-
tions, model validation, and applications of VR and DES. While
summarizing future research directions for this technology combi-
nation, 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 require-
ments 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 recog-
nition for VR DES interaction, and linkage of DES to real-time
data streams and Big Data sets.
Quintana - Amate S, Bermell - Garcia P, Tiwari A, Turner C J (2017) A new knowledge sourcing framework for knowledge-based engineering: An aerospace industry case study, Computers & Industrial Engineering 104 pp. 35-50 Elsevier
New trends in Knowledge-Based Engineering (KBE) highlight the need for decoupling the automation aspect from the knowledge management side of KBE. In this direction, some authors argue that KBE is capable of effectively capturing, retaining and reusing engineering knowledge. However, there are some limitations associated with some aspects of KBE that present a barrier to deliver the knowledge sourcing process requested by industry. To overcome some of these limitations this research proposes a new methodology for efficient knowledge capture and effective management of the complete knowledge life cycle. The methodology proposed in this research is validated through the development and implementation of a case study involving the optimisation of wing design concepts at an Aerospace manufacturer. The results obtained proved the extended KBE capability for fast and effective knowledge sourcing. This evidence was provided by the experts working in the development of the case study through the implementation of structured quantitative and qualitative analyses.
Vergidis Kostas, Turner Christopher, Alechnovic Alex, Tiwari Ashutosh (2015) An automated optimisation framework for the development of re-configurable business processes: a web services approach, International Journal of Computer Integrated Manufacturing 28 (1) pp. 41-58 Taylor & Francis
The practice of optimising business processes
has, until recently, been
undertaken mainly as a manual task.
This paper provides insight
s into a
n
automated
business process optimisation framework by using web services for
the development of re
-
configurable business processes.
The research presented
here extends the framework of Vergidis (2008) by introducing web services as a
mechanism for
facilitating business 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 proc
ess designs that
result from the enhancements
. Future research directio
ns are proposed for the
further improvement of the framework
Gonzalez Lozano G., Tiwari A., Turner C. (2018) A design algorithm to model fibre paths for manufacturing of structurally optimised composite laminates, Composite Structures 204 pp. 882-895 Elsevier
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.
Rehman Shahwar, Tiwari Ashutosh, Turner Christopher, Williams Leon (2018) A framework for innovation outsourcing, International Journal of Business Innovation and Research 16 (1) Inderscience
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.
Madenas N., Tiwari A., Turner C. J., Peachey S., Broome S. (2015) Improving root cause analysis through the integration of PLM systems with cross supply chain maintenance data, The International Journal of Advanced Manufacturing Technology 84 (5 - 8) pp. 1679-1695 Springer Verlag
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.
Turner Chris, Moreno Mariale, Mondini Luigi, Salonitis Konstantinos, Charnley Fiona, Tiwari Ashutosh, Hutabarat Windo (2019) Sustainable Production in a Circular Economy: A Business Model for Re-Distributed Manufacturing, Sustainability 11 (16) 4291 pp. 1-19 MDPI
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.
Garn Wolfgang, Turner Christopher, Kireulishvili George, Panagi Vasiliki (2019) The impact of catchment areas in predicting bus journeys,
The catchment area along a bus route is key in predicting bus journeys. In particular, the aggregated number of households within the catchment area are used in the prediction model. The model uses other factors, such as head-way, day-of-week and others. The focus of this study was to classify types of catchment areas and analyse the impact of varying their sizes on the quality of predicting the number of bus passengers. Machine Learning techniques: Random Forest, Neural Networks and C5.0 Decision Trees, were compared regarding solution quality of predictions. The study discusses the sensitivity of catchment area size variations. Bus routes in the county Surrey in the United Kingdom were used to test the quality of the methods. The findings show that the quality of predicting bus journeys depends on the size of the catchment area.
Turner Christopher J., Oyekan John, Stergioulas Lampros, Griffin David (2020) Utilizing Industry 4.0 on the Construction Site Challenges and opportunities, IEEE Transactions on Industrial Informatics Institute of Electrical and Electronics Engineers (IEEE)
In recent years a step change has been seen in the rate of adoption of Industry 4.0 technologies by manufacturers and industrial organizations 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.

Additional publications