Dr Alan Arokiam

Dr Alan Arokiam PhD, MSc

Dr Alan Arokiam

Dr Alan Arokiam
PhD, MSc

Senior Lecturer

Department of Applied Engineering and Management

Faculty of Engineering & Science


2009–present: Senior Lecturer, School of Engineering, The University of Greenwich:  Lecturing undergraduates students engineering management in second and final year, coordinating and leading the final year projects for the department.  Currently supervising five PhD students and several undergraduate students.  Lead academic and PI on several industry and research council funded projects.  On various committees and panels.  Former member of the academic council.

2006–09: Knowledge Transfer Associate/Business Development manager, The University of Liverpool Management School: Worked on improving the business processes and implementing ERP systems in manufacturing industry.  Improving marketing processes as well as strategic planning for the business.

2002–05: Laboratory Demonstrator – The University of Liverpool: Demonstrator for mechanical and materials lab courses.

2002–09: Fire and Safety Tutor – The University of Liverpool:  In charge of fire / health and safety of over 450 students and leading the fire safety team.

  • Engineering and Physical Sciences Research Council (EPSRC) Scholarship (2002-2005).
  • University of Liverpool scholarship (2002-2005).
  • Department of Engineering scholarship (2002-2005).
  • University of Liverpool scholarship (2001-2002).
  • Awarded by the Engineering Students Association as the "Best Engineering Student", as an undergraduate (2001).
  • Fellow of the Higher Education Academy
  • PRINCE2 Practitioner by the APM group
  • MSP Practitioner by the APM group
  • M_o_R Practitioner by the APM group
  • Principles of Change Management certified by the APM group
  • Energy use optimisation: Interest in the development of technological systems in conjunction with management policies to help reduce energy usage in industry, businesses and elsewhere. Modelling of energy usage is another research interest.
  • Simulation modelling of complex problems: Development of custom computer models to solve real world problems facing industry and businesses. Both discrete element and continuum modelling are used in conjunction with statistical models. The main research interest is in the use of such models to reach solutions at a lower cost and time than other comparable solutions.
  • Enterprise Resource Planning (ERP) systems and their implementation: ERP systems are key tools in current businesses and their integration with modelling and optimisation of energy are key area of interest. Other areas include the development of frameworks and systems for successful deployment of these complex systems.
  • Operations management: Optimisation of manufacturing industry from scheduling to lean philosophy and integrating them to modelling and ERP systems.
  • Programme/project and strategic management: Development of strategic polices and management systems for businesses. Integration of these with sustainable policies is another research goal.

Funded research projects

Energy Optimisation in Complex Manufacturing Environments – EPSRC Industrial CASE Award with Ford Motor Company (HSSMI) – PI and Lead Supervisor (April 2013 to September 2017) ~£91K

Energy used in manufacturing is generally quantified as overall usage and with a history of low energy costs the need to optimise or breakdown this cost was not a priority. With the rising cost of energy it has become rather significant operating cost of manufacturing industry. In order to optimise energy consumption, its actual usage must be quantified and the correlations with operation procedures, practices and scheduling must be investigated.


To develop a modelling framework and associated techniques to optimise the usage of energy in manufacturing.

Further information available at:

Lowering Cost and Carbon Footprint via Energy Modelling and Management – funded by Ford Motor Company – PI and Lead Academic (January 2012 to January 2015) ~ £60K

Large quantities of energy (~ 5MW) are used to run the plant, most of which are lost via extraction of fumes from machines and through the ventilation of the factory in addition to losses through open doors and windows. Others losses are through the roof and walls of the factory and from the transport of steam via pipes. In order to maintain air quality positive pressure has to be maintained whilst fumes and particles have to be extracted from the machines. These two conflicting requirements can lead to a lack of positive air pressure being maintained which is further exacerbated by leakage from open doors and windows. Lack of positive air pressure compromises the clean room requirements needed for optimal quality.


To reduce the overall energy consumption at the Dagenham plant whilst increasing air quality and comfort and evaluating and lowering the environmental impact of the processes in the plant.

Further information available at:

Optimisation of Ancillary and Support Systems in Large Factories to Lower Energy Usage – VC s Scholarship and co-funded by Ford motor company and the HSSMI – PI and Lead Academic (October 2014 to October 2017) ~ equivalent to £90K

Manufacturing in a large factory is an expensive operation, with both direct and indirect costs. A significant indirect cost is the running of ancillary and support machines. Recent research work lead by the supervisor under an EPSRC grant with HSSMI/Ford has shown a significant amount of energy and resources being used in supporting direct operations. Some of these energy/resources are used in running compressors, coolant pumps, MQL systems, chillers and a host of electronic systems. The relationship between resources used for indirect operations and the number of items produced is hard to correlate, unless a complex simulation is used to replicated measured data and algorithms created to establish this complex inter-relationship.


The aim of this project will be to optimise the running of all ancillary and support systems used in large factories to lower energy/resource consumption.

Material Waste Reduction Modelling in Manufacturing Industry – VC s Scholarship – PI and Lead Academic (October 2013 to October 2016) ~ equivalent to £72K

Manufacturing in a large factory is an expensive operation, with some of the inputs being turned into waste. Waste that has been targeted in the past has generally been time, but a lot of other wastes were insignificant and there was no economic sense in optimising for them, until now. The pathway of achieving total operational efficiency management systems, which are still not feasible due to the lack of intimate understanding of the factory operations, material waste is the next area to be explored. Material waste comes from machining operations, coolants, lubricants, waste water and the like, even quality rejects are wastes.


The aim of this project will be to develop a material waste reduction model that can be used in manufacturing industry.

Energy Usage Reduction in Manufacturing Environment via Simulation Modelling – Funded by Ford Motor company and Greenwich – PI & Lead Academic (March 2012 – August 2012) £14K

Manufacturing processes use energy in the transformation of input materials into finished products. This can range from the smelting of ores to the machining of metals. The total energy used in this transformation process can be quite significant. Nearly 80% of energy used by the manufacturing industry is in its various manufacturing processes.

There are many approaches to lowering energy used:

  1. Design a new process: The cleanest approach, but very expensive, sometimes impossible and can actually cost more when an existing factory has to be destroyed to make way for it.
  2. Design a better product: Already a lot of this is taking place, but high capital investment and existing processes mostly preclude this.
  3. Optimise the existing setup: Uses existing processes and products, but optimises the use of resources.  This approach has not been used for energy optimisation, but has been used extensively in the past for shop floor optimisation.

This proposal is the exploitation of this third approach, whereby existing factories can be made energy efficient without major reinvestment.  This will serve as a stop-gap solution in current factories, and also provide the optimisation inputs when building newer factories.

KTP Project with Priorclave Ltd – Academic Supervisor ( October 2010 – April 2013) ~£149K

Project Rating: Excellent

Project Description

To improve the company's competitive edge, Prior Clave have committed to implementing an ERP system. To maximise the benefits of this system will require technical expertise the company currently does not possess.

The partnership will allow the integration of the supply chain (internal and external), design processes and documentation linked with manufacturing scheduling and control. This will impact directly on inventory by reducing stock levels due to more accurate planning and improved communications with customers (leading to increased sales) and with suppliers. The overall effect of this implementation will be to reduce cost and environmental impact of the company's activities. Areas of costs reduction will include: transportation of materials and products, administration expenses, reduction of labour and overhead expenditure.

Project Aims

  • Replacement of all legacy systems by a new ERP system and the opportunity to exploit the ERP system to its full potential.
  • To build appropriate design and production documentation through the ERP system.
  • To get real-time estimates of the impact of disruption due to staff absentees and material problems on delivery schedules, thus improving customer confidence.
  • To gain monitoring and control of accurate component production time leading to realistic and reduced delivery scheduling.
  • With a fully realised ERP system, more throughputs can be achieved with the same resources leading to increased profit margins.
  • Maintain and expand the customer base by developing a reputation for reliable lead time promises, enhanced quality without a drastic change in overall product prices.

KTP Project with MEP Ltd – Academic Supervisor (January 2011 – January 2013) ~£110K

Project Rating: Very Good

Project Aim

To develop and integrate a scheduling system into the company's management information system in order to streamline the business processes, reduce inventory levels, lead times to customers and improve productivity.

This KTP will develop process and systems that will enable the company to:

  • Reduce lead times to the customer.
  • Develop a more agile supply chain management system.
  • Carry out complex scheduling quickly and error-free.
  • Reduce raw material inventory levels.
  • Faster and more efficient re-scheduling system to react to customer needs (order book).
  • Reduced overheads and labour costs.
  • Have live management information on KPIs

S. Pillai, A. C. Arokiam and R Bhatti  (2013) Linking simulation, critical success factors and enterprise resource planning in small and medium size enterprises. International Journal of Information Systems and Change Management, 6 (3). pp. 266-290

A. Lara Garzon, Dr. A. Arokiam, N. Greig, (2012) "Complexity of scheduling in SMEs specialising in High Variety Low Volume manufacturing" KTP Associates Conference, Centre for collaboration and partnership, University of Brighton 14th June 2012

S. Pillai, A.C. Arokiam, R. Bhatti, T. Collins, M. Prior.(2011) Make to Order Manufacturing and Operational Management Strategies – A Case Study at Priorclave Ltd. 18th EurOMA Conference 3-6 July 2011, Cambridge UK

Arokiam, A.C., Barashev, A.V., Bacon, D.J., and Osetsky, Y.N. (2006) Atomic-scale study of the interaction of Cu-rich precipitates with irradiation-produced defects in α-Fe. Philosophical Magazine, 87, pp. 925–43, February 2007.

Barashev, A.V. and Arokiam, A.C. (2006) Monte Carlo modelling of Cu atom diffusion in α-Fe via the vacancy mechanism. Philosophical Magazine Letters, 86, pp. 321–32, May 2006.

Arokiam, A.C., Barashev, A.V., Bacon, D.J., and Osetsky, Y.N. (2005) Characteristics of the interaction of Cu-rich precipitates with irradiation-produced defects in α-Fe. Philosophical Magazine Letters, 85, pp. 491–501.

Arokiam, A.C., Barashev, A.V., Bacon, D.J., and Osetsky, Y.N. (2005) Simulation of copper atom diffusion via the vacancy mechanism in a filute Fe-Cu alloy. Physical Review B, 71, 174205-1.

Arokiam, A.C., Barashev, A.V., and Bacon, D.J. (2004) Simulation of point defects, interstitial cluster and copper atom diffusion in Fe-Cu alloys. In: Ghoniem, N.M. (ed.) The Second International Conference on Multiscale Materials Modelling, pp. 480–82, October 2004.

Browse our publications database

A. Arokiam, H. Belaidi, J. Ladbrook and J. Wilson (2014) Simulation of Manufacturing Energy Usage and Load Profiles 7th Simulation Workshop (SW14) 1-2 April 2014,The Abbey Hotel Golf and Country Club, Worcestershire,England B98 9BE. UK

A. Lara Garzon, Dr. A. Arokiam, N. Greig, (2012) Complexity of scheduling in SMEs specialising in High Variety Low Volume manufacturing. KTP Associates Conference, Centre for collaboration and partnership, University of Brighton 14th June 2012

S. Pillai, A.C. Arokiam, R. Bhatti, T. Collins, M. Prior.(2011) Make to Order Manufacturing and Operational Management Strategies – A Case Study at Priorclave Ltd. 18th EurOMA Conference 3-6 July 2011, Cambridge UK

Browse our publications database