Improving customer demand and cost forecasting methods |
Partners
Trelleborg Industrial AVS (TI)
is a world leader in the design and manufacture of rubber-to-metal bonded engineering products, anti-vibration mountings and suspension components for rail, marine, automotive off-highway, industrial and power generation applications. It provides worldwide solutions to these industrial sectors and is, therefore, part of many complex supply chains. TI possesses a high level of understanding in terms of the knowledge of their products markets and supply chains and their needs for inventory and capacity forecasting. They possess skills in using traditional methods of forecasting demand and estimating capacity costs. They possess historical knowledge of market trends and the individual factors that effect these trends. They possess a wealth of historical data that will be used for the development of the AI methods and suitable products on which the methods can be validated.
Unipart Logistics Ltd (ULL)
are part of the Unipart Group of Companies Ltd and are one of the UK’s leading providers of supply chain management consultancy services. They employ over 50 experienced practitioners with extensive experience of managing and transforming complex supply chains. They have a proven track record in helping organisations identify and exploit supply chain and logistics business benefits.
They bring to the partnership expertise in managing inventory, application experience in the development (design, build, test, implement) of forecasting and replenishment systems for the Unipart Group of Companies (UGC) automotive, leisure, industrial and rail logistics businesses. Hence, they have skills in employing forecasting techniques in all of these sectors as well as in the development of inventory models to allow “what if” scenarios for business policy change. They also possess demand management, sales & operations planning, forecasting, inventory policies, supply chain integration, and systems design and implementation expertise. They are members of CILT Inventory special interest group, Cranfield Agile Supply Chain research forum and the University of Eindhoven research forum.
They will benefit by the provision of improved forecast accuracy within UGC, leading to higher levels of customer service, reduced inventory holding, increased knowledge base and experience and the ability to utilise this knowledge to provide consultancy services to clients.
Preactor International Ltd (PIL)
is an independent company based in the UK. First formed in 1984 the company is one of the fastest growing companies specializing in advanced planning and production scheduling software and, through its partnerships with other software vendors and system suppliers, offers implementation and software support all over the world. Its flagship product, Preactor, was developed during an extensive joint development project (FORCAST, Flexible Operational Real-time Control And Scheduling Tools) under the European EUREKA initiative during the period 1991-1993. Now in version 9.3, this suite of scaleable, flexible and configurable advanced planning and production scheduling tools has become the price/performance leader in every market that it has a presence and is setting the standard by which other packages are measured. More than 1,600 companies in 56 countries now use Preactor in almost every business sector from manufacturing to logistics, staff scheduling to airports. PIL is involved in a number of international collaborative projects with support from the European Commission. These, as well as PI's extensive development programme, are designed to ensure that existing users have access to the latest effective and proven technology and have a cost of ownership that enables wider use of the product throughout their enterprise.
Sustainable Technology Solutions Ltd
is the project’s Lead Partner. STSL is an independent energy consultancy based in Leicestershire. The company consists of a highly qualified and multi-disciplinary team that has a successful track record of delivering a wide range of technology, business development and supply chain analysis programmes on behalf of both private and public sector clients. In particular STSL provides market analysis, feasibility studies, training solutions and design services for the low carbon, renewable energy and engineering supply chain industries. STSL have introduced state of the art technologies during projects and have been involved in the design and construction of a range of renewable energy systems. Key features of their capability are the ability to deliver engineering solutions as well as knowledge services and advice. They have also worked within and managed projects in the framework of EU and UK government funding and are currently engaged in both technological evaluations and energy policy assignments.
They see the project as providing them with the tools that will enable them to forecast energy demands at small and medium scale, predict the affects of energy generation technology mix on output, optimise energy generation capacity, and minimise costs for installing new capacity. They have a high level of experience in developing models for predicting the system performance of energy generation methods and using modelling to assist in system design. They possess detailed knowledge of operational characteristics for a wide variety of energy generation technologies which will be essential in developing the energy related project deliverables. Dr Seare has taught operations planning and control at postgraduate and undergraduate levels at DMU and is, therefore, fully familiar with state-of-art forecasting techniques. Such is the high level of complexity in forecasting energy needs that they will rely on the projects outputs to significantly enhance their forecasting capabilities.
Centre for Factories of the Future (CfFF)
is an education, training, research and development company based in Coventry. CfFF have many years of experience in EU/European funded education and training programmes as well as research and development projects including EUREKA, SOCRATES, PETRA, ADAPT, FORCE, COMETT and many national programmes. CfFF is presently co-ordinating an EU Leonardo da Vinci project with a budget of over 300,000 Euros over a two-year period. CfFF undertake work in the computing and IT sector and this involves developing forecasting systems using Artificial Intelligence Methods (AIMs) such as Neural Networks. Many years of research in this area has been undertaken by personnel in the company, including one member of staff, Dr Martin Ziarati, receiving a PhD in this particular area focusing on the automotive market and its supply chain. The company analyses the market needs for inventory and forecasting in the development of forecasting systems using individual AI methods. Presently, the company is working in the automotive and maritime sectors using real data from collaborating companies for the development of its forecasting systems. The staff have undertaken research in the above aforementioned area and published their findings in several papers at International conferences and journals, including the IEEE on a number of occasions. This has led the company to produce computer programmes using Neural Networks for developing forecasting systems.
De Montfort University (DMU)
Bob John is Professor of Computational Intelligence, Director of the Centre for Computational Intelligence (www.cci.dmu.ac.uk) and Head of the Division of Computer Engineering at De Montfort University. Professor John has published extensively the field of computational intelligence and is widely recognised by the international fuzzy logic community as a leading authority in the theoretical foundations and applications of fuzzy logic. He leads a large group working in the area of computational intelligence (fuzzy logic, artificial neural networks and evolutionary computing). He and his colleagues and students have successfully applied these techniques to many problems in classification and forecasting. He has been awarded funding from a number of sources including the European Union, EPSRC, DTI and has recently been awarded venture capital funding to form a new company in the area of knowledge management. He has supervised to completion eight PhD students and is currently supervising ten. At DMU he has carried out a number of consultancy projects and particularly relevant for this proposal are a knowledge based systems development for NCR and the forecasting of computer failure for an insurance company. His understanding of AI techniques and the problems of forecasting will significantly enhance this project.
David Stockton
is Professor of Manufacturing Systems Engineering within the School of Engineering and Technology. Professor Stockton is Director of the Centre for Manufacturing and leads the Lean Engineering Research Group within this centre. He has amassed over 20 years research, industrial and project management experience in the fields of cost modelling and the optimisation of manufacturing systems design. This experience has been utilised in a number of research and consultancy projects for leading UK aerospace and automotive organisations. Of particular relevance is his work at Airbus (UK) Ltd where he was the Project Director for a major consultancy project that involves the development of cost models for a wide range of advanced composite manufacturing processes. Previous EPSRC projects have included:
(1) “Improving the Cost Model Development Process – COSTMOD”, (EPSRC Ref: GR/M58818), which involved the development of an Expert Advisor, that provides a structured approach for Cost Engineers to develop cost models. This project also involved investigating the use of Artificial Neural Networks (ANN) and Fuzzy Logic (FL) in the development of cost models.
(2) “Responsive Design and Operation of Flexible Machining Lines”, (EPSRC Ref: GR/ N05871), where the principal aim was to make available procedures for automatically designing and optimising Multi-Component Flexible Machining Lines (MCFMLs). In achieving this aim the work involved integrating a commercial simulation system with genetic algorithms optimization routines. He has also applied genetic algorithms to a range of operations planning problems including aggregate planning, MRP batch sizing, facilities layout and assembly line sequencing.
Professor Stockton has published 20 journal papers and over 50 conference papers and is a member of the Editorial Advisory Board of the Aircraft Engineering and Aerospace Technology journal and the Manufacturing Committee of the Association of Cost Engineers.