Details of Grant 

EPSRC Reference:	EP/F031394/1
Title:	Creating Physical Structure from Disarray
Principal Investigator:	Dai, Professor J
Other Investigators:	Purnell, Dr G
Researcher Co-Investigators:
Project Partners:	Faccenda Group Ltd Manor Bakeries Ltd RNA Automation Ltd
Department:	Engineering
Organisation:	Kings College London
Scheme:	Standard Research
Starts:	03 November 2008	Ends:	02 May 2012	Value (£):	355,363
EPSRC Research Topic Classifications:	Robotics & Autonomy
EPSRC Industrial Sector Classifications:	Manufacturing
Related Grants:	EP/F031653/1
Panel History:	Panel Date Panel Name Outcome 21 Nov 2007 Engineering Systems Panel Announced
Summary on Grant Application Form
The food industry is a major sector in UK manufacturing worth over 70bn per annum. The introduction of robotics and automation would free staff from tedious and arduous tasks, yet the nature of the processes and products hinder direct application of many current automation techniques. Two key aspects are the variation in food products and the typical lack of physical order in their processing. Raw food products are commonly randomly positioned on conveyors, or heaped into bulk containers. Whilst some automation does exist for processing foods, the majority require oriented infeeding of products. This is a typical task for an operative, and once processed by the equipment the products are often ejected back into a disordered arrangement! This fundamental and adventurous research is to develop automation techniques for the translation of physically disordered products into structured arrangements accommodating variations in the products and processes. This will substantially improve the range of food and other difficult processes that can be automated, remove the need for people to perform boring machine feeding tasks, and enable the producers to use valuable human resource on more value-adding tasks.The project will survey and categorise industrial physical structuring processes in terms of complexity, input sensing, and grasping requirements. For each of the categories mathematical descriptions of the states of disarray and order will be defined and translational matrices created to transform between the disorder and ordered arrangement states. Dynamic modelling of the process will be used to improve the techniques. In parallel, appropriate sensory and handling technologies will be determined for each category. Finally a proof of concept system will be constructed to physically validate the new approaches on a number of example tasks from the food sector. This research will benefit the academic community in the fields of mechatronics and automation design, and industrial users and equipment producers from all industry sectors who will gain the potential for new equipment and broaden application areas for existing automation.
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