Optimisation of Food and Engineering Supply Chain Technology (OPTFEST): A Case Study

Baglee, David, Knowles, Michael and Morris, Adrian (2013) Optimisation of Food and Engineering Supply Chain Technology (OPTFEST): A Case Study. In: Comadem 2013, 11 - 13 Jun 2013, Helsinki.

[img] PDF
Comadem.pdf - Published Version
Restricted to Registered users only

Download (188kB)

Abstract

Predictive maintenance attempts to detect the onset of a degradation mechanism with the goal of correcting that degradation prior to significant deterioration in the component or equipment. The diagnostic capabilities of predictive maintenance technologies have increased in recent years. The advances in sensor technologies, component sensitivities, size reductions, and most importantly, cost, has allowed manufacturing processes, especially where once this technology was ‘missing’, the opportunity to enter a new and necessary area of diagnostics. One area in particular is the food and drink industry. However, with the introduction of any new technology, proper application and training is of critical importance. In addition, the implementation of any new maintenance strategy should be supported by a well developed information system. This paper will present the development and implementation, through case study analysis, of a new maintenance strategy using predictive maintenance strategies and an information system designed to support staff training. This project has resulted in the transfer of modern maintenance technologies, already successfully implemented in other industry sectors to the food processing sector. This has been achieved through the transfer and implementation of structured maintenance methods and the introduction of monitoring tools for processing equipment. Significant benefits include the ability to predict equipment failure, the development of best practice and compliance with supplier audits. The information interchange systems developed in
the project allow both users and suppliers to develop and improve engineering and maintenance guidelines, thus enabling the user to improve plant and production efficiency and determine the correct mix of technologies.

Item Type: Conference or Workshop Item (Paper)
Subjects: Engineering > Mechanical Engineering
Divisions: Digital Innovation Beacon
Faculty of Applied Sciences > Department of Computing Engineering and Technology
Depositing User: David Baglee
Date Deposited: 24 Jun 2013 13:21
Last Modified: 09 Mar 2017 16:06
URI: http://sure.sunderland.ac.uk/id/eprint/3957

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year