Predictive maintenance attempts to detect theonset of a degradation mechanism with thegoal of correcting that degradation prior tosignificant deterioration in the component orequipment. The diagnostic capabilities ofpredictive maintenance technologies haveincreased in recent years. The advances insensor 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 andnecessary area of diagnostics. One area inparticular is the food and drink industry.However, with the introduction of any newtechnology, proper application and training isof critical importance. In addition, theimplementation of any new maintenancestrategy should be supported by a welldeveloped information system. This paper willpresent the development and implementation,through case study analysis, of a newmaintenance strategy using predictivemaintenance strategies and an informationsystem designed to support staff training. Thisproject has resulted in the transfer of modernmaintenance technologies, alreadysuccessfully implemented in other industrysectors to the food processing sector. This hasbeen achieved through the transfer andimplementation of structured maintenancemethods and the introduction of monitoringtools for processing equipment. Significantbenefits include the ability to predict equipmentfailure, the development of best practice andcompliance with supplier audits. Theinformation interchange systems developed inthe project allow both users and suppliers todevelop and improve engineering andmaintenance guidelines, thus enabling theuser to improve plant and production efficiencyand determine the correct mix of technologies.

Maintenance can be considered as an information, knowledge processing and management system. The management of knowledge resources in maintenance is a relatively new issue compared to Computerized Maintenance Management Systems (CMMS) and Condition Monitoring (CM) approaches and systems. Information Communication technologies (ICT) systems including CMMS, CM and enterprise administrative systems amongst others are effective in supplying data and in some cases information. In order to be effective the availability of high-quality knowledge, skills and expertise are needed for effective analysis and decision-making based on the supplied information and data. Information and data are not by themselves enough, knowledge, experience and skills are the key factors when maximizing the usability of the collected data and information. Thus, effective knowledge management (KM) is growing in importance, especially in advanced processes and management of advanced and expensive assets. Therefore efforts to successfully integrate maintenance knowledge management processes with accurate information from CMMSs and CM systems will be vital due to the increasing complexities of the overall systems.Low maintenance effectiveness costs money and resources since normal and stable production cannot be upheld and maintained over time, lowered maintenance effectiveness can have a substantial impact on the organizations ability to obtain stable flows of income and control costs in the overall process. Ineffective maintenance is often dependent on faulty decisions, mistakes due to lack of experience and lack of functional systems for effective information exchange [10]. Thus, access to knowledge, experience and skills resources in combination with functional collaboration structures can be regarded as vital components for a high maintenance effectiveness solution.Maintenance effectiveness depends in part on the quality, timeliness, accuracy and completeness of information related to machine degradation state, based on which decisions are made. Maintenance effectiveness, to a large extent, also depends on the quality of the knowledge of the managers and maintenance operators and the effectiveness of the internal & external collaborative environments. With emergence of intelligent sensors to measure and monitor the health state of the component and gradual implementation of ICT) in organizations, the conceptualization and implementation of E-Maintenance is turning into a reality. Unfortunately, even though knowledge management aspects are important in maintenance, the integration of KM aspects has still to find its place in E-Maintenance and in the overall information flows of larger-scale maintenance solutions. Nowadays, two main systems are implemented in most maintenance departments: Firstly, Computer Maintenance Management Systems (CMMS), the core of traditional maintenance record-keeping practices that often facilitate the usage of textual descriptions of faults and actions performed on an asset. Secondly, condition monitoring systems (CMS). Recently developed (CMS) are capable of directly monitoring asset components parameters; however, attempts to link observed CMMS events to CM sensor measurements have been limited in their approach and scalability. In this article we present one approach for addressing this challenge. We argue that understanding the requirements and constraints in conjunction - from maintenance, knowledge management and ICT perspectives - is necessary. We identify the issues that need be addressed for achieving successful integration of such disparate data types and processes (also integrating knowledge management into the “data types” and processes).