Part III's story about the limit switch on the conveyor line is a typical example of predictive maintenance as part of a comprehensive asset management programme.
The optimisation of all assets within a manufacturing facility is the foundation of asset management. The definition of 'assets' expands beyond the capital equipment installed in the facility. It involves the evaluation of the people and processes, in addition to the products, to find areas for increased efficiencies and cost savings. Asset management is more than just about instrument calibration; it ensures the people, and procedures they use to solve plant floor issues, are equally optimised.
The marketplace drives the need for asset management, particularly in a time where capacity and demand are both at an all-time high. And yet, the marketplace's various definitions of 'asset management' are often not representative of the discipline. The tools used in asset management - such as computerised maintenance management systems (CMMS) or enterprise asset management (EAM) packages - are mistaken for the asset management program itself. They are only as effective as the processes in which they operate. Manufacturers who place faith in EAM software packages often do so without reengineering their processes. This negatively impacts the effectiveness of both the EAM package and the asset management program itself.
Beyond the tools and software packages, usually the best asset management solutions - those with far-reaching results - start with work on the facility's procedures and practices. The beauty of asset management is its customisation to the manufacturer's processes; a supplier of asset management solutions can walk into any manufacturer facility - process or discrete - and identify areas for savings in their processes far easier than installing a software package and trying to make it work within the installed base.
Tools are part of a larger solution; on their own, however, they do not net tremendous success. In addition, today's asset data architectures have gaps that also limit the individual success of the tools. For example, asset utilisation is difficult when CMMS software is not configured to integrate with the current controls environment. And, many manufacturers fail to retain the CMMS and/or controls data for reliability investigations in their asset management programmes. Usually, asset management applications that do reach across a wide variety of devices within a plant are custom to the application.
An effective asset management programme increases a facility's reliability, and improves its maintainability. These drivers increase the plant's ability to produce at capacity. Driving a plant's reliability and maintainability requires one to optimise more than just the facility's capital equipment. Successful programmes also involve human performance, optimising the way preventative maintenance is implemented out in the facility. Other areas include reduced spares inventory and facility maintenance hours.
For the purpose of this article, asset management will be reviewed in the context of MRO operations on the factory floor. Active management of MRO is an uncharted area for CFOs deciding to take control of an organisation's total assets. This is compounded by the fact that asset management activities have historically not been of utmost importance for a manufacturing operation. However, asset management is critical for establishing and maintaining a streamlined enterprise that carries no excess in its operations. Without adequate insight into the health of its plant floor assets, a manufacturer can lose valuable production time and resources. Predictive maintenance is a powerful tool in manufacturers' ongoing efforts to maintain and improve equipment performance and achieve the highest level of productivity from all plant assets.
Traditionally, predictive maintenance has been labour-intensive and time-consuming, relying on a variety of individuals to gather information from machines using handheld data collectors, review the data and prepare recommendations. With action items in hand, a maintenance person would then go back to the machine and make the change - sometimes weeks after the initial data collection. The information would rarely be shared within the organisation. With manufacturers expanding to multiple sites around the globe, operating in remote locations, and in some cases lacking internal expertise to handle evaluations, it can be difficult to effectively capitalise on the benefits of traditional predictive maintenance. However, the Internet has made accessing, analysing and reacting to information on plant floor and machine status worldwide more efficient and faster than ever. Internet-enabled asset management, through Web-based predictive maintenance, allows companies to monitor MRO processes worldwide and seek commonalties among sites to improve efficiencies. It reduces the need for any predictive maintenance expert to conduct on-site evaluations. Linking condition-based monitoring data and predictive maintenance as part of a total plant asset management programme and integrated enterprise system helps lower overall operational costs and enhances return on assets.
As with the limit switch (discussed in Part III - March 2001), there exists a great opportunity for organisations and their predictive maintenance experts to collect on-line information across the integrated architecture on the plant floor. This data can be integrated into the CMMS and shared within the organisation to ultimately build a knowledge base about the production process and equipment for intuitive predictive and preventative maintenance. Through the integration of realtime plant-floor information with management-level business systems (ERP layer), manufacturers can realise a comprehensive MRO business solution that improves their overall plant efficiencies. This is yet another facet of a successful e-manufacturing strategy.
DaimlerChrysler
Taking asset management principles to the enterprise for launch success in the automotive industry, an inconsistent launch process and its resulting sub-optimal performance results in lost opportunities to lower the time and costs associated with launching a new vehicle into production. In the DaimlerChrysler environment, these are critical cost factors from the perspective of both speed-to-market and return on assets. In 1996, at the onset of the Daimler-Chrysler merger, the lack of a defined integration process at the plant floor level was perceived as a primary impediment to improved launch times (design to availability) for new vehicles. Similar to the overall inconsistencies in the launch processes, the plant floor controls team had no defined process in place for integrating plant floor controls with each other, or with the higher-level ERP systems.
Rockwell Automation's five-phase programme management process, developed over years of participating in automation programme launches in a variety of industries, helped forge a partnership between the supplier and DaimlerChrysler for the needed integration management programme. By defining a programme management process, where timelines, organisational structure and responsibilities, and necessary inputs and outputs for each stage of the process are defined in a roadmap, integration activities deployed in 1999 by DaimlerChrysler for the company's 42 global production facilities resulted in the first on-time new model launch in the history of the Passenger Cars and Trucks group.
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