Asset Management: Moving from a Reactive to a Predictive Business

January 2013

By Nuris Ismail & Reid Paquin of Aberdeen Group

With the uncertainty surrounding the economic recovery, manufacturing executives are compelled to make difficult decisions related to capital and operational budgets that remain very tight. Unplanned downtime, inability to maintain planned production rates, safety and environmental incidences are all problems that can be traced directly to recurring equipment failure and operation mismatches in production rates and capacities. Asset management is the methodical planning and control of an asset throughout its lifecycle, including design and construction, operation, maintenance, upgrades, and eventual disposal or decommission.

The ultimate goal of any successful asset-management program is to extend the lifecycle and maximize the efficiency of all assets. Therefore, it comes to no surprise that pressure to maximize Return on Asset (RoA) is a close second. There is a constant battle in manufacturing to get the most out of the current asset base and the subsequent aging of the asset. Manufacturers are challenged in balancing these two pressures because while every manufacturer wants to maximize asset utilization, they can't do it at the sacrifice of the safety of employees, processes and the quality of their products.

Aberdeen used four key performance criteria to distinguish the Best-in-Class from Industry Average and Laggard organizations. These metrics measure the success of an organization's asset management program not only in terms of how it has improved plant operations, but also how successful these programs have been for achieving financial goals.

Performance on the four metrics above is directly linked to the success of a company's asset management program. The Best-in-Class enjoy less than a tenth of the unscheduled downtime and 26% higher OEE when compared to Laggards. In fact, Best-in-Class manufacturers reduced their maintenance cost by 30%, hence under-spending the planned budget. These metrics show that even in the face of reduced operational budgets the Best-in-Class are saving money and improving performance.

Companies operating in an asset intensive industry face two major competing pressures. On one hand these organization attempt to operate in a reduced operational and maintenance budget environment, while on the other hand maximize Return on Assets (RoA). To address these opposing market pressures, Best-in-Class companies have implemented a series of business capabilities to drive the success of asset management programs. At the highest level, that includes means being predictive to asset conditions. Enabling predictive asset management processes requires timely access to the right information in a form that enables employees to make effective decisions.

Organizations should focus on reducing the time required by maintenance and reliability professionals to find this necessary information.

The Best-in-Class companies first collect all of their asset information from different plants and store it in a centralized knowledge warehouse. In doing so, they remove this information from individual data sources (such as excel spreadsheets and access databases located on personal computers) and have a single repository for data collection. In addition, the Best-in-Class also provide historical and real-time asset data for intelligent decision making.

By having robust data like this at hand, manufacturers can see how a particular asset has historically performed and compare that to how it is running in real-time. This is crucial in determining whether an asset is running at its peak or if maintenance is needed. In addition, by using trending data, companies are able to predict adverse events. Best-in-Class companies provide this information on-demand, thus enabling easier information access, which reduces unscheduled downtime and improves asset performance. All of these capabilities are needed for manufacturers to move from a reactive, break-fix methodology to a predictive maintenance strategy.

While Best-in-Class companies are more likely to invest in asset management solutions, they are also more likely to empower their employees with mobility tools. Overall, the adoption of mobility in manufacturing has been slow, to the say the least, but where Aberdeen is seeing the largest adoption of mobility solutions is in asset management.

The Best-in-Class lead the charge in this technology adoption and are more likely to use mobility to allow their operators to access asset condition information while on the job (Figure 3). Mobile technology lets operators view relevant data in real time. As a result of this increased access, operators are better equipped to service assets when they need maintenance, repair, or inspection.

In addition, mobility can be employed to improve change request management. Traditionally, change management relies on an outdated, paper-based system. This process is burdensome because technicians must travel back-and-forth between work sites and the dispatch center for new assignments. There is also a heightened risk of error with this system because there is no guarantee that the information will be entered into the database. With mobility, workers can receive their assignments in the field, spend more time working, and create work orders right on their devices.

Providing mobile devices to field workers lets them input data automatically, access pending work orders, track repairs, and perform other critical tasks that traditionally required a trip to a work station. These tools are essential in many industries, like Oil and Gas, Utilities, and Mining, where work stations are not easily accessible. Best-in-Class companies are over 2.5-times more likely to use mobile devices while making their maintenance rounds. Improved data capturing allows for better analysis and evaluation and, as a result, the Best-in-Class are rapidly embracing mobile technology.