6 Steps for Implementing Reliability-based Maintenance

As we approach the next decade, it is crucial to acknowledge that the journey to prescriptive maintenance begins with a change in mindset – and an investment in technology. Today’s manufacturing plants tend to consist of a wide assortment of assets patched together like a colourful quilt. The machinery and equipment can range from highly advanced robotics to outdated legacy solutions, stretched past their normal life expectancy.

“Plant engineers must make these disparate assets integrate and perform as one. This can be a challenge, especially when lean budgets, escalating market demands and conflicting strategies add to the complexity. Forward-thinking plant engineers step up to the challenge, elevating processes beyond simple reactionary mode. It begins with a new mindset and modern technology,” advises Mark Bannerman, Managing Director – Infor Services at iOCO, Infor’s Master Partner in Africa (operating as a Gold Partner).

Modern Enterprise Asset Management (EAM) solutions help plant engineers and maintenance teams step up their processes and make effective asset management part of the overall enterprise strategy. Bannerman offers six ways modern solutions help plant management.

Reliability. Reliable plant operations can become a differentiator. Customers will notice that orders are always on-time, as ordered, and with unwavering product quality. These are unusual features in some industries.

Streamlining routine. Technology helps streamline and automate basic tasks, such as scheduling routine inspections and maintenance, tracking parts and materials used so inventory is accurate, and monitoring use of consumables (ink) and replaceable items (filters), and parts subject to wear (belts and brake pads). When the basics are covered, personnel have time to focus on more advanced questions and spend time immersed in the analytics.

Planning cashflow. Using risk assessments and condition assessments, managers will be able to project future needs and calculate related costs. This includes replacement parts or any outside special services or contractors that may be needed. With data easily accessible, managers can evaluate “replace versus repair” decisions and factor in the cost of down-time.

Predicting the future. Today, innovative Business Intelligence (BI) solutions with Artificial Intelligence (AI) contain powerful predictive capabilities, using algorithms and data science to identify patterns in data points and project next likely outcomes. Users can explore “what if?” scenarios and obtain forecasts of likely costs and demands.

Prioritising investments. This glimpse of future investment needs can be evaluated against projected cash cycles, while taking into account forecasts for shifting demand. Managers can then prioritise major capital investments when funding and political backing is in place.

Providing early warnings. Managers will be able to use predictive analytics to identify critical issues so that adequate preparations can be made, including having necessary parts or back-up equipment on standby. For example, when a generator nears end-of-life expectancy, back up replacements should be on hand for a seamless switch-over.

“Plant engineering and plant maintenance teams have many pressures they face today. Some are operational and involve keeping assets running. Others have more to do with cashflow strategies and decisions about whether to repair, replace or upgrade. A new mindset helps companies change the focus from reactive to anticipatory. Technology also helps managers make well-informed decisions. With advanced solutions in place, managers can take a holistic approach to plant maintenance and a long-term view of managing assets,” concludes Bannerman.