Turning to smart technologies to keep mission-critical equipment running

We live in crisis-stricken times. Despite lockdowns easing in most of Asia, the global economy is unlikely to see a full return to business-as-usual anytime soon as many countries remain cautious about possible second waves of the pandemic. Factory output and assembly lines remain affected, and many manufacturers have also been forced to operate with minimal manpower on-site as remote work remains the default for many.

In times like these, the smooth operation of mission-critical equipment is paramount. The scale and scope of this varies greatly — from back-up generators in hospitals and emergency centers to essential services in banking and manufacturing. In short, these are assets that “cannot be allowed to fail”, despite restrictions on movement and resources. The stakes are high; a harsh reality for any personnel tasked with ensuring the continued service or performance of these equipment. Fortunately, technology can help mitigate the risks, ensuring mission-critical services are kept running and society can continue to function in this new normal.

Tighten tech to weather tough times

Innovative software providers have brought many game-changing features and functions to Enterprise Asset Management (EAM) solutions in recent years, enabling users to turn asset reliability into a strategic differentiator. Some manufacturers are exploiting this ability to the fullest by promising customers flexible and on-time deliveries. Those who continue with old-school solutions can seldom make such claims as unexpected delays plague schedules and hinder reliability. This is the unfortunate plight of many now struck by supply chain disruptions, movement restrictions and social distancing measures.

Without today’s new technologies like Artificial Intelligence (AI)-driven analytics, maintenance teams often find themselves fighting fires, jumping from one emergency to the next. Getting ahead of this type of reactive model requires predictive insights, using Internet of Things (IoT) sensors to monitor for key symptoms, like excessive heat or vibration, and tracking performance down to the component and part level. A change in mindset is often required, too. It’s time to get strategic, preventive and data centric.

Assess Risk and Potential Consequences

In assessing risks of these assets, users can use Reliability Centered Maintenance (RCM) tools to define functions, failures and the consequences of these failures. For example, the risk associated with the finishing machinery may be determined as very high, since all work orders would be affected if the equipment goes down, and the custom-built machinery has no off-the-shelf replacements. Machine failure here could cause a six-week delay in orders shipped, and millions in cashflow impact. Understanding the risk and potential consequences is an important first step in planning a strategic approach to keeping critical assets running — no matter what.  

Assess Conditions to Set Priorities

Condition Based Monitoring (CBM) is another highly effective approach to tracking real-time asset conditions and understanding the relative influence of an asset that may be starting to show signs of diminishing productivity. CBM uses a scoring system factors several criteria — from age of the asset to time and cost to replace it. This scoring method is based on carefully determined definitions and objective criteria, eliminating the guesswork that can often slow the process or render it unreliable.

Put More Solutions to Work

In addition to the foundational EAM solution, other technologies will help professionals manage mission critical assets with greater confidence, including:

Cloud Deployment. Moving systems to the cloud means turning over tasks like back-ups, data recovery, security, and compliance to a cloud provider who specializes in these issues and devotes full attention to data security. Cloud solutions are also updated continuously by the provider, ensuring that the solution is always modern, taking advantage of new functionality as it is available. This helps ensure that solutions are resilient to new threats, viruses and malware.

Internet of Things (IoT). Sensors installed on or in assets can measure, collect, and store data concerning a wide variety of physical conditions, such as temperature, vibration, moisture, and density. This data is sent to the cloud to be aggregated and analyzed for anomalies which may be early warning signs of the asset’s potential failure. Keeping an eye on red-flags in the early stages ensures that intervention can be effected early, minimizing potential disruption to performance and damage.

Business Intelligence (BI) Tools. Modern analytics are vital to delving into the cause-and-effect relationships between influencing factors and possible performance issues, particularly for issues that can be influenced or remedied. Managers can dive into data around costs, vendor reliability, lifecycle longevity, and user engagement. This may help them uncover that components from one vendor tend to fail more often, or machinery fails more often on the second shift — pointing to issues that can be addressed. Some factors, like weather, can’t be changed, but managers who understand the impact can plan accordingly, such as adjusting inventory levels of engine coolant and antifreeze during certain months.   

Predictive Analytics. Data science algorithms and AI applications can help companies analyze past trends, forecast future trends, anticipate peaks in demand, and prepare for shifts in consumer buying habits. For maintenance teams, predictive analytics helps forecast the lifespan of tools and machinery, stock items that need to be replenished, like ink or oil, or parts that need replacement based on wear, like machine filters and belts.

Artificial Intelligence. AI finds many applications in mission-critical maintenance, including the ability to create models and explore possible outcomes objectively, without human error or bias. When making complex decisions, for instance, solutions with advanced deep machine learning capabilities can weigh various factors and “what-if” scenarios, make leaps of insight and advise users on best courses of action. This is especially helpful for managers who may be evaluating things like best times for re-builds and offline maintenance, that may have an impact on business operations, cashflow, or customer experience.

In critical times, smart tech keeps essential services running

Mission-critical equipment across all sectors require special attention. These are often also highly complex, and can include the added layers of security protection, data encryption, fail-sale back-ups, IoT sensors, and remote monitoring of warning triggers. Maintenance of these assets is seldom as simple as installing a replacement part, and trouble-shooting performance issues can take a long time. Modern software is thus imperative to help simplify and streamline the process, finding correlational insights and predicting outcomes.

Today’s organizations are operating on lean budgets and even leaner maintenance staff. That is why it is now imperative that companies make strategic investments in smart technology, which can ensure business continuity and a smooth running of operations despite global disruptions. Agility will thus continue to be a critical differentiator for many organizations, empowering them to adapt to uncertainties and rapid changes in the market. Smart technology enables this as well. Aside from automating process for efficiency, these solutions can also aid with informing critical decisions on business priorities and optimal use of resources, thereby minimizing any further damage to business and customer. In short, smart technology equips organizations to better mitigate risks and protect their mission-critical assets, keeping them performing as needed and guarding the core of their businesses by proxy.

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