IIoT Based Predictive Maintenance – Hikar – IIoT

About IIoT Based Predictive Maintenance

In manufacturing, transportation, energy, or any asset-intensive field, downtime and shrinking MTBF (mean time between failures) are the enemies, topped only by outright system failure. In equipment-heavy fields, operations traditionally work to prevent machine failures and predict equipment replacement or maintenance to keep costs down. Accurate prediction is the key, but it’s also the toughest part of the job.
Today, replacing reactive maintenance with predictive maintenance (PdM) is a way to reduce the cost and disruption of planned maintenance without increasing the unplanned downtime and the phenomenal cost of operations shutdowns. Although the majority of the data for predictive maintenance originates from operations technology, it can help with predictive maintenance as well by providing predictive analytics and business data.

Most industrial organizations “over maintain” production assets, even though 51% of them say that “operational performance” is the #1 reason they focus on APM.

40.8% of industrial companies say “better visibility of operations” is one of three critical elements to improve asset performance management.

Our research substantiates a controversial viewpoint: “The most reliable plant is not always the most profitable plant.”

Today, 51% of industrial organizations say “better operational performance” is the #1 strategic objective for improving asset management.

The fact is, asset-intensive organizations with an intensive drive toward Operational Excellence must develop a systemic attitude toward asset performance management (APM) instead of a purely maintenance-centric posture.
This perception is usually the result of a purely maintenance-centric view of asset performance management (APM) instead of a systemic view. The HIKAR APM 4.0 framework is based on the premise that to maintain a smart factory, city or other infrastructure, you need smart maintenance systems. HIKAR APM 4.0 is a holistic approach to asset operations that balances maintenance performance with overall economic performance. It uses a combination of technologies that allow plant operations professionals to evaluate prescriptive options to decide how to best operate and maintain assets. Understanding the opportunities that HIKAR APM 4.0 provides, the technology that enables an APM 4.0 approach, and the steps to take to move towards an APM 4.0 based strategy will equip businesses to make a dramatic step-change improvement in the returns they see from APM investments

Never Underestimate Operational Risk

Are you familiar with McKinsey’s philosophy on operational risk? That management consulting firm’s philosophy is that operational risk carries hidden costs that too many businesses ignore. In our experience, any asset failure that adversely impacts a company’s reputation (like an environmental disaster, safety failure or business disruption) has two costs: the direct cost, plus the impact on shareholder value. By not using reasonably available technology to protect shareholder value means the board fails in its obligations to corporate and social stakeholders. Recall for a moment the impact of the 2010 Deepwater Horizon incident on BP. That event is an extreme example of the impact of failing to properly address operational risk. While other examples might not be quite so dramatic or public, they consistently show that today’s complex systems require a comparably robust management approach that, fortunately, technology makes possible and practical.

Recommendations

HIKAR APM 4.0 is so much more than just a path to reliability. HIKAR APM 4.0, via the Digital Twin and advanced modeling practices, drives profitability in a variety of ways:

  • Provides prescriptive advice on most profitable operating alternatives
  • Boosts plant and operator safety and sustainability
  • Drives product quality and customer satisfaction
  • Expands probability of replicating golden lot/batch
  • Fosters employee engagement
  • Supports regulatory compliance

Along the way, companies must come to grips with several critical capabilities to achieve HIKAR APM 4.0:

  • First principles models
  • Cognitive computing
  • Machine learning
  • Big Data analytics
  • Financial modeling
  • Calculating and displaying KPIs
  • Value chain modeling
  • User experience that supports a mobile and visually demanding workforce

Predictive Maintenance (PdM) provides the highest possible visibility of the asset by collecting and analysing various types of data to provide the following benefits:

  • Identifying key predictors and determining the likelihood of outcomes.
  • Optimizing decision-making by systematically applying measurable real-time and historical data.
  • Planning, budgeting and scheduling maintenance repairs, replacements and spares inventory. PdM comparison example

The following example illustrates the amount of time that it takes to detect a potential failure interval for each of the four maintenance models commonly used today. PdM enables you to save time and money by detecting the failure based on data sources before damage to the machine occurs.

$20 billion lost in unplanned downtime. That number represents a massive loss for the continuous process industry in 2018

Condition monitoring, aka predictive maintenance, is a detailed but rewarding method to help prevent process downtime in your factory or plant. By closely monitoring your operation-critical machinery and providing process overwatch, data acquisition systems can aid your business in the form of long-term stability and ROI.

Hikar*SmarTag® for Predictive Maintenance:

We are introducing, the first product of this year 2020, Hikar*SmarTag®, universally developed and applicable to all your existing machines and factory setup, just one click and we guarantee ZERO downtime of your factory and machines. Hikar*SmarTag® stands for excellence in technologies and solutions that enable the continuous creation of value underlying the Synaptic Business Automation Concept.

Hikar*SmarTag® is an Industrial IoT based smart machine monitoring product and platform developed by Hikar. This product and platform is a step forward to turn your factory into a smart factory. By just scanning the smart tag from the machine, Hikar*SmarTag® can monitor and display the health and parameter values of all the components of machine including electrical relays, switches, electrical sensors, motors, mechanical corrosion, leakages, wire cut, vibrations, level, pressure, temperature, humidity, vibrations, energy consumptions, energy lost, utility consumptions, utility lost, efficiency of machines and process and many more real time data directly on the web page through Hikar IIoT platform. This will help to conduct predictive maintenance on the machines as well as can troubleshoot in zero time which will eliminate the machine downtime. It Improve Overall Equipment Effectiveness (OEE) to 96% and Increases return on assets (RoA) by 75% – Profit earned from equipment resources through improved uptime.

 

Check Hikar*SmarTag® for more details

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