Prescriptive Maintenance

As we move into the 4th Industrial revolution and advances within equipment maintenance techniques by manufacturers a new dawn has evolved. Predictive maintenance captures the data generated by equipment sensors, facilitates data communication between devices through Internet-based connectivity, uses algorithms to identify anomalies in operation, and predicts asset failure. This has now provided companies with the ability to reduce maintenance and downtime plus costs by identifying expected failures, breakdowns, plus various operational risks to assets and equipment machinery diagnostics. With the use of Industrial Internet of Things (IoT) technologies through machine learning, cloud computing and real-time data analytics improving machinery, equipment lifespans thus providing companies with an efficient maintenance process and is known as prescriptive maintenance.

Prescriptive maintenance allows for improvements within the company’s maintenance processes making use of cognitive analytics and ILoT tools which can provide solutions as an option to the maintainer. When a change in the equipment (the data) occurs, prescriptive maintenance will not only show what and when a failure is going to happen, but why it is happening. Prescriptive maintenance will take this analysis and determine different options and the potential outcomes to mitigate any risk to the operation. The data and analysis will continue, constantly adjusting the potential outcomes and making revised recommendations, improving the accuracy of the results.

Prescriptive Maintenance can drastically transform how maintenance is performed throughout any industry. By evolving from time-based to condition-based, to predictive and prescriptive maintenance, companies are evolving their maintenance systems from being simply efficient to become truly strategic. Beyond maintenance, cognitive systems can integrate maintenance and operations data with other data sources, such as quality, warranty, and engineering data, to become critical to how entire companies operate.

With the automation of many industries and the explosion of computers and sensors, condition-based maintenance has become machine-led. Sensors built into equipment provide real-time readings to centralized systems, that help maintenance teams maintain equipment before problems occur.

Salvo Global’s intensive Masterclass on “Prescriptive Maintenance” will impart practical applications for implementing, measuring results and successfully applying today’s best practices for Prescriptive Maintenance. In addition, delegates will be introduced to the advantages of utilizing prescriptive maintenance in their organization.

Top Learning Objectives

  • Understand the principles of an effective Work Management Process and utilizing IIoT information
  • Acquire knowledge on Single/Dynamic Strategy Cycles, Time-based based on Prescriptive and Predictive Maintenance techniques
  • Determine Strategy based maintenance for Predictive & Preventive Maintenance utilizing Big Data and IIoT, Reliability Centered Maintenance (RCM), PM Optimization, TPM, and Statistical Analysis and Prescriptive maintenance
  • Understand Condition Based Maintenance, Preventive & Predictive Maintenance and transforming IIoT and big data analyticities
  • Predict issues and possible imminent failures within through IIoT reporting
  • Compare the performance of current Maintenance Methods through Big Data and IIoT
  • Improveme Work Management Maintenance, Scheduling and Planning Process
  • Cost Optimization using effective measurement, reporting and analysis through IIoT and Big Data analyticities
  • Understand Cloud Based Artificial intelligence to predict future maintenance and forecasting trends and maintenance business requirements

Who Should Attend?

This course is very relevant to technical engineers and professionals who handle and are responsible for their organisations’ maintenance; as well as the overall smooth operations and processes of their organizations’ plants and machineries. These include, but are not limited to:

  • Maintenance SuperintendentsMaintenance Managers
  • Asset Managers
  • CMMS Managers
  • IIOT Specialist
  • Maintenance Analyst
  • Preventive Maintenance Supervisors
  • Preventive Maintenance Engineers
  • Predictive Maintenance Supervisors
  • Predictive maintenance Engineers
  • Maintenance Supervisors
  • Maintenance Engineers
  • Maintenance Planners
  • Maintenance Schedulers
  • Maintenance Foreman
  • Maintenance Planners
  • Physical Asset Managers
  • Reliability Managers
  • Reliability Engineers
  • Engineering Managers
  • Operations Managers
  • Plant Directors
  • Plant Managers
  • Plant Engineers

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