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We are living in a world where a machine not only can warn you before it breaks down, but it can also tell you what you should do about it. The financial and operational impact of such capability is tremendous if you consider the following:

  • Maintenance Costs: Unplanned downtime is costing industrial manufacturers an estimated $50 billion each year. [1]
  • Asset Reliability: 82% of companies have had unplanned downtime in the past 3 years. [2]
  • Productivity: Poor maintenance strategies can reduce the overall productive capacity of a plant by 5-20%. [3]
  • Safety:  Breakdown of an asset may directly or indirectly jeopardize the safety of workers and process. [3]
  • Quality: Machine failures result in low production rates and lead to inferior quality. [4]
  • Customer Satisfaction: Machine failure & downtime may prevent meeting customer demands on time again affecting negatively customer satisfaction.

Industry 4.0 capabilities enable companies to monitor their assets in real time, integrate data from many different sources, analyze and translate that data into meaningful insights and automatically turn those insights into prescriptive actions to optimize maintenance.

Would such capability help you improve your maintenance strategies?

Watch this on-demand webcast to hear from Scott Rogers, Founder and Technology Director of Noble Plastics, on how they harnesses Industry 4.0 capabilities, the power of the Internet of Things, big data and machine learning to increase equipment reliability and uptime while reducing overall maintenance costs and ensuring quality.

Jai Suri, Senior Director Product Management at Oracle and I explain how Oracle’s Future-Ready Predictive Maintenance solution uses predictive analytics to predict asset failure, generate actionable insights in real-time and automatically turn those insights into prescriptive actions to optimize maintenance.

A 2020 study [5] conducted by Oracle in partnership with ESG shows that from 700 finance and operations executives 46% of respondents rely on predictive maintenance data for their continued financial and operational well-being. By monitoring factory, product, and machine performance, organizations can achieve the operational visibility required to spot inconsistencies (i.e., anomalies in asset health and performance); continuously track and predict equipment failures before they occur; and act fast with integrated manufacturing system notifications.

The benefits of predictive maintenance are dependent on the industry or even the specific processes that it is applied to. However, predictive maintenance on average, according to Deloitte [3]:

· increases equipment uptime by 20%

· increases productivity by 25%

· reduces breakdowns by 70%

· lowers maintenance costs by 25%

Read this brief to learn more about Oracle’s Future-Ready Predictive Maintenance solution and join us at Modern Business Experience, March 23-26 in Chicago, to hear from your peers and learn how they extract full value from technology to optimize maintenance strategies.


[1] Industry Week & Emerson “How Manufacturers Achieve Top Quartile Performance”, Partners.wsj.com 2017 

[2] Aberdeen, The (Rising!) Cost of Downtime, 2016

[3] Deloitte “Predictive Maintenance Taking pro-active measures based on advanced data analytics to predict and avoid machine failure” 2017

[4] Hindawi, “Analyzing Critical Failures in a Production Process: Is Industrial IoT the Solution?” 2018

[5] Oracle and ESG “Emerging Technologies: The Competitive Edge for Finance and Operations” 2020

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