SAG_Twitter_MEME_Making_Predictive_Maintenance_880x440_Jun18In a mad dash to cut operational costs, oil and gas companies are looking seriously at using predictive analytics, according to a new IQPC survey.

 The survey, Asset Optimization in Oil and Gas, said that 92% of participants believe that using predictive analytics will increase operational efficiency, lower capital costs and result in safer and more profitable operations. Q1 Survey

Volatile oil and gas prices, geopolitical instability, increased regulation and disruptive technologies have set off a rush to improve operational efficiencies across the industry. Short-term measures including layoffs and delayed capital expenditure are not viable long-term strategies for improving business performance.

So, in order to maintain a competitive edge, innovative companies are making their operations more cost-competitive by leveraging digital asset optimization practices.

The analysis, where Software AG and IQPC teamed up to survey more than 200 oil and gas operations providers, was conducted over a period of six weeks with a goal of better understanding how oil and gas companies are adapting and adjusting their asset optimization efforts in this environment of unprecedented complexity and volatility.

Predictive maintenance was the first trend discussed in the survey. And, although 92% of those surveyed confirmed a belief that using predictive analytics will increase operational efficiency, lower capital costs and result in more safe and profitable operations – only around 30% have predictive and prescriptive capabilities embedded in less than 25% of their assets.

Q5 SurveyAnd despite the fact that 75% of those we surveyed are using preventative maintenance practices, a whopping 36% are still using run to fail/reactive maintenance.   For assets categorized as critical, 50% are using some form of predictive maintenance and 31% are using first generation prescriptive maintenance.  For critical equipment that is not run to fail, most are using third party service providers or home-grown solutions that may or may not be enabled for real-time processing of streaming operational data.

Despite these somewhat disturbing figures (or perhaps because of them), the survey revealed that predictive maintenance programs are on the rise. One reason is the Internet of Things (IoT). Predictive maintenance leverages IoT by continuously analyzing real-time equipment sensor data to understand when maintenance will be required. Technician locations are coupled with replacement/repair equipment available and job completion time to identify the best technician available to perform the needed service during a scheduled downtime.

Q14 Barriers to Asset OptimizationIn fact, 45% of those we surveyed indicated that predictive and prescriptive maintenance capabilities are a very important management – and a high investment - priority in 2018.  So we asked our survey respondents “what barriers are currently preventing you from achieving your asset optimization goals?” The top barriers identified included lack of subject matter expertise; lack of understanding “what operational excellence” looks like; comfort with the status quo and initiative overload.

While some oil and gas companies are adopting digital transformation initiatives, the industry approach remains overly conservative for technologies that have been proven by leading oil and gas companies, as well as leading companies in both the industrial discrete and continuous process manufacturing sectors.  In today’s competitive and dynamic energy environment, maintaining a wait-and-see approach is not a viable mid- or long-range strategy if they are to remain competitive with their best in class peers.

In our next post, we will delve further into the survey to show you why the future is digital for the oil and gas industry.

Read the Survey Here

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