Year After Year, Refinery Sees Big Savings with Machine Health

Business Impact 

As the largest oil refinery and petrochemical producer in Israel, this industrial manufacturer is the cornerstone of the country’s industry. The company produces a wide range of petroleum distillation products with a daily production capacity of approximately 197,000 barrels of oil. Their key operational goals include optimizing output, streamlining maintenance costs, and increasing profit margins. To achieve this, they needed a solution to drive immediate impact and YoY results. 

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The Challenge: Balancing Maintenance Costs Across Complex and Hazardous Operations

This manufacturer relies on a complex array of machines to turn crude oil into petrochemical products. Maintaining this complicated network of equipment is essential to keeping production running continuously and efficiently. However high maintenance costs were impacting operational budgets and machine issues were increasing downtime, safety, and environmental risks. 

Prior to deploying Machine Health, the company relied on different maintenance strategies, like route-based, preventative, and run-to-failure, and used portable data collectors and manual analysis tools. This led to inconsistent machine data, delayed repairs, and occasionally unexpected or extended outages. The team knew they needed to change their maintenance approach and that access to real-time machine data could save them considerable costs and inefficiencies. 

The Solution: Reduce Maintenance Costs Without Sacrificing Standards

To reduce costs and improve maintenance practices, this petrochemical producer needed a solution that could monitor heavy industrial equipment and reliably collect data across their most important assets. They weren’t interested in solutions that provided generic alerts. They wanted insights with root cause analysis that could recommend maintenance actions. This meant finding a technology partner that could deliver highly accurate diagnostics at scale, across a variety of machine types.   

With Augury’s Machine Health, their teams found an end-to-end AI solution backed by reliability experts and a proven track record of helping industrial customers achieve fast results and strong adoption. 

Impact on Maintenance Costs Year-to-Year 

In 2021, the manufacturer piloted Machine Health to ensure immediate and long-term value. The team deployed the solution across a specific set of redundant assets and saw huge potential. After a 1–2-week baseline period, real-time insights into the health of their equipment exposed many issues. With access to prescriptive alerts that identified the issues and recommended courses of action, they could plan and execute their repairs. This created early buy-in and adoption from site-level teams.

Since their initial deployment, the overall health of their equipment has exponentially improved. A financial analysis conducted on a set of machines monitored by Augury from the 2021 pilot to the end of 2023 shows how their team increased reliability and lowered maintenance expenses year after year. 

The Result: Impact on Maintenance Costs Year-to-Year

The financial impact of Machine Health for this manufacturer extends beyond maintenance costs. Since most of the refinery's assets are redundant, catastrophic failures typically do not disrupt production. However, machine failures can expose teams to hazardous conditions and derail workdays with unplanned maintenance demands. Since 2021, based on recorded repairs, the company has avoided over 1,800 hours of machine downtime- which means reduced production expenses and risk. 

Ultimately, Machine Health has improved morale and the day-to-day experience of their site-level teams. It has enabled them to change how they do maintenance while increasing overall productivity. With access to steady and reliable data, they are no longer firefighting or acting on outdated information. Now they prioritize maintenance tasks and work as a connected team. 

Scaling for Future Success

Over the past three years, this manufacturer’s leadership has expanded Machine Health to cover the majority of their critical assets, leading to richer details and insights and even more optimized workflows for their teams. 

Year after year, their program becomes increasingly proactive, and data driven. As a result, their cost savings continue to increase as unplanned downtime, costly repairs, unnecessary machine rebuilds, and preventative tasks become rare occurrences.