Plants Break Down Reliability Barriers

Better integration of data and more powerful software enhance efforts.

By Seán Ottewell, Editor at Large

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Chemical manufacturers are able to collect a wealth of production data but effectively using those data to improve reliability remains a challenge for many firms. However, some operating companies such as Salalah Methanol Company (SMC), Honeywell Performance Materials & Technologies (PMT) and BASF are making the most of their data.

John Harrison, Toronto-based senior solution specialist for software provider SAP, sums up the general situation: “Our chemical customers told us that they had been collecting operational information for years and they believed that there was ‘gold’ in the data, but they lacked the capability to quickly bring multiple sources of data together and to transform the data into actionable information.”

So two years ago, SAP teamed up with Rolta, Alpharetta, Ga., to tackle this situation. Key to the relationship is Rolta’s OneView software that is designed to quickly transform operational data into information, says Harrison.

A project carried out at SMC, Aquad, Oman, provided an early success for the partnership. In 2013, SMC decided it wanted to improve operational excellence, including reliability, by increasing transparency and cross-functional visibility, and by getting a unified enterprise view of its information (Figure 1). It selected SAP Business Objects and Rolta’s OneView.

The companies identified 107 overall key performance indicators (KPIs). Of these,14 solely focused on reliability and maintenance, e.g., covering preventative maintenance compliance, preventative maintenance overdue, planning effectiveness, backlog of work orders, number of breakdowns, maintenance budget compliance, inspection compliance variance, and availability of reliability instruments.

SMC notes the immediate benefits of the five-month project, which was completed in 2014, included automating all business-critical reports, standardizing KPI definitions, minimizing efforts required for reporting, and achieving better transparency and visibility of performance. It also has reduced operational and process failures.

Over the longer term, the company hopes to improve regulatory compliance and operational excellence while maintaining a strategy of continuous improvement across processes and procedures.

SMC says one of its key takeaways from the project is how powerful its capabilities are now, both in terms of compatibility with cutting-edge developments such as the SAP HANA relational database, and of support for the latest technologies such as predictive analytics.

In addition, the strategy has helped SMC break production records: in January the company announced a new peak output of 5 million metric tons/y of methanol.

The strategy an operating company uses for its data depends upon where that company is in the operational excellence cycle, notes Houston-based Richard Martin, senior vice president of engineering design and operations solutions for Rolta. “Some want to start with high-level benchmarking KPIs that cross the facility and enable executives to define metrics that reinforce collaboration and drive enterprise initiatives. Many clients have a specific business issue, for example product development or quality, that they need to address and use it as a quick success to provide predicted benefits, which in turn funds the rollout of a transformation initiative. Other companies are very focused on product development or quality, for example. So what is required varies on a case-by-case basis — but as a whole the industry appreciates that there is value here.”

To illustrate the point, St. Louis-based David Dunn, vice president of business development for Rolta, notes the techniques used at a plant making bulk commodity chemicals— such as predictive analysis and operational risk management — might differ significantly from those needed at a batch production site wanting to optimize a particular product that only is manufactured a few times a year. “Many areas can drive value, including: composite risk identification and management; quality and process improvements to identify and even predict batch quality and create the optimal batch, creating improved plant throughput; and prescriptive maintenance and reliability to improve asset reliability. Ultimately, there are many areas specific to each plant situation where we can help drive down the cost per pound out the plant door.”

However, pursuing better reliability as part of improved operational excellence poses challenges. A crucial one is the basic definition of the KPI being used (Figure 2). “What is included and excluded for the calculation? Does the production quantity include scrap (waste product), or does it only include first-pass product? If you can reuse the scrap to produce good product, how is this quantity included in the waste calculations? I’ve come across cases of 15 different people who work on the same plant all using different KPI calculation methods because of this lack of definition,” Harrison warns.

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