Tech-enabled asset productivity in chemicals and agriculture

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Excellent maintenance and reliability create significant value in chemical and agriculture manufacturing. Indeed, approximately 50 percent of fixed costs at a typical chemical plant are tied to maintenance, and unplanned equipment downtime is typically the largest cause of lost production.

Chemical companies that get maintenance and reliability right can increase their profitability (by 4 to 10 percent) and the efficiency of their asset bases, resulting in less redundancy and fewer unplanned outages (7 to 13 percent higher overall equipment effectiveness).1 Furthermore, sites with high reliability have correspondingly higher operating margins and better safety records than their lower-reliability counterparts: 7 to 16 percent fewer unscheduled maintenance events, 20 to 30 percent better safety performance,2 and 20 to 30 percent lower costs.

Implementing a successful maintenance and reliability transformation has never been easy—and several factors make it even harder today. The average site suffers from a cycle of excessive unplanned maintenance, which is three to five times more costly than planned maintenance. Average asset life has doubled over the past 30 years, increasing costs to maintain reliability. And large maintenance workforces—saddled with complex work processes and antiquated systems—spend significant time on low-value activities (wrench time is less than 30 percent for the typical chemical and agriculture player). Further complicating matters, many skilled workers are retiring (27 percent of the workforce will retire in the next three to five years). Without them, intellectual capital will be lost, and productivity will decrease. Finally, many of the digital solutions currently in place were initially presented as silver-bullet productivity enhancers, yet system-to-system incompatibility, clunky user interfaces, and poorly planned deployment and integration have led to disappointing outcomes.

With all this in mind, selecting the right asset-productivity approach—one that integrates classic lean thinking with the right digital tools—is critical to achieving the next level of maintenance and reliability performance (exhibit).

World-class asset productivity requires a combination of traditional and  tech-enabled levers to create value.

As traditionally lean fundamentals and external spend management have the highest potential impact, they should be the top priorities for enhancement. Other areas of high impact include deploying the right talent for reliability analytics and overinvesting in work execution planning and scheduling. Digitization and analytics, assuming they are built on a solid lean foundation, can help achieve and sustain lean productivity gains. Utilizing condition-based maintenance to prevent failures can also be productive. Finally, failure prediction through machine learning has the potential to create value for certain assets, assuming sufficient data exists to develop advanced analytics algorithms and the cost of failure warrants the effort involved in developing and maintaining models.

Selecting the right approach requires comprehensive knowledge of the problem at hand. Companies looking to improve maintenance and productivity typically face one of three scenarios, each of which requires pulling a unique combination of levers.

  • Rapid cost reduction: This scenario occurs when there is an urgent need to cut costs to increase competitiveness; it involves eliminating less-valuable tasks, improving execution efficiency, and better selecting and managing contractors and spare parts.
  • Increased product sales: If there is an opportunity to sell more product, companies can focus on maximizing critical-asset reliability, minimizing unplanned events and the execution of planned events, and increasing overall excellence in turnaround planning and execution.
  • Digital excellence: The third scenario applies to companies that have mastered traditionally lean fundamentals and are looking to achieve the next level of productivity, supported by digital and analytics. Success here requires identifying and deploying the right digital tools while avoiding pilot purgatory and drawn-out implementation timelines.

One large global chemical manufacturer’s excessive focus on short-term cost reductions over the years led to a reactive maintenance culture. As a result, inadequate reliability contributed to missed production deadlines and unmet customer commitments. The high volume of mechanical break-ins made it nearly impossible to plan work, and mediocre scheduling practices translated into inefficient execution, with wrench times between 15 and 20 percent. Preventive maintenance was not done on time, leading to an unmanageable backlog of more than 30 weeks of work in the pipeline. Consequently, equipment was highly unpredictable, and frequent breakdowns limited production capacity.

The manufacturer implemented a two-step solution to maximize effectiveness and efficiency. First, it redesigned its management processes (prioritization, gatekeeping, and planning) and clearly defined maintenance and reliability roles. Second, it adopted a digital tool to improve work scheduling, cross-functional coordination, and task speed.

This combination of traditional and digital levers drove rapid improvements. For starters, planning and scheduling productivity improved by 30 percent, and wrench time improved by a factor of 2.5. The backlog was reduced to less than two weeks and preventive-maintenance compliance increased substantially, reducing unplanned downtime by nearly 10 percent. Finally, as equipment reliability improved, so too did customer satisfaction. As a result, the plant regained the sales team’s confidence in its ability to meet demand and take on more production.

Every chemical and agriculture manufacturer has its own unique experience with maintenance and reliability and will therefore begin the journey toward tech-enabled asset productivity at a different point. To ensure that journey is as successful as possible, companies should assess the specific needs and opportunities for value creation and then select the right transformative approach.

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