The productivity of scientific and technological assets in chemical companies and agriculture
Choosing the right combination of traditional and technical support maintenance and reliability solutions is critical to improving performance and operating profitability.
Excellent maintenance and reliability create great value for chemical and agricultural manufacturing. In fact, about 50% of the fixed cost of typical chemical companies is related to maintenance, and unplanned equipment downtime is usually the biggest cause of production loss.
Chemical companies with proper maintenance and reliability can improve profitability (4% to 10%) and asset base efficiency, thereby reducing redundancy and unplanned downtime (7% to 13% overall equipment efficiency). In addition, the sites with high reliability have higher operating profit and better security record than those with low reliability: unplanned maintenance events are reduced by 7-16%, security performance is improved by 20% – 30%, and cost is reduced by 20% – 30%.
It has never been easy to achieve a successful maintenance and reliability transformation in chemical enterprises. Now several factors make it more difficult. The average site suffers from excessive unplanned maintenance cycles, which is three to five times as much as planned maintenance. Average asset life has doubled in the past 30 years, increasing the cost of maintaining reliability. A large number of maintenance personnel – burdened with complex workflow and outdated systems – spend a lot of time on low value activities (less than 30% in typical chemical and agricultural enterprises). More complicated, many skilled workers are about to retire (27% of the workforce will retire within the next three to five years). Without them, intellectual capital would be lost and productivity would be reduced. Finally, many of the existing digital solutions were initially proposed as silver bullets to improve productivity, but the incompatibility of system to system, clumsy user interface and improper deployment and integration lead to disappointing results.
With all of this in mind, choosing the right asset productivity approach – one that combines classic lean thinking with the right digital tools – is critical to achieving the next level of maintenance and reliability performance.
As the traditional lean base and external expenditure management have the highest potential impact, they should be the first task of strengthening. Other areas of significant impact include the deployment of appropriate reliability analysts, as well as over investment in work execution planning and scheduling. Digitization and analysis, assuming that they are built on a solid lean foundation, can help achieve and maintain lean productivity. It is also effective to prevent failures by using condition based maintenance. Finally, it is possible to create value for some assets by machine learning fault prediction, provided that there are enough data to develop advanced analysis algorithm, and the cost of fault also ensures the efforts of development and maintenance model.
Choosing the right method requires a comprehensive understanding of the head’s problems. Companies seeking to improve maintenance and productivity often face one of three situations, each requiring a unique leverage mix.
Rapid cost reduction: when this happens, there is an urgent need to cut costs to increase competitiveness; it includes eliminating lower value tasks, improving execution efficiency, and better selecting and managing contractors and spare parts.
Increase product sales: if there is an opportunity to sell more products, the company can focus on maximizing the reliability of key assets, minimizing the execution of unplanned and planned events, and improving the overall excellence of turnover planning and execution.
Digital Excellence: the third scenario is suitable for chemical companies that have mastered the traditional lean basic knowledge and hope to achieve the next level of productivity with the support of digitization and analysis. Success in this area requires identifying and deploying the right digital tools, while avoiding pilot Purgatory and lengthy implementation schedules.