Downtime is costly in any industry but particularly in chemical manufacturing where it can equate to hundreds of thousands of dollars or more in waste and lost production. Problems can lead to scrapped output or the need to rework a batch, incurring extra material and energy costs. Safety mandates may require emptying equipment prior to its repair. Cooling and then reheating units to operating temperature takes energy and time. In addition, today's lean supply chain and lower inventory levels may mean insufficient raw materials and finished product are on hand to meet demands.
Most companies, of course, have maintenance programs in place to prevent equipment failures. However, many of these still focus on tactical procedures to track and fix assets; they don't provide much analysis into why assets fail or predict when they will. With today's corporate focus on reducing operational expenses across the enterprise, it's time to assess your current procedures, determine what kind of asset management system you have in place and, depending on what you find, move to a more-strategic process that incorporates predictive practices.
Knowing Where You Are
There are five stages to a company's asset management maturity, starting from the very basic and completing with a comprehensive enterprise-wide maintenance strategy.
1.Operate. In this stage, you are reactive on all of your maintenance; you fix something when it's broken. You take few or no preventive measures. This approach raises downtime costs and often results in lost sales. It prompts excessive safety stocks that reduce inventory turns and increase pressure on cash flow.
2. Consolidate. Here, you recognize maintenance could be improved but can't properly fund a major overhaul in practices. You continue to focus on reactive procedures but add some element of planning, such as ensuring spare parts are in inventory and, when practical, rebuilding instead of replacing equipment.
3. Integrate. This is the stage when you begin to emphasize financial aspects of maintenance. You better communicate return on investment to senior leaders to secure extra funding for additional preventive measures such as routine inspections, lubrications, adjustments, and scheduled service to improve equipment mean time between failures (MTBF).
4. Optimize. As the evolution continues, enterprise participation grows; management support is mandatory. A shift toward predictive maintenance occurs -- data are collected to understand when failure is likely to occur and the business impact. This stage affords significant improvements in MTBF because you're proactively managing risk.
5. Innovate. The final stage includes maintenance as part of a total company system where you combine prior techniques with operator involvement to free maintenance technicians to concentrate on repair data analysis and major maintenance activities.
The stages have closely followed the evolution of enterprise asset management (EAM) systems, from early computerized maintenance management systems (CMMS) to today's advanced asset performance management ones.
CMMS usually is tactical in nature. It provides an understanding of when to repair assets and sets the flow for issuing and tracking work orders. Such a system is well suited to small single-plant operations with limited resources. However, it doesn't take into account the hierarchical nature of complex assets.
Assets aren't isolated; instead each consists of a complex system of other components, likely interrelated to assets across the plant floor. This hierarchical setup requires the ability to monitor, track, report and execute activities based on an understanding of how one move will impact another. Such an asset chess game can be daunting when you realize how far reaching an asset problem can be. For example, a sudden drop in pressure of a liquid moving from one tank to another can be due to many factors, including a crack in a nozzle, build up within a pipe, inaccurate pressure in the origin tank, a pump's motor or even a faulty transformer or voltage regulator feeding power to the entire process. Managing this ecosystem takes an understanding of how each asset works with others, identifying indicators to determine where a failure is and then acting to correct the problem.
Modern asset management systems provide tools to help manage the ecosystem, including:
Asset hierarchies. These help processors view assets from both a system and positional perspective so they can understand true costs of assets with the aim to control, plan and avoid capital expenditures.
Inventory control. This provides real-time visibility of inventory to help reduce inventory and material costs while enhancing purchasing control and efficiencies.
Maintenance control and scheduling. Such functionality helps prevent overtime and lag time and creates a more-effective maintenance team and better work scheduling.
Inspection management. These tools help plan and control inspection routes and measurement points, including those that highlight vulnerability of critical assets.
Regulatory and safety requirements. Specific information capture and material labeling requirements by categorization help manage U.S. Environmental Protection Agency inspections, internal self-audits, spill reports and all safety-related matters; tools provide the ability to track and manage key safety and regulatory data related to assets, maintenance and inventory.
Warranty management. This tool keeps track of asset warranty status to reduce maintenance expenditures and prevent unnecessary work and time on assets under warranty.
Asset analysis. Analytics help you understand why assets fail, the costs to operate them and where each asset is located to optimize deployment. Such tools, while seemingly independent, greatly impact each other.
Realizing progress in your asset management strategy isn't something you can just do with a snap of your fingers; you should rely on five best practices to achieve your goal of a strategic predictive maintenance program.
1. Assess existing maintenance strategy. It's difficult to move forward if you don't know where you've been. The stages outlined earlier provide a good indicator of where you are in your asset management program but you first must understand the past and establish a performance baseline. For example, analyze benchmarks such as percentage of work that's planned versus breakdown related/reactive in nature. Further evaluate these indicators by equipment class (e.g., reactors) or type (e.g., 1-gal. fill lines) to determine more accurate baselines and possibly even root causes of failures.
Also, determine your proficiency in capturing and analyzing asset data. The amount of data you can collect and analyze forms the foundation for the entire program. Often the information needed to drive decisions and processes comes from multiple disparate sources, including your asset management and production systems. For example, the Overall Equipment Effectiveness (OEE) metric requires availability information from an asset management system as well as quality and capacity information from a production system. Likewise, production and maintenance requirements and schedules reside in two distinct systems yet apply to the same equipment. You need a holistic view across disparate sources to drive greater efficiencies and better decision-making. With the right data, you can develop a sense for how your asset portfolio is performing and where to invest additional budget to ensure assets align with strategic goals.
In a multi-plant operation, look at how well you're sharing best practices, inventory management and procurement across facilities. Are common performance measures established so you can make comparisons? Can you easily consolidate information across plants and facilities into a single source of truth for analysis? Is cross-plant collaboration taking place? Answering these questions will help you gauge how well your operation leverages best practices.
Maintenance typically is thought of in a silo, one plant at a time, when in fact multi-location economies of scale can offer substantial cost savings.
2. Identify strategic assets. Predictive maintenance isn't a practice to be carried out across all assets. Identify your strategic assets — the ones that directly impact revenue. For example, a reactor is strategic if it's essential for making product; its performance and availability affect your output. In addition, consider production throughput to determine to what extent equipment failure would lower revenue. Failure of a highly efficient production line that operates at high throughput may be more tolerable to the business than stopping a production line that struggles to meet throughput requirements. Non-strategic assets often are facilities related, pertaining to the physical building such as lighting, stairwells, etc.
3. Determine best indicators of failure. Failure occurs for different reasons and varies by equipment, environment and operating requirements. A pump handling abrasive slurries may suffer excessive vibration before bearing and seal failure while excessive energy consumption may signal wear problems in another pump. Combining performance history of assets, failure studies and references with intuition based on individual experience, trends and patterns emerge. In addition, strategic assets, because of their importance, may merit monitoring of multiple indicators to minimize production disruptions. Also, watch out for false positives. For example, relating high material usage variances to excessive energy consumption in equipment could be a false positive. In this case, the use of extra energy could stem from poor material or formula quality — and thus wouldn't serve as a leading indicator of an equipment performance problem.
4. Automate analysis. Timely action based on real-time operating data is instrumental to an effective predictive maintenance program. The old method of having staff sort through data is inefficient and may provide an outdated analysis because of the time lag. Plus, manual review and analysis takes staff away from performing maintenance and creates a backlog of activity. Automating the process allows action to be taken on the analysis provided.
Analysis and trending technology can take information and, based on your business conditions and experience, identify issues and trends. Actionable analysis derived from software that includes a trending engine can pinpoint problems, filter false alarms, immediately notify stakeholders, adapt to ever-changing conditions and help drive your asset management practice. In contrast to systems that capture, for example, a slurry pump's real-time performance information and produce reports for an engineer to sift through for answers, a system that supports actionable analysis takes this several steps further. It automatically analyzes pump performance data (e.g., electrical consumption) for predetermined trends over time — such as 10% or more excess energy consumption for more than 60 minutes — and alerts key stakeholders to take action when specific conditions are found. An alert can be in the form of a prescriptive set of steps (e.g., 12-point inspection work plan) pertaining to the pump's condition to guide staff through the diagnosis, repair and restore process.
Furthermore, solutions now can assess the situation in real-time, including identifying stalled work orders and issuing alerts to escalate the matter and ensure work is completed and regulations are satisfied.
5. Measure and refine. It's essential to continually measure and refine your asset management program to achieve better results and ensure it expands to cover additional assets and business processes. You should identify the best opportunities for improvement, monitor the most critical areas, implement enhancements and measure them. Evaluate the impact of process changes across the program, not just at one data point.
With today's leaner supply chains and reduced safety stocks, minimizing time to correct issues and increasing equipment availability are becoming more critical. There're a lot of different approaches to measurement from OEE to MTBF and energy efficiency. There's no single Holy Grail for measurement; each company must find one or a combination of several that best meets its needs.
This often is overlooked as part of a company's asset management practice — indeed measurement of energy efficiency is one of the best-kept secrets about predicting failure. Energy consumption actually can indicate, far in advance of a failure, a problem is developing. Consider the example provided earlier of the complex nature of identifying the cause of a change in pressure in the flow of liquid from one tank to another. By monitoring energy usage of each asset, you can tell which asset is either drawing too little or too much energy and start your inspections there.
As an added benefit, asset sustainability — the combination of asset and energy-demand management in one system — has been shown to lower energy consumption by up to 20% across an operation or facility. By measuring consumption across each asset, you can identify equipment drawing more power than the manufacturer specified. The alert generated starts a chain reaction to determine why the asset isn't performing at its optimum and correct it.
To relate this to actual costs, consider a single 100-hp motor running continuously at 95% efficiency for five years. The motor should consume approximately $350,000 in energy (at 10¢/kWh). If the same motor develops a minor problem, not detected by traditional inspections and monitoring, and consumes just 5% more energy, it will cost almost $17,500 more to operate.
The problem is pervasive. Most plants incur significant added expenses by continuing to operate assets whose energy consumption has increased.
When integrated with an asset management system, alerts can trigger when energy consumption or efficiency reaches a predetermined threshold for each asset and can issue a work order for inspection. In some cases, the energy consumption indicator can serve as warning signal for a larger issue that could impact production if not caught early enough.
For chemical processors, failure isn't an option. It costs too much. Capital assets and operational efficiency dictate economic return and determine success. Today's asset management involves more than balancing asset performance and longevity. Companies must employ predictive maintenance techniques on their most strategic assets. In addition, they must consider energy efficiency to develop a comprehensive strategy to eliminate unplanned downtime and reduce operational costs.
John Murphy is director of solution marketing, EAM, for Infor, Alpharetta, Ga. E-mail him at John.Murphy@infor.com.