Manufacturing eased last year from a 13-year high. In light of this, manufacturers are faced with the pressures of producing more high-quality goods, with less money, time and resource. Regulations are become more stringent and competition is growing in the market. Due to these increased business pressures, there’s a greater emphasis on alternative ways of being competitive. These include improving speed to market with new innovations and being more environmentally conscious.
To achieve the goals of lean operation industrial manufacturers need to constantly monitor, benchmark and improve. KPIs can prove a valuable gauge of progress, helping manufacturers to set and achieve their business goals.
Many manufacturers still operate preventative maintenance schedules. Preventative maintenance is costly because only 15% to 20% of all components fail after a predictable time. Reducing operational costs means approaching maintenance in a new way.
A predictive maintenance programme – servicing machines based on need-based early stage notifications – is much more efficient than a Fixed Time Maintenance (FTM) Preventative Programme. This allows manufacturers to be proactive, rather than reactive when it comes to equipment repairs and operational downtime. They can make informed decisions, based on transparency and a pattern that is most suitable to their business.
81% of manufacturers are aware of the potential for machine learning to enhance maintenance. With the visibility provided by modern sensor technology and machine learning, maintenance schedules can be updated in real-time and processed on the spot for actionable takeaways. Reduced costs and eliminated outages should be demonstrable when manufacturers transition to a predictive maintenance mode and track overall downtime.
Consider the true cost of unplanned downtime. This could cost manufacturers £180bn a year. The cost is likely to be even greater in the US. Decreasing downtime and improving operational efficiencies can save manufacturers millions of pounds.
By calculating your True Downtime Cost and showing measured improvements in this realm, you can illustrate saved time and money, as well as reduced waste. Understanding true costs can also help you to make cost justification within day-to-day management decisions.
Acceptable Rolled Throughput Yield is dependent upon a very high individual first time yield for each process. It is the sum of the parts measurement that is most critical to overall operational efficiency. RTY is a great KPI to track as it alerts manufacturers to the health of their entire operation, rolling all processes into a single measurement.
Diminish the cost of owning and maintaining equipment by using equipment to its full capacity. By measuring the output that is actually produced and comparing it to its potential maximum output, manufacturers can understand the efficiency of their operation. Increasing capacity utilisation increases overall efficiency.
By multiplying availability, performance, and quality, manufacturers get a score for your overall equipment effectiveness (OEE). An OEE score presents “an accurate picture of how effectively your manufacturing process is running. And, it makes it easy to track improvements in that process over time”.
These KPIs will give you an indication of the overall efficiency of your operation. Any downward trends in performance will require deeper analysis. Manufacturers should also look at processes, systems, and the performance of equipment. With improved visibility and intelligent use of smart technologies throughout the plant, manufacturers can take a leap forward when boosting operational efficiency throughout the business.
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