In-School Productivity Campaign | Overall equipment effectiveness - a critical productivity improvement tool for managers

Today's consumers are more sophisticated - they are demanding products and services that are fast, readily available and of superior quality. As a result, specialised equipment along with people are a company's most valuable and necessary resource that work together to exceed customer expectations. Gone are the days when customers would not react negatively to being told that their orders are not ready because the machine broke down.

This means that the use of equipment increasingly play a critical role in business excellence, particularly in equipment-intensive enterprises that engage in processes such as: electricity generation, printing and manufacturing. If the success of your company is heavily dependent on the use of equipment, then investing in Overall Equipment Effectiveness (OEE) is definitely something you should explore.

Professor Holly Ott of Production and Supply Chain at the Technical University of Munich, considers OEE as a key metric and tool to manage equipment-intensive production processes. OEE is a measure of system productivity that helps management determine how well their production unit is performing relative to its designed or rated capacity during scheduled production runs. Simply put, OEE measures the ability of the system to produce repeatedly what is expected.

OEE was proposed as a hierarchy of metrics by Secichi Nakajima to measure the performance of equipment in production facilities. It was first described as a central component to the Total Productive Maintenance (TPM) concept, which is an organisation-wide effort to reduce losses due to equipment failure, slower speed and defects.

There are three (3) fundamental components which determine the OEE within production systems, these are:

1) Availability - This component includes all events that stop planned production for any appreciable length of time such as equipment failures and material shortages and planned stops (such as setup and changeover time). Availability means we want the equipment to be ready for use when needed. For example, availability of generating equipment is central to the smooth operations of an electricity generation business.

2) Performance - This component focuses on all factors that cause the production asset to operate at less than the maximum capacity. For example, when running slow cycles and short stops.

3) Quality - This component refers to conformance to production specifications and determine product quality in a manufacturing process environment. A good example is a machine which over-fills or under-fills bottles. Reducing unnecessary yield and product defects will improve OEE, additionally start-up yield losses will also affect quality.

Now that we have an appreciation of the components it is clear that calculating OEE requires extensive measuring and data collection and multiplying each to derive a final OEE number. This now creates perspective for us to realise that minimising losses in each of these components are critical in achieving an acceptable OEE value of 85 per cent - where 100 per cent is perfect, 60 per cent is typical and 40 per cent is low.

The strength of the OEE metric is in making losses more transparent and in highlighting areas for improvement. Breaking out each of the three components into six key groupings allow for tailored solutions toward improvement. The six main sub-groups of OEE losses are:

Breakdowns or Machine Failures - eliminating unplanned downtime is critical to improving OEE. Other OEE factors cannot be addressed if the process is down. It is important to know how much and when equipment down time occurs as well as being able to link the lost time to specific source or reason for the loss. With down time data tabulated, the most common approach is the Root Cause Analysis. It is applied starting with the most severe loss categories.

1) Setup or Changeover Times - tracking setup time is critical to reducing this loss. The most common approach to reduce this is the Single Minute Exchange of Dies program (SMED), which aims to reduce set up times and change over time to single minute digits.

2) Stoppage - Minor stoppages and reduced speed are the most difficult of the Six Big Losses to monitor and record. Cycle Time analysis should be utilised to point out these loss types.

3) Reduce operating speed - Reduction in operating speeds occurs when the equipment is running slower than its design or rated capacity. This could be due to a bottleneck in the process, which dictates the speed at which the machines operates.

4) Rework and Scrap - Firstly the input raw material to process has now been lost since it becomes scrap, also the time spent to produce the product has been lost. Secondly, for rework, additional manpower and equipment time have to be utilised which becomes a major waste (over or under-filling of bottles).

5) Start-up yield Losses - This can occur during any type of start up due to changing of shifts that require equipment to be restarted.

In 2017 General Electric (GE) reported on how it utilised OEE to help a well-known food manufacturer that was facing equipment related challenges. GE's intervention involved helping the customer to view real-time production data anytime, anywhere and quickly make adjustments to current production runs. After the intervention the results showed that OEE increased by an estimated 10 per cent over a seven-year period and savings in excess of US$300,000

Having conducted several productivity audits in Jamaica it is fair to conclude that many equipment-intensive production facilities do not utilise OEE as a key productivity metric. Since OEE is data driven it is impossible to manage or improve existing equipment effectiveness if measurement is not being done. OEE data can be collected and monitored in a simple manual way for starters or with a standalone integrated IT system.

OEE is one of the most powerful measurement tools that when applied correctly, allows managers to make effective, accurate, and objective decisions in real time for greater productivity and optimised equipment performance.

- Jonathan Isaacs is a productivity specialist at the Jamaica Productivity Centre.