To compete in a global market, no organisation will tolerate losses. Overall Equipment Effectiveness (OEE) is such a performance metric which will indicate a performance rate with very simple calculations. It considers all-important measures of productivity (1).
Chandrajit P Ahire & Anand S Relkar, KK Wagh Institute of Engineering Education and Research, Nashik, India
The saying ‘if you can’t measure it, you can’t manage it’ tantamount to a cardinal proverb in management science. The 20 Keys framework provides a structured process approach in measuring the progress of keys implementation from level 1 to level five, providing tangible practical steps to be followed from one level to the next. There are a couple of keys that lend themselves to more process measurements, but require technical measurement intervention to improve their effectiveness, such as key 9: Maintaining equipment. Kobayashi states the core function of key 9 is to prevent breakdowns and eliminate three evils of machine breakdowns (2) which are:
- contamination,
- inadequate lubrication, and
- misoperation (disoperation).
The 20 Keys System does not prescribe any methodology on the measurement of machine effectiveness beyond the level-based process steps towards perfection at level 5.
There are many methods that have been developed to calculate the machine effectiveness based on the elimination of losses that impact on its effectiveness such as
- Overall Equipment Effectiveness (OEE),
- Machine Effectiveness (ME),
- Equipment Effectiveness and Reliability Model (EPR), and
- Equipment Effectiveness.
All these methods or models mentioned above are based on the technical fundamentals developed by Seiichi Nakajima (3) to measure equipment and / or machine efficiency by looking at the product of machine availability, performance efficiency and quality rate. The product of these combined measurement leads to what Nakajima coined Overall Equipment Effectiveness (OEE).
This blog will focus on the OEE measurement in order to achieve a pointed approach to the Key 9 technical measurement of equipment and machines to augment its process based measurement as explained above.
In order to maximise machine and equipment effectiveness, Nakajima identified 6 big losses that must be managed in order to maximise overall equipment effectiveness. Table 1 below shows the classification of the six big losses and their origin.
Table 1. The Six Big Losses and OEE Measurements (Nakajima 1988 14)
| The Six big losses | ||
| Downtime | ||
| Equipment failure | From breakdowns | |
| Setup and adjustment | From exchange of die in injection moulding machines, etc. | |
| Speed losses | ||
| Idling and minor stoppages | Due to the abnormal operation of sensors, blockage of work on chutes, etc. | |
| Reduced speed | Due to discrepancies between designed and actual speed of equipment | |
| Defect losses | ||
| Process defects | Due to scraps and quality defects to be repaired | |
| Reduced yield | From machine start-up to stable production | |
Calculation of the Overall Equipment Effectiveness (OEE) (4)
The calculation of the OEE is a clever manipulation of three technical parameters, namely machine or equipment availability during its operation, its performance efficiency and the quality rate of the products it produces as shown below in Table 2.
Table 2: World Class Performance Scorecard (Abdul, Kamaruddin & Abdul Azid, 2012) (5)
| OEE Parameters | Availability Effectiveness | Performance Effectiness | Quality Effectiveness |
| World Class Performance | 90% | 95% | 99% |
| Overall Equipment Effectiveness | 85% | ||
Measuring Availability
Availability or operating rate is based on a ratio of operation time, excluding downtime, to loading time. It is expressed mathematically as follows:
|
Measuring Performance Efficiency
The operating speed rate of equipment is based on the discrepancy between the ideal speed and its actual operating speed. It is expressed mathematically as follows:
|
Measuring Quality Rate
|
Therefore: Overall Equipment Effectiveness = Availability x Performance Efficiency x Rate of quality products
The ‘world class’ performance measurement on availability, performance efficiency and quality rate have been provided by researchers Samat H. Abdul et. al. from the School of Mechanical Engineering Universiti Sains Malaysia, Engineering Campus in Malaysia. This gives an OEE of 85%. It is worth noting that in the 20 Keys Implementation System, the quoted OEE ‘world class’ figures is equivalent to Level 3 which gives an OEE of 85%. In 20 Keys, the highest Level is 5 with an OEE of 95%.
The OEE case study – The Aussie Connection
Researchers (6) from Monash University in Australia and Lund University in Sweden collaborated to investigate the impact of implementing OEE amongst 18 Australian companies. Of the 18 firms, only 6 responded, and whose results were analysed. The summary of their findings is presented below.
(1) Drivers and motives
- Intra/inter firm benchmarking and removal of waste (and identification of losses)
- Be considered as part of a programme to change the organisations operational culture.
(2) Critical success factors
- operator involvement, education and understanding, plus visibility of data/target
(3) Common difficulties, barriers or pitfalls
- Resistive cultures
- Data entry and display was delayed
- Reduced motivation
(4) Critical success factors
- Simplicity of data capture, storage, display and benchmarking;
- Enabling role that management should play in the system (role must shift to the enablement of simplicity (perhaps through automation) to ensure the system’s continuity)
(5) Main benefits or specific outcomes
Primary
- Tangible aspects of performance metrics
- improvements in CTQ [critical to quality] family
- financial dimensions of throughput efficiency
- waste removal
Secondary
- Intangible domain
- HR empowerment,
- engagement and
- morale
(6) Main challenges
- How to maintain the shop floor (HR) engagement and commitment to the system
- Integrating the increasingly demanding objectives of the business
In a nutshell, the researchers’ conclusion is that they found that “the implementation of OEE is typically based on the motivation to use a basic reference measure for analysing and comparing the utilization of resources at the plant. The use of OEE can also be transformed to a system for analysing production data to identify potential areas of improvement, and supporting lean initiatives”.
The implementation of the OEE is very difficult if it is implemented manually because the calculations are complex and cumbersome, and this can be compounded further if one is dealing with a large battery of machines and or workstations. This does not discourage companies from setting up an initial base even if it is for a few machines. Practitioners of TPM are beginning to use computerised systems to optimise the OEE calculations. The Romanian researchers (7) at Valahia University of Targoviste have presented two case studies of OEE computerisation systems. The first one is by a Turkish Doruk Automation Enterprise which implemented a computerized system that monitors the work on line and displays the values of OEE for each workstation in real time. The second one is a Romanian domestic appliances manufacturer ARCTIC Gaesti that implemented FICO XPRESS optimizer to calculate the OEE.
On the South African shores, there has been a number of companies implementing OEE. For example, Nampak Mono Containers in Maitland, now Huhtamaki South Africa based in Springs, used Excel spreadsheet to calculate OEEs for a battery of their thermoforming machines as part of their TPM world class manufacturing initiatives (experience by yours truly). Roland Rohrs, Chairman of ODI is one of the best authorities in OEE implementation. He is currently teaching OEE methodology to industrial engineering students at the University of Pretoria. Having had the privilege to attend some of his lectures as a guest student, he possesses a rich picture of OEE case studies that he uses to demonstrate his OEE art to his students.
The best way forward however, would be to invest in the 4th Industrial Revolution (4IR) technologies such as predictive analytics, real-time asset health monitoring, and asset tracking, amongst others. All these technologies link directly with Key 9: Maintaining machines and equipment.
As the doyen of PPORF (Practical Program Of Revolutions in Factories) Iwao Kobayashi puts it succinctly when he says: “When factory workers and managers use equipment without properly maintaining it (“we’re too busy for that,” they say), they eventually run into a bigger problem\ breakdown and line, stoppages’ (8). Who can argue against such vintage wisdom?
The 20 Keys System does not specify a particular methodology to augment its process based improvement techniques. However, it leaves a wide room for companies to adopt any method appropriate to their industries to effect and augment the process initiatives within the 20 Keys blueprint, where warranted. Some keys are adequate to achieve highest levels of improvement without an injection of technical measures such as Keys 1 and 3, while others require a drill-down to specifics. Key 9 is such an example. That said, OEE may not necessarily be the only method of enhancing Key 9, but is one of the simplest methods that encompasses machines performance within available operating time, speed and quality to achieve the 20 Keys mantra “better, faster and cheaper”
- Author: Dr Ntokozo Mthembu, Pr. Eng., PhD
- Affiliations | Mthembu-Heath Consulting Engineers; Innovation & Technology: ODI; ASME; ECSA
To read Dr Ntokozo Mthembu’s blog about ‘Balancing job losses amidst innovation – The Kawada Industries’ innovative thinking’, click here.
REFERENCES:
- Kobayashi I 20 Keys to Workplace Improvement Revised Edition (Productivity Press Portland Oregon 1995) 91
- Nakajima S Introduction to Total Productive Maintenance (Productivity Press Portland, Oregon 1988) 21-29
- Nakajima S Chapter 3 Total Productive Maintenance 21-29
- Nakajima S “Maximizing equipment effectiveness” in Chapter 3 Introduction to Total Productive Maintenance (Productivity Press Portland, Oregon 1988) 21-29
- Samat H. Abdul, Kamaruddin S & Abdul Azid I “Integrating of overall equipment effectiveness (OEE) and reliability method for measuring machine effectiveness” South African Journal of Industrial Engineering May 2012 Vol 23(1): pp 92-113 100
- Sohal Amrik, Olhager Jan, O’Neill Peter and, Daniel Prajogo “Implementation of OEE – issues and challenges” https://www.researchgate.net/publication/228974091 (Date of use: 17 May 2019)
- Mâinea Marin, Duţă Luminiţa, Patic Paul Ciprian and Căciulă Ion “A Method to Optimize the Overall Equipment Effectiveness” (2010 Management and Control of Production Logistics University of Coimbra, Portugal September 8-10, 2010) 237-241
- Kobayashi I 20 Keys to Workplace Improvement 91
