Q 602. Performance is one of the three parameters in the calculation of OEE. How is it sometimes mis-calculated to artificially inflate the OEE numbers? How can this be avoided and what is the right method to calculate Performance? Provide relevant examples.

 

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OEE ( Original Equipment Effectiveness) is calculated as 

 

Availability X Performance x Quality= OEE. 

 

Availability = Availability of the Equipment which is basis on Run time / Planned production time. Run time can be calculated as  of Planned production time - Stop time. 

 

Here there possibility of artificial inflation of Run time by reducing planned production time which can be fix based on RCCP ( Rough cut capacity planning)

 

Performance = It consider maximum possible speed of equipment when it is running. This can also be manipulated by setting up Run Time incorrectly. 

 

Quality = First time Right. It consider parts that need to rework or not meet the Quality Standards. So formula to calculate First time right very simple.  No of rework  or Defects /Total Count.  

 

for correct OEE ( Original Equipment Effectiveness ) we need to aligned parameter like Planned production time, Run time need to be predefined as per Industry benchmark study. 

OEE efficiency takes into account performance loss, which takes into account everything that makes the production process work at  the highest possible speed while it is running (including both slow cycles and small stops).

 

 The decrease in working capacity is caused by, for example, machine wear, poor quality materials, feed failures and blockages.

 

 Efficiency is calculated by dividing the total by the driving time and comparing it to the ideal driving speed or performance = (total / driving time) / ideal driving speed.

For example,

 If you produced 30,000 pieces (total) in 400 minutes and your ideal operating speed is 80 parts per minute, your throughput is calculated by dividing 30,000 pieces by 400 minutes and dividing that number by 80 parts per minute, which equals 0.9375 or . 93.75% throughput. In other words: (30,000 counts / 400 min runtime) / 80 parts per minute = 93.75% throughput.

 

 It is important to note that performance should never exceed 100%. If the performance exceeds this threshold, it may mean that the ideal driving speed is too low.

 

Common methods used to miscalculate performance :

 

Ignoring Downtime: One common mistake is to ignore downtime when calculating performance. Failure to properly account for downtime can lead to overestimation of equipment performance. Example: Suppose a machine produces 100 units per hour, but experiences an unexpected downtime of 30 minutes during that hour. If you calculate performance based only on units produced during an operation, you would mistakenly assume that the machine is operating at 100 degrees of capacity.

Avoid: Efficiency should consider both operational time and ideal cycle time. In this example, the throughput calculation should consider that the machine only worked 30 minutes per hour, resulting in 50% throughput (actual production rate / maximum potential rate).

 

Omitting set-up and change times: Another mistake is to omit set-up and change times from the calculation. These times are important to determine the efficiency of the machine. Example If you only consider the time the machine is actively producing and don't consider the time it takes to set up, it can artificially inflate the performance meter.

Avoid: Allow for setup and changeover times when calculating total time available for production. The performance should reflect the actual production time of the machine.

Performance Rate is the one of the parameter for OEE calculation that measures actual throughput against designed throughput.

 

Manufacturers set the benchmark to achieve the world class results that is generally 85% for manufacturing sector

 

The table below shows right calculation method for OEE estimates for a manufacturing process that produces finished goods at the required throughput.

 

The 3 scenarios listed below demonstrate how performance is commonly assessed incorrectly in an effort to artificially raise OEE for the process:

Scenario 1: Considering design speed instead of standard speed (average actual throughput) – Few manufacturers consider design speed for inflating OEE and believe that there is no opportunity for improvement, thereby reaching maximum available throughput

 

Scenario 2: Considering actual throughput as best throughput achieved instead of average actual throughput – Some managers take best speed achieved in the entire month or period and consider this value for OEE calculations

 

Scenario 3: Increasing production counts for same run time by changing customer specification limits of few parameters such as weight  

 

 

 

 

 

 

 

 

As the name suggests, OEE is an overall measure that reflects performance from several aspects, it computes parameter of availability, performance  and quality into single key process indicator expressed as a percentage. Out of these parameters, performance rate (%) determines that “does the machine produce level of output that it should do” ? The simplest way of calculating the performance rate is “[Actual output / Predicted output ]% “

Actual output : we consider all parts including good and defective

Predicted output : Based upon actual availability and the machine cycle time

sometime, performance rate is mis - calculated due to :

 

Scenario-1: Team forgets to consider rejected part into actual output which results wrong performance rate like below example:

		Data Entry	Unit
Case-1	Good product:	800	pcs
	Defective Product:	200	pcs
	Actual Output ( Good+Defective):	1000	pcs
	Predicted Output:	1200	pcs
	Performance Rate ( with defective part):	83.33%	%	Correct
	Performance Rate ( without defective part):	66.67%	%	Wrong

 

Scenerio-2: Some time team adds old stock also in actual output for showing higher throughput which becomes higher than predicted output and result more than 100% performance rate.

Case-2	Good product:	800	pcs
	Defective Product:	200	pcs
	Actual Output ( Good+Defective):	1000	pcs
	Old stock for posting:	300	pcs
	Predicted Output:	1200	pcs
	Performance Rate ( with defective part):	83.33%	%	Correct
	Performance Rate (  with old stock for posting):	108.33%	%	Wrong

Scenerio-3: Actual output can never be more than predicted output otherwise performance shows more than 100% which indicates that cycle time is wrongly set.

Case-3	Good product:	1100	pcs
	Defective Product:	200	pcs
	Actual Output ( Good+Defective):	1300	pcs
	Old stock for posting:	300	pcs
	Predicted Output:	1200	pcs
	Performance Rate ( with defective part):	108.33%	%	Wrong
	In this case need to review ideal cycle time OEM and subject matter expert

Performance rate includes losses due to Reduced speed, minor stops and idling of machine.

1.      Reduced speed means running the machine slower than the idle cycle time or slow cycle time.

2.      Minor stops and idling of machine i.e., where the machine stops for shorter period i.e., < 5 Minutes. Common minor stops include Material jam, Misfeeds, Flow obstruction, Setting error, Misalignment, Sensor misfunctioning, and equipment design.

Performance Calculation:

Performance rate = Net operating time / Idle operating time

                                             Or

                                             Actual cycle time / Idle cycle time

                                             Or

                                     Actual run rate / Idle run rate

 

Reason for Miscalculation:

1.      Monitor and Recording: It’s difficult for Companies to Track, Monitor and Recording of Minor stoppages. Due to most reasons being chronic and team also have less time for manual data logging.

2.      Reduced speed and Small stop: Reduced and Small stop should be separately captured and analyzed. Since the root causes of these two are typically different separate analysis are required.

3.      Fixing Low Base:  Typically, when a cell is “balanced”, meaning that the Nameplate Capacity of all contributing machines or stages is designed to produce at reasonably close to the same rate, In that scenario, the fastest stage should be kept as target, not the slowest.

Solution:

1.      Cycle time analysis: Automation recording of cycle time for later analysis, hence manual logging can be avoided.

2.      Implement Effective and improvement actions like,

-        Improve the Quality of information for better understanding. (E.g., Automatic logging)

-        Improve the Process that will mitigate the loss. E.g., Standardized work and develop skills through training.

-        Temporary or Quick Fix based on analysis (Referred to as ‘fire-fighting’)

-        Permanent Fix (permanently improve the process so the problem is unlikely to recur).

Overall Equipment Effectiveness – OEE

 

OEE is generally refer to overall equipment effectiveness. This is a key factor in manufacturing and measure performance indicator also used in production industries.

 

This value derived by multiplying three factors :

 

·       Availability

·       Performance

·       Quality

 

This matrix generally used as comprehensive to identify areas for improvement in manufacturing & production industries.

 

Basically, OEE is essential and valuable metric used for assessing manufacturing efficiency, but it can be mis-calculated or manipulated in many ways that artificially inflate the numbers.

 

Below are the few common ways:

 

·       Excluding downtime – If managers are ignoring planned downtime and considering only unplanned downtime for any maintenance or breaks.

 

·       Overestimating ideal cycle time – When managers are calculating any performance, then there would be a chance that they can overestimate the ideal cycle time. This should be based on achievable rates under optimal conditions.

 

·       Ignoring small stops – We should consider any small stops or short interruption if they occur. Sometimes it can be ignored, and calculation would not be accurate.

 

·       Quality manipulation – To calculate OEE, one should consider all defects or rework, if some one is ignoring certain defects or rework then this can artificially boost the quality components.

 

·       Selective time period – Sometime managers considered only ideal time period (selective time zone) and they ignored exception conditions then OEE can be wrong.

 

Data manipulation – any manipulation in data while calculating OEE can lead to inaccurate results.

Best practices to follow to calculate correct OEE:-

 

·       Define clear metric and objectives – Metric and objective should be clearly defined to calculate OEE.

 

·       Capture all downtime – We should capture all downtime including planned and unplanned.

 

·       Account for all production – We need to ensure that all produced units are counted correctly to measure OEE including scrapped or rework.

 

·       Calculate OEE honestly – We should use correct data while calculating OEE.

 

·       Regularly review and improve – Manager should review OEE data regularly and try to identify improvement areas.

 

·       Standardize data collection – We should reliable data source to calculate OEE.

 

·       Training and communication – Project manager should ensure that resources are involved in calculating OEE should be well trained regarding methodology and data.

 

·       Automate data collection – where possible try to automate data collection to avoid any misses.

 

·       Regular audits – Can conduct regular audits to review methodology and data.

 

·       Benchmark against industry – Project managers should set their benchmark according to industry and use best practices to calculate OEE.

Interesting answers to this question. There are joint winners for this question - Ashutosh Bhardwaj and B Ravi Sankar. Do read all the answers for a better perspective on Performance (OEE)