PRACTICALLY SPEAKING - How to determine where to target machine improvements

During a career spanning nearly 40 years, I have worked in--and visited--many machine shops. These ranged from small subcontractors to valve OEMs (Original Equipment Manufacturers) and commercial aircraft manufacturers. Everyone is looking to improve their operations. Those who aren’t are either going out of business or already out of business. The real question is how and where does one start?

Follow a simple 3-step process.

Step 1: Focus. Trying to fix everything all at once will ensure that there will lots of effort expended with little return in either the short- or medium-term. Start by focusing on known bottlenecks. These are usually best identified via regular walks through the value stream (known as a GEMBA walk) and by simply asking employees about trouble spots. A few machines almost always have piles of work in front of them while the work at other machines ebbs and flows.

Step 2: Gather data. This can be done manually in the short-term quite easily. It may involve little more than dutifully recording key information on a chart kept close to the equipment and entering the data into a spreadsheet for analysis. There are even sample data collection forms available online that could be tailored to your specific needs. For firms planning on implementing an IIoT (Industrial Internet of Things) strategy, just a few machines can serve as a proof-of-concept or pilot project before investing heavily in a technology solution. Some solution providers, such as Forcam GmbH (www.forcam.com) and 42Q (www.42-q.com), have start-up packages to get automated data collection installed and working quickly on a handful of machines.

Whether collecting data manually, or through a software application, operators will have to input some of the reasons for, and frequencies of, events that occur. To facilitate this, predefine some standardized reason codes for items related unplanned downtime, low performance and impacts on quality. These can be modified along the way based on the frequency of occurrence.

 Step 3: Analysis. Analyse the data to determine a course of action. Standard techniques, such as histograms and Pareto analysis, will go a long way to being able to see the top few reasons for not achieving goals in one aspect or another.

Don’t jump to conclusions

I had an experience where there was a big emphasis from executive management to focus on operator performance to standard time. Fortunately, I was able to hold off and wait for the results of an initial period of data collection. The analysis showed that although standard times could be improved, the BIGGEST improvements were to be found simply in keeping the machine running (productively). Without the data, we would have been going down the wrong path.

By the numbers

Bring this all together by using OEE (Overall Equipment Effectiveness) in a judicious manner. OEE is comprised of three separate components:

Availability – a comparison of the scheduled operating time that the equipment is actually operating

Performance – a comparison of the speed at which the equipment is operating versus the speed at which it is designed to operate

Quality – the ratio of good parts produced to total parts produced

OEE = Availability x Performance x Quality

A worked example of the calculation is shown in the attached image. The boxes highlighted in blue represent the data that users must collect and enter. The rest is calculated by formula. Beyond these figures, operators must be recording reasons and frequencies relating to key events (see step 2 above).

OEE can be used as a high-level indicator and, to some extent, as a comparison between pieces of equipment or even between companies in order to identify a starting point. Its real power is in determining direction by allowing you to answer the question – are we getting better? Exercise caution, maximizing OEE is not the end goal. Improperly used, chasing OEE can lead to poor behaviours, such as running large batches to reduce changeovers and trying to hit peak performance inside those batches.

People use Availability, Performance, and Quality as second level indicators of where to focus improvement efforts or to determine where to collect more, or more detailed, data for further analysis. These metrics can guide us toward the right approach, whether it be to implement SMED (Single Minute Exchange of Die), 5S, or Kaizen to name a few of the key lean approaches available.

Companies should also look at TEEP (Total Effective Equipment Performance) because it introduces the concept of Loading to the equation. Loading is the percentage of calendar time that equipment is scheduled to run. From total of 7 days of 24 hours in a week, we need to subtract planned non-working days, non-working shifts within a workday, and scheduled maintenance. This comes together with OEE as per the formula:

TEEP = Loading x OEE

Significant improvement in TEEP and OEE can come quickly by working with employees and supervision to add shifts, stagger breaks, implement TPM (Total Preventive Maintenance), and other approaches.

TAKEAWAYS: Use data to drive decision-making. Look first for the low-hanging fruit. Don’t chase the metric to the exclusion of good practice.

NOTE: A version of this article was published in Valve World Magazine 2018-09