An investigation showed that operations had decided one employee could
operate a machine that regularly required two employees. In fact,
sometimes they assigned one employee to operate two machines. Usually,
one employee would keep the machine fed and cull out poor feedstock,
while a second would remove the processed product and clear the jams
that occurred every 10 minutes for about 30 seconds.
OEE was down to about 40 percent for equipment that usually achieved 70
to 80 percent. Further investigation revealed a wider batch-processing
window than on the other shifts.
The bottom line was that the labor cost per unit processed was reduced
by nearly 40 percent while meeting production timeframes. Operations
really did not know the makeup of OEE, and instead of defending their
numbers, they chose to cast blame.
For those who do not remember the OEE formula, for the required run window, it is:
Throughput performance percentage x quality performance
percentage x uptime performance percentage = OEE (expressed as a
percentage)
That is the quick two-penny version.
Who uses OEE? Hopefully, it is used by those who know what the three
factors mean and how they are measured. My experience says there are
various levels of OEE.
OEE was thought to be the miracle metric by some organizations, and a
lot of management attention still is paid to the metric. I submit that
the metric at a plant level means squat to the line operator — and plant
level was the original use of OEE. Yet it is this operator and his or
her maintenance technician that makes or breaks the company during the
operating shift.
Could an OEE be developed that was a meaningful metric to the line
machine operators? How about for the engineers and process developers
who established equipment performance and line-balancing parameters? How
about the supervisor who oversees a production of machines in series?
How about the planners and schedulers? In other words, specific OEEs
could be developed that represent the specific impacts various players
have on the plant performance.
I’ll even go one further. How about the finance guys who watch the pennies? How about human relations?
Most companies recognize the importance of customers, employees,
resources and the bottom-line budget performance. It not possible to
separate them, yet each must be managed.
In the late 1990s, my old organization searched for a meaningful metric
to gauge employee motivation and satisfaction with the workplace. The
usual factors of safety, attendance, Equal Employment Opportunity (EEO)
complaints and grievances were numbers that alone could not be
individually correlated to performance.
As we moved out of the 1950s and into the enlightened times of the late
20th century, the old term KSA (knowledge, skills and abilities) did
not seem to be the end-all when dealing with workers. We wanted them to
no longer leave their brains at the front door. We wanted the whole
person on the job. Empowerment, quality of working life, involvement,
and the importing back into U.S. industry of Deming’s and Crosley’s
quality concepts caused an upheaval in how management must view and
treat the worker. Then came total productive maintenance, lean, Toyota,
process management and a host of other programs.
The literature began to talk of employee talents, situational
flexibility, learning organizations, systems thinking, self-direction
and self-motivation. My organization categorized this as employee
willingness. Yes, we hire a person that walks through the door with
KSAs. What happens to his or her willingness or desire to produce to
his/her finest? Can we measure that, and what do we need to help him or
her walk out of the plant at the end of the day feeling satisfied?
I once had a manager who said that if we provide the right tools and
timely, pertinent information, then employees will work. That means the
organization exists to support the employee.
OK, so how does all of this hot air relate to OEE? It can be timely
information. It can identify training and skill problems. It can
indicate process and equipment problems. And, it is a barometer of
employee willingness. Should, therefore, OEE be an analytical metric?
Absolutely. Otherwise, throw it away.
The bottom line was that OEE became a top-level workforce metric for
plant management. At the same time, all processing equipment produced
(in real time) the OEE that the operators managed to gauge their
performance and analyze problems. The biggest issue was to train
supervisors and superintendents to use the same OEE as a diagnostic tool
to help remove obstacles to operator performance.
The directors of HR were now held responsible for understanding OEE and
how it should be viewed and used. It was no longer an “operations
problem” but a plant-wide tool to recognize employee excellence.
by Rex M. Gallaher
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