Tips for measuring line efficiency
Quantifying what constitutes a "good day" on your production lines is the first step toward improving efficiency.
What is a "good day" on the processing line and how do you know when you are having one? What would a good day look like? What if you had a system to tell you how good things were going simply by walking your processing floor?
The first thing you need to know is what qualifies as a good day.
Ask most production supervisors and they would say a good day is one where they get all their orders done. A maintenance man would say a good day is one where nothing broke down.
A quality assurance supervisor might say a good day is one where nothing got put on hold. A safety manager might say a good day is one where no one got hurt. The point is they all know what a good day looks like, but how do we measure it?
Measuring how good it is
So defining a good day is the first step. Wouldn't it help if you knew every hour how many trays, bagged birds, batches, pounds, etc. you were supposed to produce and how many trays, bagged birds, batches, pounds, etc. you actually produced?
Now you can begin to see if you are having a good day.
For example, if you are supposed to vacuum bag 55 birds per minute, you should produce 3,300 bagged birds or 275 cases of bagged birds per hour.
So, you can count your cases every hour or put a counter on your machine.
Do what you must, but start measuring your throughput rate every 60 to 90 minutes. Some would argue that is too often and feel that measuring throughput at each break is enough. Ask yourself how often you look at your speedometer if you were going to drive for 8 hours.
You would probably look at it more than three to four times. In fact, you would look at it more than once an hour. So why let an entire production facility run two to three hours before looking at its speedometer?
The same measurement practice holds true for any process whether it's deboning 36 birds per minute (2,160 per hour), overwrapping three piece trays at 24 trays per minute per machine (1,440 per hour), measuring is the key. If you are measuring specific processing equipment like overwrap machines or vacuum baggers many have the ability to count the units processed.
All you have to do is track rejects so you can subtract them from the count to know how many good packages you produced in that period.
Measuring packing rates of people is a little trickier, but it can still be done.
For example, if you are trying to measure the packing of trays that feed an overwrap machine, you can track a person's tray usage. By counting the trays each person packs, a supervisor can give positive affirmation to individuals who are meeting or surpassing their planned rate and coach those who are not.
What gets measured gets fixed
Now that we have created a production goal and are measuring it, what happens when we don't meet the goal?
Let's say you are supposed to produce 275 cases of bagged birds in an hour. At the end of the first hour you count cases and find you have only produced 245 cases. Working backwards shows there were 30 cases that did not get produced (275-245=30).
This is equivalent to about 7 minutes of lost time (30 cases times 12 birds per case divided by 55 birds bagged per minute = 6.5 minutes).
So what happened? Was there mechanical downtime? Did we start on time? Did we run out of birds? Did we run out of packaging material? Did we start late? Why did we not meet our goal?
These are the questions that we need to start asking before the end of the day so we can make changes to ensure it doesn't happen again.
If the same problems are occurring and we continue to lose 6.5 minutes every hour we'll lose 52 minutes which equates to 240 cases of production! Why wait until the end of the day to find this out?
Measuring performance and doing something different when results fall below expectations is the first step in improving any operation. If all you ever do is collect data, all you'll ever get is a lot of data. Taking action by making changes to the process is what drives the success.
Make the invisible visible
As managers and supervisors you would want to be able to know if you are having a good day, but what about the people actually doing the work? Don't you think they want to know how well they are doing?
This is why the results need to be visible. Creating a graph or chart to post results not only gives the production personnel feedback, but makes it easy for supervisors and managers to see how things are going.
This allows them to take better decisions regarding where they need to spend their time. Additionally, posting the results in either red or green can break down the language barrier and help to involve everyone in the plant.
When a production line does not meet its goal, the supervisor needs to solve the issues plaguing the processing operation.
Again, they are doing this throughout the production day, not waiting until the end of the day when it's too late to fix the problems.
And once they begin to realize that management is going to review their results or may ask for an explanation while walking through the department they will begin to experience a sense of accountability.
To automate or not
As soon as supervisors are asked to collect data and perform simple math on the production floor, management and IT want to find a way to automate the data collection.
The arguments for and against are many, but experience has shown the manual method can have amazing results.
Once everyone is into the routine of data collection, it shouldn't take more than five to 10 minutes an hour.
Forty to 80 minutes a day (8-16% of a typical eight hour shift) following up on the status of their department does not seem an unreasonable amount of time for supervisors to spend.
Additionally, by requiring the supervisors to post the results on an hourly basis, they are required to be on the production floor, know what the results are and if they are not meeting the set target, knowing why and doing something about it. This forces active participation in the success or failure of their operation.
It creates a sense of ownership and accountability that one can easily lose when they have to go into an office to get their data from a device which is not on the production floor.
So, the next time someone asks if you are having a good day, I hope all you have to do is glance at the chart on the wall so you can honestly answer, "As a matter of fact, yes I am!"