You know that feeling when you forget to start your Apple watch or Strava and you don’t get credit for your whole workout- that’s what it feels like to jump into a data driven project without baselining. No matter what you may be working on, if you don’t know where you started from, you probably don’t have an accurate view of how far you have gone or what you actually achieved. The key variable in calculating distance traveled or progress made is knowing where you started. This is what the Baselining process is all about- understanding where you are so you can know how far you have gone.
Technology implementation often has the goal of making an impact, either on operations or process, etc., and with MachineMetrics, it is no different. Our goal is to improve the operations of Manufacturing organizations around the world. Helping manufacturers understand how much they have improved over time with our product means helping them, first, understand where they are before they implement our technology. We call this Baselining, and it is a vital part of our Technical Validations process for sales prospects and onboarding for our new customers.
We will admit that some of our customers want to jump right over Baselining, but many, after understanding the value, do go through this process. Over time, we have shown just how valuable Baselining is. We have found that most manufacturers don’t actually know where they are today. With limited data available and data tracked in silos and on whiteboards, knowing where you are as a manufacturer can become extremely challenging. This, in turn, makes it difficult to know how far you have gone after starting to use MachineMetrics or other technology.
This article will focus on the Baselining process we use with our prospects and customers which includes Baselining Utilization across a customer’s machines and factory floor overall. For clarity, Utilization meaning is the machine actively executing, or being Utilized, during a set period of time.
By knowing where you are before implementing a new technology, you enable your team to clearly define the improvements that should be made once implemented. This provides a clear ROI and makes the decision making around renewal or expansion crystal clear. For us, this means that our customers don’t have to wonder if MachineMetrics works. Comparing the Baselining data to the data over time speaks the facts.
Our Baselining process consists of 4 Unique steps that naturally end with an improvement plan derived from real data. Because Baselining is measuring where you are now, impacting your operations in any way can skew the results. This is why we ask all of our customers and prospects to withhold from installing hardware on their machines that is visible to the Operators running the machines. If Operators see the installation or hardware, they will likely adjust something about their operations, which will prevent you from getting that clear Baselining data. Now, let’s explore the steps in the Baselining Utilization process:
The purpose of this first step is to get your team on the same page and gather expectations and understand what your team thinks the current utilization on machines is or should be. This is a time when you choose how Utilization will be measured as well. For example, if you have a machine that has a robotic arm that loads material, will you count that loading time in the Utilization calculation? Additionally, the expectations or guesses your team makes about Utilization will later be compared to the actual data. The difference between the expectation and the actual Utilization can sometimes come as a shock.
How would you feel or what would you do if you expect your factory to be operating at 80% Utilization and you discover through Baselining that you are actually performing at 55% Utilization? We talk more about what this means below in the "Evaluating the Data" step.
This is the most important step in the Baselining process. In order to Baseline properly, the data you are using must be good data. Good data means true data. This step in the process answers two questions:
Does the machine operating status match the operating status reported for that machine in MachineMetrics?
Is each machine counting parts correctly? When a part is made, is it showing a part is made in MachineMetrics?
Comparing your team’s original expectations to the actual Utilization data that you have gathered from your machines will be the basis of an important conversation. This will also lay the groundwork for the improvements that can be made and measured.
Back to the scenario where your team guesses that the Utilization is around 80% but in reality, it is 55%. What does this mean?
We see many of our prospects and customers surprised at the actual Baselining data. However, we have seen this represent really positive things for manufacturers. For example, some manufacturers may be considering purchase of new equipment only to find out they have a large amount of hidden capacity within their existing equipment! Without this Baselining exercise, they may purchase another under-utilized piece of equipment, rather than maximizing the equipment they already own.
At this point in the process, you know what your Team expected, you know you are getting good machine data, and you know what the actual Utilization of your machines and factory floor are. Based on what you see in the reports during the evaluation process will determine what adjustments can be made.
There are two types of Adjustments that we outline for customers that can be made after the Baselining Data has been gathered and evaluated: Basic Adjustments and Advanced Adjustments. We always recommend starting with the basic adjustments; We have seen these Basic Adjustments catalyze some of the largest impacts and cost savings for our customers.
After making Basic Adjustments, you may be ready for the Advanced Adjustment: Implementing Operator Tablets at the machine to track Downtime and other Operator input data like Quality.
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