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    CTodd Lombardo
    CTodd Lombardo MachineMetrics / April 29, 2020

    Actionability: You Have the Data, What Now?

    Machine monitoring surfaces data to you. Do you know what to do with it?   


    The Problem 

    Data, data everywhere, yet not an action to complete

    You spent the time to connect your machines to get production data, and now you have the percent utilization across your factory floor. (By the way, it’s likely lower than you think). Once a manufacturer has connected their machines, we often hear the question: “What do I do with all of this data?” 

    Too much data can paralyze a team because they are unsure how to take action. You may have also heard the term “analysis paralysis” which refers to when you’re mired in data analysis and not taking action on an insight staring you in the face! 

    More often than not, we hear teams are only scratching the surface with the data they have available.

    The flip side to this problem is not having actionable data and relying on staff experience to make decisions. Even with the highest trained staff and experienced machinists, these decisions can be incorrect, resulting in downtime, unwanted scrap, and a frustrated team.


    The Solution

    Communicate continuously, and utilize monitors to drive action

    We have seen these four key principles work well across many of our clients.

    1. Visibility: If you can see it, you can do something about it. From the many conversations we have had with customers, we find the most successful teams continuously look at their data and make that data visible to the right people in the organization. For example, one of our clients places TV monitors in their lunchroom so if something goes awry during lunch, a staff member can address it immediately.
    2. Communication: Successful organizations communicate the data to the team. Many of our clients run a “stand-up” daily meeting at the start and end of each shift where the shift teams overlap and there can be a transfer of knowledge. Many of our customers take snapshots of their daily production reports and share them with the team so they can see the broader picture. We’ve seen many of our customers literally print out copies of the weekly reports and tape them to their machines.
    3. Action: Any successful IoT platform implementation includes the most important step: taking action on the data. Here is a perfect example of a team that is using the data to take an action towards resolution: One of our customers set up a Monitor in our product that looks for a particular alarm code. If that alarm code is thrown, their maintenance team receives an automatic text message. This alerts the right person on the team to take action at the right time. One of our customers experienced a significant drop in maintenance response time just by having these notifications sent to the right staff members. Further, by including relevant information, staff members can be better prepared to address the problem. A maintenance tech would need to approach a spindle failure or a compressor issue very differently, so having the context beyond ”there’s a problem” is a time-saver.
    4. Follow-up and prioritize: Any action taken that might solve a short-term problem is great. Identifying longer term patterns, however, is likely to lead to an even larger impact. One example a client experienced was an alarm trigger that occurred frequently on a machine. The operator was able to solve the issue quickly, however in looking at the data across multiple days and weeks, this alarm was triggered on average 40 times per day. With an average time to resolution of 45 to 90 seconds, this added up to nearly one hour of unproductive time across the shift! This example of “low-hanging-fruit” was able to instantly provide an impact to the customer.


    In Review

    Data is a tool. And like all tools it is only as good as the person using it. Further, data without context  and without visibility to the right staff members it is of little use to anyone. As we continue to collect more and more data from machines, it’s incredibly important that we make the data available to the right people so that they are able to appropriately follow up with action. In doing so, data has the ability to create an immediate impact across the factory, with the potential for that impact to be amplified as greater amounts of data are collected over time.


    By C Todd Lombardo with input from Jonathan Bicknell


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