Delayed Response – A Red Flag in Manufacturing
It is a unique time we are living in. If we have learned anything by now from the events of the past couple of months, it is the importance of having an agile business model that can respond rapidly to any number of unexpected trends or events. Whether that includes the impact of COVID-19 on manufacturing, the retiring workforce of baby boomers and the influx of Millennial workers, or adopting Industry 4.0 initiatives – business as usual is no longer an option.
Manufacturing leaders in particular need to look internally to understand what support they need to be providing workers, in order to remove pressures associated with the crises above. There are a number of inherent inefficiencies prevalent throughout the factory floor in industrial environments.
At the top of that list are delayed responses.
What is a Delayed Response?
If we break it down to its simplest form, a delayed response is a gap in time between when an event occurs and the response to that event. The gap in time is waste – waiting – and it is tied closely to the efficiency (or inefficiency) of your operations. If you are truly a lean manufacturing operation, then the immediate response to any event should be the appropriate follow-up task. Across more operations, that is not the case.
Delayed responses are often normalized, explained with classic tales of complacency like, “That is just how we do it,” or “It has always been this way.” Make no mistake, that mindset is not compatible with continuous improvement or lean manufacturing, and it is most certainly not congruent with remaining competitive.
The most common delays that we have seen can fall into one of two categories: broken workflows and trending issues. Both lead to non-productive time, unplanned downtime and incidents.
A broken workflow is one that, for whatever reason, is isolated from the task that comes before or after, and requires some sort of manual intervention to overcome.
A common occurrence of a delayed response is when an issue with a machine is reported. For example, if there is an issue during the clean/inspect/lubricate (CIL) process, a worker makes a note of that issue or raises a tag and places the tag wherever it is supposed to go (sometimes on the machine, at the station or on a board in between lines).
What is next? The wait. The waste. Each subsequent step in the process fails to add value to production. After the tag is created, once per shift a mechanic walks the factory floor to pick up all the tags from each line. After gathering the tags, the mechanic enters it into the computerized maintenance management system (CMMS) to convert the tag into a work order. Then, one by one, work orders are picked up or doled out for investigation and corrective action. What was the time to resolution? No one really knows. And what impact did the issue have on production during the wait time? Did the line encounter downtime? Was overall equipment effectiveness (OEE) impacted? Were units rejected for not meeting spec? What is the true impact of these delays in response to production?
If we think about the time from when an issue is initially reported, to the time it takes before someone actually addresses that issue – there are tiny breaks in between throughout the workflow. And there is the possibility for information to be lost along the way. Like death by a thousand cuts, workflows can be delayed by a thousand gaps big and small.
This highlights the criticality of eliminating any delay, even ones we accept as “normal.” In the previous example, by the time someone responds to the issue, the problem could evolve into something much larger.
For example, say there is an issue with the capping machine on a bottling line and it breaks down. One of the valves dropped and broke the revolver that puts the valves in. When you turn to your “5 Whys” analysis to understand why the valve fell, you will uncover the following: Why was it not tightened correctly? Because the operator tightened it, but the carving on the grip was not solid enough so they were a little bit round. Why were they round? Someone alerted maintenance that they needed to be changed a month ago, but they did not change it because it was due to be changed next month. A majority of the time, part of the root cause has been raised by an operator or a maintenance technician, but it is stuck in a queue of all the things that need to be fixed.
A trending issue is an event with a negative or potentially negative impact that happens at a consistent frequency. The longer it takes to identify the trend, the greater the risk the issue becomes to operations.
Tracking and responding to trends is particularly important with regard to safety. Take for example, near miss reporting. A common process used on the floor is to have operators report to their supervisors the details of the event. Supervisors will either grab a paper form to capture the details when they can, or in some cases need to work with the environment, health and safety (EHS) manager to capture the near miss on record (also … sounds a bit like a broken workflow, no?).
Depending on the handling of this process, which can vary from company to company or even site to site, that near miss report may be entered into a spreadsheet or system of record. The delays in that process – from observing the incident to reporting it, from reporting it to converting the key data points into an extractable format – expose an inherent risk that is prevalent throughout operations.
The longer it takes to capture an event and convert it into a traceable format, the longer it takes to track and trend what is happening, leaving unsafe behaviors or working conditions to continue and increasing risk – risk of a lost time incident, risk of a third-party audit failure, or even risk of churn as workers seek better working conditions or expedite their path to retirement.
The same concepts apply to quality, when there is an inability to track and trend compliance to spec and production when the causes of unplanned stops or downtime (check out these interesting stats on downtime) are not quickly identified. Without the ability to efficiently track in real time what is happening, operations put safety, quality and production at risk. The more manual it is for teams to capture information means that there will be delays in action as a result of that data. It could be days or weeks before you are able to access and draw any actionable insight from it.
Back to our example of near miss reporting, after all your data is input into your spreadsheet or system of record, you can now look at the data points to try to determine the possible connections between similar or seemingly separate events. The shorter the lead time between the event and the corrective action, the better. The delay between the reporting of these potential problems and these near misses – which are understood as indicators of future lost time incidents – increases risk. Waiting a week to go through that information because it takes too long to aggregate and interrogate the data increases the likelihood of something potentially worse from happening. The opportunity to course correct quickly is lost.
How Connected Worker® by Parsable Reduces Delayed Responses
Broken workflows, trending issues and delayed responses in general share a root cause – isolation. People are isolated from the processes, systems and people involved in the complex workflows that keep operations running. What further exacerbates the isolation is the fact that processes, systems, workflows and machines are becoming increasingly digital, while the people who must work with these complexities to keep the day-to-day running as smoothly as can be expected are left behind.
This digital isolation can only be overcome through connection, and that is where Connected Worker closes the gaps.
A customer I worked with found that by closing these gaps, line changeovers were made more efficient. They initially deployed Parsable because they recognized the need to go digital and get rid of paper. What they found was that going digital was just the first step, and where the value came from was the connected experience of workers to the work being performed.
Without sharing too much, their line changeovers were what you would expect, for the most part. The machines were safely shut down and various team members (one to two, if I recall) worked to exchange the appropriate parts and adjust the settings to prepare the line for the next product. Depending on the type of changeover, there may be a need for a cleaning, which was to be performed by someone from the quality team.
After reviewing the execution data captured through Parsable, they identified that the reason the cleaning took so long was not because the cleaning required a significant amount of time, but because there was a delay between when the mechanics had successfully shut down the machine and when the quality team was notified that the line was ready for cleaning. When the quality team was finished with the cleaning, the line started back up.
As soon as this was surfaced with verifiable data, they took action by leveraging the embedded collaboration capabilities within Parsable to streamline the alerts – connecting people with the fellow workers with whom they need to work, which helped to reduce average changeover times by 20 minutes on average (up to 40 minutes in some instances). Not bad for a minor change.
The power of connected work brings real-time visibility and real-time response to what is happening on the factory floor, allowing you to connect the dots and quickly respond to unexpected issues and improve inefficient practices. And with the industry trends and world events that are forcing companies to change, companies must find ways to adapt quickly. Waiting continues to be a waste.