Downtime is a plague on productive manufacturing. Downtime is a period of time during which a machine, line, or entire facility is not producing any product.
In the food industry, according to Food Quality & Safety, food manufacturers lose as much as 20 percent of their productivity to unplanned downtime, and most manufacturers dramatically underestimate the downtime they are suffering from. Unplanned downtime can cost a typical food processing plant $30,000 per hour.
To maximize efficiency and profit, downtime must be eliminated whenever possible. However, eliminating or even reducing downtime can be harder than it seems.
There are four things that need to happen to reduce downtime:
- Awareness: The people who can respond to a downtime event and minimize its duration need to be aware as soon as a downtime event is happening.
- MTTR reduction: Mean time to repair (MTTR) needs to be recorded so that response times and resulting downtime events are minimized. As downtime responses are evaluated to see what reduces MTTR, overall downtime will decrease. Steps such as having people on call and having the right instruments, parts, and tools available to quickly respond to downtimes are actions that can be taken to reduce MTTR.
- MTBF: Mean time between failures (MTBF) can be evaluated in order to establish preventive maintenance (PM) procedures that will reduce unscheduled downtime.
- Downtime Elimination: The root causes of all downtimes and their frequency and durations need to be understood so that downtime causes can be addressed in the priority of impact on production availability. It’s important to log downtime with a timestamp, duration, and suspected or actual cause so that root cause analysis can be performed.
Effectively tracking downtime in a manufacturing facility is the first step in the process of reducing downtime. Without accurate and comprehensive data, none of the steps above are possible.
Recording information about downtime events is a crucial part of improving the performance of a manufacturing facility, or even a machine or assembly line. Only recording the downtime events themselves isn’t enough on its own, however. Details including the length of the event, the cause of downtime, and which machine or part of the system experienced downtime are vital to understanding how to prevent future downtime events.
Understanding the causes of downtime allows companies to eliminate problems at their source so that they do not become recurring issues that hurt the company in the future.
There are a number of ways in which downtime can be tracked.
Manual Downtime Tracking
Manually recording downtime events and details is often accomplished by hand or using a computer spreadsheet and ideally involves recording all of the relevant details from the downtime event. Unfortunately, manual tracking is seriously flawed for a number of reasons:
- Manual tracking relies on workers who may be busy addressing the actual downtime event and under pressure to restore operations. Because of this, workers may miss certain events.
- Humans are susceptible to pressure to achieve and perform at high levels. A worker may feel that it would be costly to report downtime on their watch in terms of compensation or employment.
- Transcribed data can be lost, whether a physical sheet on which events were recorded is misplaced or a spreadsheet on a computer is put in the wrong folder or accidentally deleted.
- Manually recorded data can sometimes be inaccurate. When manual tracking is used, the length of downtime events is often only estimated rather than actually measured. Worse yet, sometimes short downtime events aren’t recorded at all. These small downtime events can add up to significant amounts of downtime, so it is vital that all events are recorded.
- Employees don’t always record all relevant data, and they may misremember events when they finally get around to recording them.
- The recording of events may rely on a subjective measure of the cause, and different employees on different shifts may use different criteria to decide how to log events.
Automated Downtime Tracking
Automated downtime tracking is an excellent alternative to manually recording events. This method of downtime tracking takes the task out of the hands of the employees and gives it to computer software, which performs it consistently and with a high level of detail. Not only does it accurately record all of the relevant details of each downtime event, but it also lowers the stress on employees, because they only need to focus on operating their machines and getting production back online when a downtime event occurs.
Qualities of a Good Downtime Tracking Software
A good downtime tracking software should have several key features, designed to minimize room for human error and to maximize efficiency and user-friendliness when human input is necessary.
1. Data Collection
One key feature is that as much of the data as possible should be entered into the software before machine operation begins. For example, setting the time should only need to be done once, product information should be entered before a product begins to be manufactured, the shift number can be entered automatically based on a schedule and the pre-entered time, and the machine number can be identified whenever the software is monitoring a new machine.
With all of this information already entered into the software, when a downtime event occurs on a machine, all of these details will be automatically gathered to be noted in the downtime event data, without need for human interaction.
2. Downtime Reason
The reason for the downtime is arguably the most important detail, and it should be identified using the software if at all possible. This can be accomplished by using error codes to indicate to the software what problem has occurred. If it is necessary for the machine operator to enter the reason the downtime occurred, the software must make this process as quick and easy as possible so that an accurate reason is entered.
A list with common reasons for downtime should be presented to the operator—not with so many causes that they are hard to find, but not with so few causes that “other” is the most popular cause of downtime. This reduces the role of individual judgement in recording downtime causes.
User-friendliness is crucial to ensure that the operator logs accurate downtime reasons, because if the operator feels pressured to get back to work, they may select an inaccurate reason for downtime. This will lead to inaccurate data recording and issues with finding the source of problems later.
3. Operator Notes
Another valuable feature to include in the software is operator notes. If an operator is presented with the option of entering notes about the event, this may add information and detail that isn’t apparent in the data recorded by the automated tracking software. After all, if the operator is frequently working at their machine, their input about the downtime event would probably be as valuable as most data collected about the event.
4. Data Storage
Once all of the data and notes for a downtime event are collected, storing the data in a central database or computer automatically at the end of a shift will help to keep the data organized and accessible. With all of the data in one location, it will be significantly easier to compile and compare when looking for ways to reduce downtime later. Additionally, the data won’t get lost if an individual machine experiences a malfunction or memory loss.
5. Effective Downtime Tracking Software
An effective downtime tracking software helps you turn data into insights. SaaS products provide always-on availability to key stakeholders in the downtime information chain and can provide dashboards at the mobile device, laptop, or large screen levels. Customized dashboards let each employee see exactly what they need to in order to effectively do their jobs and crush downtime.
Worximity meets all of the requirements of a quality downtime tracking software. The software ties directly into machinery outputs in order to maximize the accuracy of the data and minimize human error. It also enables operators to easily select the reasons for downtime, removing subjectivity. Data is stored securely in the cloud, and customized dashboards can be created for each key role in the manufacturing hierarchy.