Manufacturers are in a constant state of improvement. Increasing efficiency and reducing lead times have brought much attention to machine downtime. Companies often underestimate the cost and amount of downtime they experience, despite the fact that it greatly affects the capacity of an entire shop.
The following will explore strategies and solutions to track, categorize, expose, and ultimately reduce unplanned downtime to ensure manufacturers are generating as much throughput as possible.
Machine downtime is based on a complex series of events; it isn’t related to a single event or type of event. Downtime can be expected or a surprise, depending on the circumstances.
The goal of any manufacturing company should be to decrease downtime using data and sound best practices. These practices include eliminating downtime caused by equipment failures or material shortages and a concentrated effort to minimize downtime for cases where it’s expected.
Just as there are several reasons for downtime, there are several different impacts on the company. Planned downtime that isn’t driven by optimized production processes (such as for changeovers and preventive maintenance) drains resources.
Likewise, unplanned downtime due to equipment failures or training reduces efficiency and threatens the ability to complete orders. Dangers include:
Calculating downtime is straightforward. In its simplest form, downtime is:
Planned Time – Actual Operating Time = Hours of Downtime
When data collection is automated and connected to a cloud-based analytics platform, downtime can be broken down by:
These actionable insights can help drive improvement and reduce downtime. If data collection and tracking are manual, deep dives into other aspects of downtime will be difficult.
Manufacturers often know they have problems and cite that the biggest one is downtime. However, that might be the extent a manufacturer knows about the problem. A 2017 report titled "" stated that most companies significantly underestimate their true downtime cost. Additionally, over 80% of the companies lack the data or ability to accurately calculate the cost of their downtime. With recent trends in IIoT, machine connectivity, and monitoring solutions, manufacturers are starting to get answers to questions they did not even know they should’ve asked.
Carolina Precision was able to increase shop productivity by 20% and save $1.5 million by identifying the top causes of downtime using MachineMetrics. Read the full story.
Identifying the top causes of downtime is a good place to start looking for improvement. The most egregious downtime culprits often reveal seemingly obvious inefficiencies and areas for improvement. Below are some of the most common reasons for machine failures and causes of downtime in manufacturing.
Every manufacturing process has periods of time where equipment is unavailable due to setup, tooling changes, material changes, part changes, program changes, or any other changes to production that must be performed while equipment is stopped. However, many of these processes are highly inefficient due to a lack of measurement, analysis, and improvement. While it's highly important to track this time, most shops are unable to do so, and those who do more often than not attempt to do so manually which is inefficient, inaccurate, and the data is often difficult to compile, analyze, and derive insights from.
No one is perfect. Humans get tired, injured, forget, etc. Sometimes operators are overworked or are tending multiple machines. These reasons can lead to a machine going down for a significant time before being noticed. The skills gap is also resulting in a large portion of the workforce retiring, bringing with them deep tribal knowledge that may not be passed on to new hires.
With the cost associated with inventory, many manufacturers want to operate as lean as possible. Unfortunately, a lean inventory can increase downtime events when there are disruptions in the supply chain. Having insight into demand forecasting and materials supply can help to mitigate this problem.
However, it isn’t all about predictive analytics. In one example a manufacturer documented over 14,000 hours for machine setup. After adopting MachineMetrics to automatically track setup times the company discovered the true time for machine setup was closer to 1,000 hours. Being able to reduce planned downtime can free resources and make it easier to spot the size and scope of unplanned downtime. It isn’t necessarily about planned versus unplanned downtime, but rather the largest problems affecting production and capacity.
Manufacturers are under stress. Letting this stress reach the operators can make them feel like they don’t have time to breathe, fix mistakes, perform routine cleaning, or maintenance. A stressful culture of constantly operating at maximum speed can lead to increased operator error and machine maintenance. This is why it’s imperative to have accurate cycle time data to ensure expectations are realistic.
It’s imperative to follow the analytics journey using data as a foundation. Before automation can be adopted and successful, data is needed to bring visibility to the problem and drive the decision-making that can eventually lead to automation. This visibility will show where the problem exists, the extent to which it is affecting production, and how you can work towards solving it. Not everything needs predictive analytics.
Manufacturers may talk about a fully autonomous facility, but you have to walk before you run. Using data as a foundation is the first step to learning what affects production and lead times the most. A production downtime tracking solution provides accurate, real-time machine data and gives workers the ability to log and categorize the causes of downtime. All the information is automatically collected and standardized to be displayed in pre-built and customized real-time reports and dashboards to deliver critical visibility for managers. These insights identify gaps and opportunities for manufacturing leaders to drive improvements.
Here are some strategies to help reduce unplanned downtime:
Without enough accurate downtime data, it’s difficult to prioritize improvement actions. Switching from manual to automated machine tracking is essential for not only understanding the total amount of downtime a shop is experiencing but it’s also helpful for tracking a variety of KPIs, such as machine utilization and OEE. However, operators are still important to downtime data collection. They can provide the "why" behind downtimes by quickly documenting the reason for the event.
With MachineMetrics, operators can easily categorize downtime events on tablets placed at machines. All of this data is collected and propagated in pre-built and customized reports.
For a better view of the shop floor, MachineMetrics developed software with the operator in mind. If the machine is down or is down longer than expected, features appear on tablets placed at the machine which lets the operator categorize and add reasoning for the downtime through the Operator view. Between automatic machine tracking and features that let operators log reasonings for downtime directly on the machine’s tablet, MachineMetrics gives both operators and managers the information they need to make better operational decisions and work to reduce downtime.
Using automatic tracking technology provides real-time visibility to the shop floor, whether stakeholders are on the shop floor or at home. Downtime events are seen immediately on the dashboard. With real-time data and the right software, managers can address downtime as it happens. Additionally, automated notifications can be triggered based on downtime events. For example, if a pump alarm is triggered, MachineMetrics can send a notification directly to maintenance to streamline downtime response. If materials are running low, inventory control can receive a notification to refill or order more supplies to ensure machines do not shut down while waiting for material.
Real-time data also streamlines analysis and reports. The faster raw data is contextualized to be consumed (in reports and dashboards), the faster decision-makers can find and attack the largest causes of downtime. MachineMetrics uses connected technology and advanced cloud computing to deliver accurate fast downtime reports with interactive Pareto bar charts that highlight the top reasons for your downtime.
Downtime Pareto charts easily identify the most common and costly downtime reasons.
Goals give direction to staff and organizations. With accurate data and easy-to-follow dashboards, it’s possible to track production between shifts, operators, and machines to establish baselines and set goals. Other benefits include the ability to:
Overall, goals and accurate data work together to improve overall communication. Employees that understand the connection between downtime and goals, or profit, help prioritize responsibilities and can increase their productivity which can reduce downtime.
Finding the sweet spot for maintenance is possible with the right tools. Tracking machine performance can help adjust maintenance schedules or even predict when maintenance is needed. With the ability to reduce or eliminate unplanned downtime, predictive maintenance is another driver of connected technology. Managers who can predict when a machine needs servicing can prepare and plan maintenance to minimize disruption to production and if any other parts should be serviced during downtime to combine and reduce the overall amount of downtime.
While a platform solution can reduce the amount of hardware needed, legacy machines may still need a way to connect. Simple I/O adapters or on/off monitoring is enough to start collecting downtime data. Most modern equipment will have the needed sensors or technology but may need an Industrial gateway to send data to a platform. MachineMetric offers hardware with multiple ways to connect for quick, easy integration.
With the adoption of new technology, the skills gap, and operator error being common causes of downtime, training is imperative. Training can’t simply be a series of checklists and documents. It must also include a clear understanding of goals. A properly trained employee will reduce downtime by understanding their responsibilities and how they affect the team, production, and downtime. It’s important to enable operators with visibility into production so they can better understand where they stand when it comes to production goals on any given day. While training sounds self-explanatory, having performance data can improve training by identifying knowledge gaps and focusing on more likely challenges each employee might face.
There are a few different types of maintenance in manufacturing. The reactive approach says, "let’s fix it when it's broke." This method is often disruptive, costly, and can result in a loss of production. The proactive approach says, "let's fix it before it breaks."
Proactive maintenance considers the condition of machines and the environmental observations made by staff to help prevent small issues from becoming big problems. The proactive mindset starts with monitoring the entire process and piecing together the data to understand what’s happening on the shop floor. A proactive approach is a broad, important change. When a machine is in optimal condition, it runs smoother and with fewer errors, which means less unplanned downtime.
Several factors can impact the amount of downtime a machine experiences. Some of the most common causes are operator error, equipment failures, material shortages, and other unexpected maintenance issues.
To reduce unplanned downtime, you must first understand how much downtime is happening and where it’s occurring. If you aren't already, track your downtime as a percentage of scheduled production time. Record each downtime event, including how long it occurred and what caused it.
Once you have data, it's time to prioritize. How much downtime is coming directly from equipment issues? Material shortages? Operators not following proper procedures? Whatever it may be, you need to get rid of downtime "killers" to reduce your overall downtime percentage. For example, if an equipment problem is causing the majority of your downtime, you’ll want to focus on how that machine runs and what can be done in order for its performance to match production goals.
Not all factors can be mitigated, but it's a good idea to mitigate as much as you can.
A process control monitoring system must be in place to reduce unplanned downtime. This type of system aims to detect and prevent process conditions that could lead to downtime.
A good process control monitoring system will have the ability to:
It's important to note that a process control monitoring system isn’t a one-time fix. It needs to be continually monitored and tweaked as the manufacturing process changes. Downtime will always occur, but having a stringent process control system in place can minimize the chances of unplanned downtime.
When employees are out sick or on vacation, there's a good chance that your production line will be affected. To maintain consistent output levels when staff members are away from work, it's important to have a solid plan to ensure you have enough coverage to keep up production. Low production levels can add up over time and significantly impact your overall bottom line.
Some things you can do to prepare for unexpected employee absences include:
While these steps can't eliminate unexpected employee absences, they can help reduce the fallout and ensure production continues as seamlessly as possible.
A poorly maintained machine will lead to more frequent breakdowns and unplanned downtime. To reduce this risk, have a detailed inspection checklist in place. A thorough and well-organized inspection checklist will help to ensure that all necessary inspections are performed and potential problems are identified and addressed quickly.
Creating a detailed inspection checklist can be a daunting task. Here are some tips to get you started:
Specific examples of things you should include on your inspection checklist are:
These are only a few basic starting points - your inspection checklist should be as detailed as possible to suit your specific production process.
We all know that accidents can happen and machines can break down unexpectedly. To reduce the impact of such an event, it's important to have a backup of your data, programs, and machine configurations. A backup can help you get back up and running quickly in the event of a problem.
There are a number of ways to make backups. One common and reliable method is to make backups using cloud-based services that securely store your files online. MachineMetrics offers this service through a cloud-based manufacturing software that ensures data reliability through backup and recovery solutions, meaning your data will always be protected from data loss.
Many manufacturers do not have accurate downtime data. They’re unsure of the exact reasons or how much downtime is costing the company. Many manufacturers are experiencing a skills gap and stressed resources. Adding manual data collection, analysis, and reporting only strains employees and resources further. This is why enabling a downtime tracking solution is so important.
With the high cost of production and lack of accurate data, managers can’t make effective decisions to reduce unplanned downtime. Manufacturers must hone processes, reduce waste, and maximize machine utilization. MachineMetrics makes this possible without increasing already strained employees and resources. Our production monitoring software can give you insight into your downtime issues to improve processes and reduce unplanned downtime.
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