Production processes with minimal downtime can free up capacity for when demand spikes. This reduces direct labor costs, which allows companies to make more money with the same amount of resources.
When reducing downtime, it’s important to identify which factors are the most impactful. This includes determining how much time is lost due to equipment problems, material shortages and operator errors.
In manufacturing, downtime can cost manufacturers in lost revenue, angry customers and even possible legal penalties. However, a break in production doesn’t have to be a total disaster. With a few smart strategies, manufacturers can minimize downtimes and increase ROI.
Robotics is one of the most advanced technologies manufacturers can use to keep their production running. These robotic systems have multiple applications, including reducing warehousing costs and producing products on demand. Additionally, they can reduce the need for costly tooling by using pre-made fixtures and adapters.
With advances in sensor technology and machine learning, robots are continually becoming more useful in manufacturing. They are now able to work alongside humans and take on more complex tasks. The latest advancements in robotics also allow them to be programmed faster and more efficiently. The ability to monitor robot performance in real-time and make adjustments on the fly is a game changer for manufacturers. Moreover, robots consume significantly less energy than traditional industrial equipment.
Sensors can help manufacturers detect and resolve issues that may lead to unplanned downtime. By logging performance aberrations, sensors can identify potential machine failures before they occur, allowing maintenance teams to address them as soon as possible.
Today’s sensors are trending away from hard-wired end-point transducers and toward onboard computers with decision-making functions that can be adjusted based on a factory’s specific requirements. This new design places more flexibility and software-adaptive capability into the hands of designers rather than relying on a wired connection to an off-site server for data analysis.
For example, a production line monitoring sensor uses a photoelectronic beam proximity sensor to count and timestamp products as they pass over on a conveyor. Edge computing at the sensor node then calculates the product count and time increments, and wirelessly transmits the results to a gateway and a cloud-based application for real-time production count and downtime tracking. The sensor node comes factory pre-configured for easy installation.
Manufacturing downtime can create unhappy customers and even ruin a company’s annual profits. Manufacturers need to identify the best strategy for avoiding downtime and ensure they have visibility into human and machine performance across all processes.
When deciding whether to automate or not, start by collecting as much data about your current costs (including product loss, safety risks and employee training costs). Then, decide how you want to allocate those resources in the future.
Automation technology excels at repeatable, rule-based tasks that are easy to learn and understand. It can also reduce your energy consumption, cutting down on your facility’s operating costs.
However, the upfront cost of hardware and software can be high, so it’s important to calculate your costs before making the decision. Additionally, human labor is valuable for strategic, complicated tasks that machines can’t perform. That way, you can repurpose staff and eliminate unnecessary overhead expenses while saving on production costs. Ultimately, the combination of reducing labor while increasing high-quality output will result in a positive ROI for your business.
Monitoring production downtime objectively gives manufacturing teams the data they need to reduce machine issues and operator errors. A downtime tracker automatically collects and analyzes machine performance to deliver real-time, customized reports and dashboards that make analyzing problems easier and faster. By determining what is causing the most downtime, manufacturers can target areas for improvement like reducing maintenance and repair costs, ensuring employees have proper training, and making sure equipment is in good condition.
In addition, analyzing downtime causes allows manufacturing companies to improve communication by linking employee goals to reducing downtime. This helps motivate workers and makes the connection between their daily responsibilities and production results. A good downtime tracking solution also makes it easy to record preventative maintenance data and see how that correlates with downtime. This helps prioritize and address maintenance issues before they cause production problems. By implementing these manufacturing process strategies, manufacturers can produce with minimal downtime. The time saved and additional profits earned from minimizing downtime are well worth the effort.