In manufacturing, every second counts, so it's not surprising manufacturers are increasingly looking to remove one of the biggest productivity killers found on the factory floor; unplanned machine downtime.
Machine downtime causes disruptions that ripple through production schedules, delay deliveries, and impact the bottom line. In this article, we share some of the most common issues uncovered by our customers when using our machine monitoring platform.
From overestimated machine utilisation to small but frequent stoppages, these real-world anecdotes reveal the surprising ways productivity can slip through the cracks in even the best-run factories.
ISSUE |
DETAILS |
| Overestimating utilisation |
Tracking machine utilisation data through tools such as machine monitoring often leads to manufacturers discovering their utilisation rates aren’t as high as they believed. |
| More machines than people | Data shows that staff managing multiple machines face challenges like divided attention, timing conflicts, increased setup time, and quality control issues. They must balance physical demands, stress, and error risk while optimising workflow across machines. |
| Small stoppages, add up |
Brief, recurring stops due to things like misfeeds, minor jams, or adjustments may seem small but if gone unchecked can significantly erode productivity over time. Monitoring reveals their true cumulative impact. |
| Opinions, not facts | Manual methods of reporting often capture operator annoyances and niggles rather than true top downtime drivers, leading to misplaced priorities and missed optimisation opportunities. Machine monitoring replaces opinions with facts. |
| Bottleneck Blindness |
Machine monitoring pinpoints the actual causes of production bottlenecks by capturing the downtime reasons from operators. This data enables targeted and continuous improvement to be made to processes, leading to greater productivity. |
| Housekeeping | Regular housekeeping on the factory floor is critical to maintaining a safe operating environment, but you'd be surprised how much time can go unchecked. For example, Machine downtime caused by swarf management is often overlooked. Machine monitoring identifies the true amount of time spent on swarf management and can identify where process improvements can be made. |
| Output and hours invested not aligning | Production output falls short of expectations based on available manpower and hours. Machine monitoring software can easily uncover the root causes. |
| Staffing miscalculations and skill gaps |
Inaccurate assumptions about staffing and skills lead to lost productivity. Data-driven insights can optimise resource allocation, inform training needs, and improve staffing policies, reducing downtime and enhancing efficiency. |
W. Edwards Deming once said, “Without data, you’re just another person with an opinion.” But that was before the rise of modern technology. If he were around today, he’d likely add, “But not all data is created equal.” Nowadays it is clear that traditional pen-and-paper methods often edge closer to guesswork than solid facts. Automated data capture, on the other hand, delivers accurate, real-time insights that cut through the noise, and identify the core issues giving you the clarity to make decisions grounded in reality.
