Two Critical Production Metrics for a Plant Manager’s Dashboard

Two Critical Production Metrics for a Plant Manager’s Dashboard

Two Critical Production Metrics

The majority of, if not all, manufacturers will state that their primary goal is to improve quality. End customers need superior products, and operations managers require high-performing operations throughout their supply chains. Tolerance for anything other than a high-quality product is low, as the risk to the company’s reputation is just too high.

Monitoring operations around the clock in a can making plant is necessary for maintaining a continuously high-quality product. Accurately monitoring shop floor operations affects your power to govern them. Therefore, KPIs are very valuable in managing your operations. To ensure the quality of goods and operations, the two KPIs most often used by Acumence’s can making customers are as follows:

1. Spoilage Analysis

One essential technique to gauge production issues is to determine how much spoilage your factory produces. For example, short-can tear-offs are a common issue and it’s often due to bodymaker tooling that needs serviced. A lack of tooling repair results in high spoilage rates and lost productivity if left unchecked. Unfortunately, operators and maintenance personnel may not fix the equipment without the necessary software to track which machines are experiencing the greatest spoilage until they become a severe operational nuisance.

spoilage analysisMaterials are a typical manufacturing expense. Manufacturers cannot eliminate this expense, but you can control it with the correct business intelligence (BI) solution.

Acumence by Flexware Innovation is a BI software platform that identifies critical indicators such as which machines are primarily responsible for higher-than-average spoilage. Operators may evaluate these metrics, who may locate specific machines creating an excessive amount of short cans. With this knowledge, manufacturers can plan new tooling and machine services before it has a significant operational impact. As a result, manufacturers can see an increase in production, reduction in spoilage, and production flow is improved.

2. Reducing Downtime by Fault and Root Cause Analysis

Downtime is by far the most significant loss faced by the majority of manufacturers today.

According to a Forbes article, “Unplanned downtime in manufacturing is one of the largest causes of lost productivity, causing delays, unhappy customers and lost revenue. In fact, the problem costs industrial manufacturers an estimated $50 billion each year, according to recent studies.”

The first step toward identifying unused capacity is tracking it through the use of real-time data. A distressing situation, such as prolonged decorator downtime, garners the majority of attention because it is widely known. However, it is often the frequently occurring, short-duration downtime events that lead to significant inefficiency.

Downtime Pareto

For instance, a Downtime Pareto report for a decorator could identify the primary reasons for short duration downtime, such as in-feed track jams.  This visual representation aids operators in assessing which machines have the most downtime occurrences and duration and the reasons for that downtime. This analysis can help to streamline a data-driven maintenance improvement strategy.

Implementing Acumence as an enterprise-wide Production Information System simplifies downtime tracking by providing consistent access to real-time data and historical reports. All information is complete and contextualized with no gaps. Operators can rapidly locate outages and access data 24 hours a day, seven days a week.

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