How to Measure Quality in Manufacturing
Understanding a handful of the most important KPI’s is the first step toward increasing consistency in the quality of your facility’s production operation. There are five key performance metrics in manufacturing to consider to obtain right-first-time quality.
The 5 Most Important Lean Manufacturing Metrics To Achieve Operational Success
Lean manufacturing strives to boost customer value by improving efficiencies and reducing waste across operations. Moving toward lean manufacturing requires more effective management of materials, human resources, and energy. Compiling and analyzing the right data is crucial to the success of lean manufacturing.
What is Machine Data Collection?: The Data-Driven Approach to Manufacturing
Manufacturers use automated manufacturing equipment (CNC machines) to improve manufacturing processes and increase efficiency. These machines are capable of producing large quantities of products. Machine data collection ensures that your shop floor is gathering accurate data to improve your operations.
A Guide to Factory Floor Monitoring
Data collection from the factory floor is a crucial part of improving manufacturing processes. The data can be used to determine how well machines are operating and what areas need improvement, which will lead companies down new paths for success.
Why Collecting and Analyzing Data Is a Must for Improving Productivity
Collecting and analyzing data is crucial to ensuring long-term productivity and sustainability of operations. Detailed manufacturing metrics from machine monitoring software facilitate the optimization of shop-floor assets, improve overall productivity, and protect the bottom line.
Without this critical information, manufacturers cannot identify which aspects of an asset’s operational efficiency and overall equipment effectiveness (OEE)—availability, performance, and quality—are lagging. As a result, companies fail to identify where inefficiencies and bottlenecks may be occurring, placing valuable production time and money at risk.