Key Performance Indicators (KPI) are essentially used to understand how quality impacts the production floor and how it can be improved. It is generally used as a Quality Management Systems (QMS) tool that focuses on enhancing customer relations, reducing time, resources and finances and increasing productivity. KPIs provide real-time insights, letting managers fix and solve quality issues on the go. A KPI assesses the entire organisation, which is meant to help managers execute their company goals. It often goes hand in hand with manufacturing metrics, which in contrast to providing an overall assessment of the company, gives specialised insight into one aspect of an organisation’s production.
There are several KPIs that a manager can implement in its manufacturing factory. Traditionally, human specialists spent enormous time arranging data from different systems to analyse and help managers to make critical decisions. Where KPIs were recognised this way, it has proved to not be as effective due to the lack of timely data and the delay in taking positive action. However, with technology, KPIs can now be easily monitored through software. Technology can be infused to ensure that KPIs are seamlessly automated regarding planning, maintenance, complaints or anything else. Manufacturers that keep track of their KPIs and other metrics have performed better in their production processes and sales than those who do not, thereby highlighting the vital role KPIs play.
This article will explain different forms of quality KPIs that manufacturers should take note of.
What Types of Quality KPIs Are Best for Manufacturing?
Throughput
Also known as First Time Yield (FTY), Throughput KPIs assess how many units a machine is producing on an average over time, on a real-time basis. This is calculated by dividing the units produced by the total production time. This integral KPI provides data-driven insights into a factory’s overall efficacy and profitability. Using those insights, manufacturers may re-work processes that affect various other KPIs, including the total cycle times metric.
When the total number of units being produced decreases, it significantly affects the overall process of manufacture. In other words, if the throughput decreases, it is a sign that there is an issue. This will only increase when downtime is eliminated, and steps are taken to maintain the health of machines, ensuring that it runs during cycle time or changing the raw material or tools that are usually used to produce it. In essence, FPY KPI aims to achieve a healthy target of yield, removing all defects in items being manufactured. Hence, managers can understand how specific assets perform and which assets underperform.
Cycle Time
The term ‘Cycle Time’ is defined by manufacturers differently and, at times, calculated differently. Some consider this manufacturing KPI to calculate the time it takes for a consumer order to be completed. This is called Target Cycle Time, which calculates the time taken from manufacturing the goods with raw materials to the time it takes to be packaged, shipped and delivered to the consumer. In contrast, some consider cycle time to refer to the maximum number of parts that can be produced in a particular period (Theoretical Max Machine Cycle). Others view it as calculating the time taken to make actual parts per cycle (Actual Cycle Time). While some can produce multiple parts in a cycle, others may only be able to build one.
Knowing the difference between cycle time KPI is beneficial to understanding the data it produces. Manufacturers are hence able to understand the reasons why processes are slow and consider whether there are enough raw materials and other items required to ensure consumer targets are met. Thus, manufacturers can use cycle time to examine the inefficiencies of both macro and micro scales.
Overall Operations Effectiveness (OOE) and Overall Equipment Effectiveness (OEE)
On the one hand, OOE is calculated by multiplying performance with quality and availability. To assess availability, the KPI considers the actual production time and divides it from the operating time. Through this, managers can track how production is improved over time by comparing the OEE monthly or yearly. Receive instant access to such insights in seconds, especially when it is time to write any reports that help managers to consider the ROI of its production.
On the other hand, an OEE is one of the most integral quality KPIs required for manufacturing. The performance, quality, and availability of manufacturing assets must be calculated to gain the OEE. It is meant to showcase the overall productivity of the machine. Hence, where any anomaly is detected in the machine, the system notifies managers, giving them ample time to rectify it. OEE provides a specific score by comparing the performance of a machine at a certain point to its relative capacity. It should be noted that OEE on a stand-alone basis is not effective and, thus, should be considered with other manufacturing metrics.
