
Where Neural Networks Earn Their Keep in Demand Planning
When neural networks improve demand forecasts, how to train them on short weekly histories, and why every model should compete against simpler ones before it ships.
In today's competitive manufacturing landscape, understanding and optimizing production efficiency is crucial for sustainable operations. This comprehensive blog post explores key production measures that help manufacturers identify opportunities for improvement and optimize their operations for the value chain.
The foundation of production metrics consists of two fundamental measures:
These fundamental metrics provide a snapshot of how effectively production resources are used but to truly understand production performance, we need to dive into more sophisticated measurements.
OEE is the gold standard for measuring manufacturing productivity. It's composed of three critical components: Availability, Performance, and Quality.
Availability is the measure of how much total planned production time is actually used to produce:
Availability = Run Time / Planned Production Time
where Run Time = Planned Production Time − Stop Time
This metric reflects how much available time is lost to both planned and unplanned stoppages.
Performance captures how efficiently the production line runs when it is operating. It accounts for all factors that cause a production asset to operate below its maximum possible speed, including:
Performance = (Ideal Cycle Time × Total Count) / Run Time
Quality measures how many “good” units are produced against the total units started in production:
Quality = Good Count / Total Count
This metric is crucial, as it directly impacts customer satisfaction and bottom-line profitability.
By combining the three components as follows, we have our first key measure:
OEE = Availability x Performance x Quality
While traditional OEE accounts for planned stops and focuses on unplanned stops, tracking planned production stoppages is equally important:
Planned Downtime Ratio = (Total Planned Stoppage Time / Planned Production Time) × 100%
This downtime metric includes:
To ensure sustainable operations, the MCR metric tracks maintenance costs relative to asset value:
Maintenance Cost Ratio = (Total Maintenance Cost / Replacement Asset Value) × 100%
This standard performance metric tracks production planning accuracy:
Performance Against Schedule = |Scheduled quantity - Net Cases produced| / Net Cases produced × 100
Understanding how different types of production time are related is crucial to successful measurements:
Total Time, which is time available in the planning horizon covering both production and non-production periods, breaks down into:
Planned Production Time further breaks down into:
Run Time breaks down into:
Net Run Time breaks down into:
See Production Time Hierarchy visual below:
It can be difficult to fully and confidently track each of the components used to calculate OEE. An alternative straightforward method for tracking that production resources are optimized, downtime is minimized and output is maximized may be implemented through the following measures:
Key Performance Indicators (KPIs) used for this method:
Time Utilization (%) – Measures the percentage of total hours effectively used for production:
Time Utilization=Run Hrs / Total Hrs ×100
Line Utilization (%) – Evaluates how efficiently available production hours are utilized:
Line Utilization=Run Hrs / Available Hrs ×100
See Alternative Time Hierarchy visual below:
Areté’s Production Scheduling functionality tracks critical production metrics used in the Alternative Method to drive smarter decision making.
Production lines often can't achieve peak efficiency soon after startup. Several factors influence this "warm-up" period:
Areté’s methodology for determining the amount of time for a production run of a required quantity includes several parameters that capture line warm-up time.
Perfect Production (100% OEE) and perfect Time and Line utilization requires:
While 100% OEE might seem theoretical at best, understanding the required metrics helps to identify improvement opportunities and set realistic targets for continuous improvement.
Measuring production performance is essential for identifying improvement opportunities and tracking progress. While OEE provides a comprehensive view of production efficiency, supporting metrics like planned downtime and maintenance costs offer additional insights for optimizing operations. By understanding and monitoring these metrics, manufacturers can make data-driven decisions to improve their operations continuously.
Remember: the goal isn't perfect scores across all metrics, but rather continuous improvement and balanced optimization of key interconnected measures.

JR has 2 decades of experience in Demand and Supply Planning helping customers achieve desired results.

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