1. The following are the most valuable types of metrics for managing manufacturing operations today:
- Financial metrics that are based on real-time data monitoring from the shop floor
- Customer responsiveness and satisfaction metrics
- Supplier and product quality metrics
- Efficiency-based metrics
- New Product Development & Introduction (NPDI) time-to-market performance
2. Operations teams are also designing their smart factory IT and Operations Technology (OT) systems to capture real-time data when possible on the following types of metrics:
- Asset and maintenance metrics including preventative metrics
- Inventory management, turns, and velocity
- Compliance metrics
3. The following are the valuable metrics to manufacturers as they plan, pilot, and launch smart factories.
CARRYING COST OF INVENTORY
1. Combines the most challenging costs to capture for managing inventory, including put-away labor and storage costs, costs of obsolescence, and how effective warehouse management is at reducing logistics and fulfillment costs.
2. Carrying cost of inventory is a must-have because it’s invaluable in tracking how much working capital is being allocated to inventory as well.
GROSS CONTRIBUTION MARGINS BY PRODUCT, PRODUCTION FACILITY, AND BUSINESS UNIT
1. An essential metric for measuring the financial outcomes of manufacturing decisions.
2. Tracks Gross Contribution Margin (GCM) performance levels by product, region, and production center or factory.
INVENTORY TURNOVER
1. Defines how many times a given plant’s inventory is consumed to build salable products and replenished in a specific period.
2. Inventory Turns are most often calculated using the Sales by Average Inventory factoring for specific accounting periods.
3. The second approach is to divide Cost of Good Sold (COGS) by the average inventory level for a specific accounting period.
ORDER CYCLE TIME
1. Defined as the total elapsed time it takes from when a customer places an order to when they receive it.
2. Order Cycle Time is an excellent metric for determining how collaboratively the entire production team is working.
3. Smart factory pilots using this metric are attempting to quantify the contribution of inventory management, supply chain, manufacturing, and fulfillment performance levels.
DIGITAL MATURITY INDEX
1. The main reason for implementing Industry 4.0 technologies is to drive digital transformation across different business verticals, especially manufacturing units.
2. The digital maturity index (DMI) is a method of measuring the digital performance of an organization across the most relevant parameters.
3. DMI outlines an organization’s digital capabilities and their maturity levels to provide an effective roadmap for successful digital transformation.
PO CYCLE TIME
1. Purchase order cycle time is the time required to prepare and dispatch a purchase order to its respective supplier or customer.
2. For a manufacturing company, the PO cycle time should be as low as possible.
3. As this time depreciates, it’s a clear indication that your software performance is improving after Industry 4.0 implementation.
4. It means you can easily increase production capacity that would help you expand your business to new horizons.
FILL RATE
1. Fill rate is defined as the percentage of orders that were successfully delivered to the customers in good condition i.e the number of completed orders.
2. If this percentage is high, you’re on the right track and it’s also an indication that the newly installed systems are performing well.
3. On the contrary, if the percentage is low, it suggests that there are loopholes in your existing order fulfillment system.
4. You can also use fill rate as a KPI to measure the performance of your enterprise systems post the Industry 4.0 implementation.
ORDER PICK, PACK AND SHIP ACCURACY
1. An essential metric for measuring how effectively the main functions of an inventory management system are performing and how well integrated they are to fulfillment systems.
2. By definition, pick, pack & ship is the logistics process of locating inventory and packing items for shipment to customers.
PERFECT ORDER PERFORMANCE
1. Measures how effective a production facility is in delivering accurate, damage-free orders to customers on or before their delivery due date.
2. It’s often defined as the (Percent of orders delivered on time) * (Percent of orders complete) * (Percent of orders damage free) * (Percent of orders with accurate documentation) * 100.
SCRAP MATERIAL RATE
1. Effective scrap management is imperative to efficiently run manufacturing and supply chain operations.
2. Although waste generation is inevitable, by enabling automation across your manufacturing units, you can significantly mitigate its quantity.
3. At the same time, smart manufacturing tools provide effective scrap handling capabilities, enabling organizations to dispose of their biodegradable waste and recycle non-biodegradables.
4. Scrap material rate is a crucial business KPI that enables organizations to measure the extent of their waste generation. At the same time, it can measure the scrap management efforts of an enterprise after Industry 4.0 implementation.
FORECAST ACCURACY
1. Analyzing the forecast accuracy of your Industry 4.0-compliant enterprise systems is a simple and straightforward way to measure its performance changes.
2. Due to the implementation of machine learning algorithms, the accuracy of these systems increases with time. As more data is fed to these systems, their accuracy increases gradually.
3. As a result, enterprises can enhance their production capacity and align their operations with towards efficient workflows through intelligent decision making.
4. Therefore, if the forecast accuracy of your enterprise systems is improving, it’s a clear indication of Industry 4.0 doing its job.
DEMAND FORECAST ACCURACY
1. A must-have metric to determine if the supply chain planning, procurement, production scheduling, and fulfillment systems are synchronized with each other.
2. Demand Forecast Accuracy also indicates the variation in real or actual demand and what is forecasted at the factory level.
SUPPLIER QUALITY INDEX
1. A useful metric for determining how integrated inventory management, quality, and compliance systems are and how effectively they can isolate supplier quality problems before they impact production.
2. In regulated industries, it’s required to track supplier quality and compliance, often to the lot and vendor level.
3. Medical products manufacturers need to provide this level of visibility to comply with the U.S. Food and Drug Administration mandate, 21 CFR Part 11.
SUMMARY
1. There are many other similar metrics that you can use to measure your business performance post the Industry 4.0 implementation. The most basic ones are energy consumption, overhead costs, capacity utilization, error resolution time, and supplier lead time.
2. Besides, hardware and software maintenance plays a critical role in improving the performance of your enterprise systems that ensures speedy recovery of the capital investments.
3. Analytics is the cornerstone that keeps smart factories focused on customers and their changing needs. Their greatest potential, however, is in providing production teams with a sense of purpose and meaning to continually keep striving to improve manufacturing process performance, product quality, and customer satisfaction.
Source:
https://erpsolutions.oodles.io/blog/performance-metrics-industry-4/
https://blog.flexis.com/5-key-metrics-industry-4.0
https://www.forbes.com/sites/louiscolumbus/2019/11/20/the-10-most-valuable-metrics-in-smart-manufacturing/?sh=7f163932e054
