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Understanding your efficiency can be challenging without clear benchmarks and objectives. This is where Key Performance Indicators (KPIs) in manufacturing prove invaluable.

Table of Contents

What is a manufacturing KPI?

Manufacturing KPIs, or Key Performance Indicators, serve as metrics essential for gauging the efficiency of critical functions within a manufacturing enterprise. While all KPIs are metrics, not every metric qualifies as a KPI. The distinction lies in their purpose. Metrics encompass all measurable values, whereas KPIs are specifically linked to predetermined business objectives, making them pivotal indicators of success or failure. Tracking an excessive number of metrics without strategic relevance to your business is generally unproductive. However, aligning goals with selected metrics provides a reliable method to accurately assess progress and enhance targeted processes.

Selecting the right Manufacturing KPIs

The designation of KPIs as “Key” Performance Indicators underscores their significance. While any metric can be utilized to assess performance, KPIs are the ones deemed most crucial. What holds importance for companies can vary significantly based on their respective industries. Generally, it’s advisable for a company to limit its focus to no more than ten manufacturing KPIs to avoid unnecessary complexity. These selected metrics should cover various aspects of the business, such as manufacturing efficiency, customer satisfaction, lead times, and more. Determining KPIs is a unique process for each company, but each metric must meet specific criteria to ensure its utility in driving success.

An effective manufacturing KPI:

  1. Aligns with strategic objectives.

 Before choosing a KPI to monitor, it’s essential to define your desired outcomes. Once objectives are established, the KPI should serve as a tool to gauge progress towards those goals.

  1. Is quantifiable and measurable.

 Without clear measurement criteria, it’s impossible to track progress. Goals must be specific to ensure that KPIs provide tangible value to the business.

  1. Is achievable and actionable.

 Setting unrealistic goals is counterproductive, just as tracking superficial metrics that don’t accurately reflect the business’s status.

How to use Manufacturing KPIs?

Having effective manufacturing KPIs enables businesses to optimize production capacity, enhance productivity, elevate product quality, streamline delivery times, reduce waste, and manage costs efficiently.

It’s crucial to recognize that manufacturing KPIs can evolve over time. Certain metrics hold greater significance during specific phases of a company’s development, with priorities shifting as circumstances change. For instance, during the initial stages of a manufacturing operation, the focus may be on swiftly increasing production volumes and maintaining momentum. However, if there’s a surge in customer complaints later on, the emphasis may shift towards product quality and yield.

Regularly reviewing manufacturing KPIs is essential to ensure that efforts are directed where they’re most needed for improvement. Every KPI undergoes an iterative process aimed at achieving business goals, which includes:

Measuring the KPI.

  1. Breaking down the KPI into categories.
  2. Prioritizing categories based on the highest percentage of losses, possibly utilizing Pareto charts.
  3. Identifying the root cause of issues.
  4. Implementing countermeasures for problem-solving.
  5. Reassessing the KPI in an iterative manner.

I6. t’s worth noting that the terminology used to define each KPI may vary depending on the source and the specific context within an organization.

Infographic of business process key performance indicators.

Top 10 most important Manufacturing KPIs

While it’s important for manufacturers to monitor universal KPIs such as sales revenue and net profit margin, the nature of the production business necessitates tracking specific manufacturing KPIs. Here are several critical manufacturing KPIs to focus on:

Overall Equipment Effectiveness (OEE)

Overall Equipment Effectiveness (OEE) serves as a pivotal performance indicator, facilitating the monitoring and enhancement of machine or production line productivity within production centers. Calculating OEE entails various methods, one of which involves dissecting availability, performance, and quality. The formula for OEE is as follows:

OEE = Availability x Performance x Quality

Correct, the Overall Equipment Effectiveness (OEE) measures the percentage of time that a machine or production line produces good quality articles during the scheduled production time.

For Example

A machine is scheduled to run from 7:00 a.m. to 3:00 p.m. (8 hours) with a standard production rate of 120 units per hour. During this time, there was 45 minutes of downtime, and a total of 850 units were produced, out of which 800 were of adequate quality.

To determine the OEE, we’ll follow these steps:

Availability:

Planned production time = 8 hours

Downtime = 0.75 hours (45 minutes)

Actual production time = Planned production time – Downtime = 8 hours – 0.75 hours = 7.25 hours

Availability = (Actual production time / Planned production time) * 100%

Availability = (7.25 hours / 8 hours) * 100%

Availability = 90.63%

Performance:

Total units produced = 850 units

Ideal production rate = 120 units/hour

Ideal production for the actual production time = Ideal production rate * Actual production time

Ideal production for the actual production time = 120 units/hour * 7.25 hours = 870 units

Performance = (Total units produced / Ideal production for the actual production time) * 100%

Performance = (850 units / 870 units) * 100%

Performance = 97.70%

Quality:

Total units produced = 850 units

Units of adequate quality = 800 units

Quality = (Units of adequate quality / Total units produced) * 100%

Quality = (800 units / 850 units) * 100%

Quality = 94.12%

Now, let’s calculate the Overall Equipment Effectiveness (OEE):

OEE = Availability (%) * Performance (%) * Quality (%)

OEE = 90.63% * 97.70% * 94.12%

OEE = 84.83%

 

So, the Overall Equipment Effectiveness (OEE) for this example is approximately 84.83%.

Overall Equipment Effectiveness (OEE) is a metric that measures the value-added time and identifies losses within the production process. These losses are activities that do not contribute to the value of the final product. There are various categories used to classify these losses, including:

Machine breakdown:

 Downtime is caused by mechanical failures or malfunctions.

Contingencies:

 Unplanned interruptions or delays, such as power outages or material shortages.

Setup time:

 Time required to prepare the machine or production line for a new task or product.

Shortstops:

 Brief interruptions in production due to minor issues or adjustments.

Speed loss:

 Decrease in production speed below the optimal rate, often due to equipment limitations or inefficiencies.

Scrap or quality defect:

 Production of defective or non-conforming units that must be discarded or reworked.

Work-in-process (WIP)

Work-in-process (WIP) serves as a critical performance metric that evaluates the value of raw materials or subassemblies within the manufacturing process before reaching the finished product stage. It can be categorized into two main groups: items waiting to be processed and those currently undergoing processing.

The formula for calculating WIP is as follows:

WIP = Manufacturing Lead Time × Production Flow Value

Let’s consider a different work center that takes 6 hours to complete a batch. The production flow rate is on average 80 kg/h, and the cost per kilogram is $1.50.

Using the formula:

WIP = Manufacturing Lead Time × Production Flow Value

WIP = 6 hours × (80 kg/h × $1.50/kg)

WIP = 6 hours × $120/hour

WIP = $720

This means that there is $720 worth of material in that work center. Whether it’s being processed or waiting to be used, this represents the value of materials within that stage of production.

The level of work-in-process inventory is influenced by factors such as manufacturing lead time, manufacturing costs, the number of orders in progress, and batch sizes. Further analysis by the operational team will be necessary to identify potential areas for performance improvement.

Potential improvements may include:

  1. Decreasing manufacturing costs
  2. Shortening manufacturing lead times
  3. Optimizing batch sizes
  4. Enhancing labor efficiency
  5. Maximizing space utilization on the shop floor
  6. Streamlining transitions between work centers

Lead Time (LT)

Lead time, also known as order cycle time, stands as a pivotal KPI for businesses involved in manufacturing and product sales. It offers insights into your company’s order processing efficiency and the promptness with which customer demands are met. Lead time encompasses the duration required to fulfill an order from confirmation to complete delivery.

Extended lead times may signify inefficiencies within your business processes, leading to bottlenecks and increased costs. Conversely, shorter lead times are preferred as they indicate smoother processes and swift responsiveness to customer needs. The overall lead time can be deconstructed into several components:

Production lead time:

 The duration from commencement to the completion of product manufacturing.

Delivery lead time:

 The time taken to deliver a product to the customer from available stock.

Material lead time:

 The period required for suppliers to deliver goods to the manufacturer.

By dissecting lead time into its constituent parts, businesses can pinpoint inefficiencies more accurately within their processes.

On-time-in-full (OTIF)

The On Time In Full (OTIF) serves as a crucial performance metric that assesses the proportion of orders delivered to customers with the correct quantity and quality, meeting the specified deadline. It is calculated by comparing the number of orders meeting these criteria to the total number of orders placed.

The OTIF has the following formula:

OTIF = Number of perfect orders / Total number of orders

 Let’s consider an organization with 100 orders scheduled for delivery on a particular day. However, there are discrepancies in some of the orders:

4 orders did not meet the required quantity specified by the customer.

3 orders exceeded the quantity required by the customer.

2 orders contained defective products.

1 order arrived late.

To calculate the On Time In Full (OTIF) for that day:

OTIF = [100 – (4 + 3 + 2 + 1)] / 100 orders

OTIF = (100 – 10) / 100

OTIF = 90 / 100

OTIF = 0.9 or 90%

On Time In Full (OTIF) serves as a stringent KPI measuring the service level of an organization, encompassing various functions such as commercial, logistics, production, and purchasing. It’s essential for each organization to establish tolerances regarding product defects, order quantities, and delivery punctuality.

By analyzing the losses, the breakdown can help identify:

  1. Delays within the supply chain.
  2. Product defects.
  3. Shipments with quantities differing from the sales order.

Cost per Unit (CPU)

Cost per Unit (CPU) serves as a significant key performance indicator (KPI) aiding manufacturing systems in optimizing product costs. It plays a vital role in enabling companies to offer competitive prices in the market while simultaneously boosting profitability. The formula for CPU is as follows:

CPU = (Direct Material Costs + Direct Labor Costs + Manufacturing Overhead) / Total units produced

Let’s consider an organization that manufactures 1000 units of a product with the following cost breakdown:

  1. Direct Material: $3000
  2. Direct Labor: $2000
  3. Manufacturing Overhead (MOH): $1000

To calculate the Cost per Unit (CPU):

CPU = (Direct Material + Direct Labor + Manufacturing Overhead) / Number of Units

CPU = ($3000 + $2000 + $1000) / 1000 units

CPU = $6000 / 1000 units

CPU = $6 per unit

Different methodologies exist to allocate Manufacturing Overhead when a company produces a mix of products. These methodologies may include standard cost, direct cost, activity-based cost, etc. It is crucial to define the correct allocation methodology as it helps determine the profitability of a product and establish pricing by adding a markup to the total product cost.

Yield or First Time Through

The first-time yield (FTY) or first time through (FTT) key performance indicator measures production efficiency and quality. FTT, or Yield, reflects the number of units produced without defects or additional improvements against the total number of produced items.

The formula to calculate this metric is simple:

FTT = (Total Items Produced – Defective Items) / Items Produced

Let’s consider a scenario where an organization manufactures 300 units of a product, but 8 of these units are found to be defective.

To calculate the First Time Yield (FTY):

FTY = (Total units – Defective units) / Total units

FTY = (300 – 8) / 300

FTY = 292 / 300

FTY = 0.9733 or 97.33%

In this case, the First Time Yield (FTY) is approximately 97.33%.

It’s important to note that any units failing to meet the quality standards after the production process are classified as defective items. FTY tends to be higher when the production process isn’t fully optimized or when it’s performed manually.

Production Downtime

Production downtime is a period when the manufacturing process is on hold and no products are produced. Terms such as idle time, downtime, or off-line period usually relate to the same KPI. Usually, this manufacturing KPI shows a ratio of downtime to operating time and is directly related to the availability of assets for production.

Downtime is a critical metric since if for some reason no goods are being produced, a loss will be incurred. There might be various reasons why the whole production is at a stop, beginning with human factors or mistakes, and ending with broken equipment. It is also a good practice to record the reasons for downtime and try to reduce them in the future.

Inventory Turnover Ratio

Excessive inventory usage ties up valuable resources, contrary to the primary objective of manufacturing, which is to utilize space for production rather than storage. A higher inventory turnover rate signifies a more efficient supply chain.

The formula for calculating the inventory turnover ratio is:

Inventory Turnover Ratio = Cost of Goods Sold (COGS) / Average Inventory

Target turnover ratios vary depending on manufacturer-specific requirements. However, generally, a turnover period exceeding 30 days could be deemed prolonged. An excessively high inventory turnover may indicate insufficient inventory levels, leading to missed business opportunities. Conversely, a low ratio may suggest either sluggish sales or overstocking, both of which can impact profitability.

Low sales result in stagnant inventory that generates no revenue, while overstocking ties up funds that could be utilized elsewhere in the business.

Production Schedule Attainment

This manufacturing KPI measures the effectiveness of production planning and the efficiency of production workers in achieving their targets.

In manufacturing, planning is crucial, especially in complex processes where executing plans becomes more challenging yet essential. Creating accurate production schedules to meet output targets as per the plan is vital for meeting customer expectations and aligning with corporate strategy.

The calculation for this manufacturing KPI is as follows:

Production Schedule Attainment = (Actual Output / Planned Output) x 100

For example,

when a company plans to produce 4000 units in a month, but actually produces 3500, the

PSA is:PSA = (3500 / 4000) x 100 = 87.5%

By using this KPI, you can set performance benchmarks, improve MO completion time estimates, and increase delivery accuracy.

Supplier OTIF

In manufacturing, the quality of suppliers significantly impacts operations. Dependable partners are integral to the success of your company, underscoring the importance of monitoring KPIs related to supplier performance. One comprehensive method is to assess the On-Time-In-Full (OTIF) performance of suppliers.

OTIF = Number of perfect orders / Total number of orders

 For example, let us say that your supplier has made 28.

deliveries, of which:

1 had defective goods.

3 were late.

3 had fewer quantities than ordered.

Then the OTIF rate for the supplier is:

OTIF = (28 – 1 – 3 – 3) / 28 = 0.75 = 75%

Key Take Aways

  • While all metrics are measurable, not all metrics are elevated to the status of KPIs.
  • KPIs stand out due to their critical role in assessing the achievement of business objectives.
  • Aligning business goals with metrics is essential for progress tracking and process enhancement.
  • Effective KPIs should align with strategic goals, be quantifiable, measurable, achievable, and actionable.
  • It’s advisable for companies to focus on a limited number of KPIs, ideally around ten, covering various aspects of the business.
  • Well-defined KPIs empower businesses to enhance operations across all facets.
  • Regular review and adjustment of KPIs are necessary to align with evolving goals and objectives.

 

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