By Jay Fisher, Senior Systems Engineer

Data is constantly the talk of the town. Manufacturers have the ability to collect data on almost anything. So the question becomes, what data should you collect? We identified eight key performance indicators (KPIs) that manufacturers should track and why.


Downtime is a period when the line or operation is down or not producing any products. When production doesn’t take place, money doesn’t come in.

Downtime falls into two categories: scheduled and unscheduled. Scheduled downtime is planned and includes breaks, lunch, shift change and meetings. Unscheduled downtime varies depending on the process but includes events like out-of-stock, equipment malfunction, and operator error.

When manufacturers analyze unscheduled downtime data, they glean valuable information, including:

  • Causes
  • Trends
  • Process issues
  • Bottlenecks
  • Equipment issues

Knowing this information enables manufacturers to improve processes, increase profitability, and calculate overall equipment effectiveness (OEE). (Continue reading to learn about why you should track OEE.) After implementing an enterprise-wide MES, some our clients decreased downtime by upwards of 20%.


If downtime tracks the time that a line is down, uptime tracks the opposite: the time that a production line or process makes money for the business. Manufacturers asses this process or production-performance KPI individually or together with the downtime KPI. Uptime is also a required KPI to calculate the OEE KPI.

Manufacturers calculate uptime as a percentage of production run-time divided by available production time:

Uptime = Run-Time (Production) ÷ Total Available Time

Production Run-Time = Total Available Time to Run – Scheduled and Unscheduled Downtime

Uptime identifies increases in production stoppages, product changeover times, and maintenance issues such as plant breakdowns. Factors such as time of downtime, effected operations, and downtime length contribute to capturing down and uptime, which go hand-in-hand. Understanding of these KPIs provides a basis for resolving issues and a mechanism for tracking the results.

Production Target

Production target is a simple and common production-process KPI. The production target is the amount of production (in terms of units) the manufacturer expects to produce in a certain time period. Tracking production counts and target allows for visibility of production performance.

Production target KPIs fall into two categories. The first is “gross production” which includes total good and scrap units produced. The second is “saleable production” which includes only parts deemed as good and acceptable to ship to the customer.

Real-time visibility of this KPI shows line performance and gives manufacturers the ability to react to possible process or operation issues.

manufacturing production target

Defects On a Line

Defect tracking is an important KPI in the production environment. This metric indicates the number of defects during the production process, final inspection, or quality audit phase. You also need this KPI to calculate the first pass yield percentage and the defects per 1,000 or per 1,000,000.

Tracking defects on a line is valuable because it allows manufacturers to recognize trends related to the quality of a product and the operation of equipment. For example, if a line of car doors all have a scratch in the same spot, you can identify which machine is causing the defect. Many defect tracking solutions also display real-time data to prevent you from running a defective line for a whole week.

Defects Per Thousand Units or Per Million Units

A practical way to communicate the quality of products produced or served is through the quantity of defects per thousand or per million units.

This KPI is easy to interpret. It points to equipment or maintenance problems, production issues, and skills deficiencies. The amount compared to (thousand or million) depends on the industry and/or production levels. Most manufacturers have a target threshold they strive to stay below.

Here’s an example formula using defects per 1,000:

Defective units ÷ (total units per 1,000)

To calculate the value, take a sample of production and count the defective units that don’t meet the required standards. Here’s an example of this measure:

Units manufactured this month: 23,030

Defective units as per quality tool standards: 12

Defects per thousand units produced: 0.52

23,030 ÷ 1,000 = 23.03

12 ÷ 23.03= 0.52

First Time Through (FTT)

The first time through (FTT) or first time yield (FTY) KPI is a measure of production efficiency, ability/skill, and quality. It’s a percentage that places the number of units without defects or re-work, against the total units produced in a production process or value stream. The formula to calculate FTT is:

(Total Units Produced – Defective Units) ÷ Units Produced

first pass yield (FPY)

Units of production that are scrap, re-work, do not meet standards, require repair, or are not sellable fall under the definition of defective units.

The FTT will help you identify production efficiency and changes in performance in the production process. You can also use it as an indicator to perform further analysis and improvements if it exhibits sudden big changes.

Cycle and Takt Time

Cycle time is the amount of time taken to complete an operation in a production process. Typically, each operation within a given production process collects this data. Cycle time opens insight into operation efficiency and bottlenecks.

Compare this to takt time. Takt time is how quickly you must create the product to satisfy the needs of the customer. When comparing the two, you can see where potential issues may lie because the deviation is outside of expected parameters. Using this data enables efficient line balancing/rebalancing and a uniform line.

cycle time

Overall Equipment Effectiveness (OEE)

OEE is a KPI that combines line availability, performance efficiency and quality of a specific line, equipment or process. Management commonly evaluates this KPI to compare performance among similar or identical machines, lines, or plants. OEE is a ratio usually expressed as a percentage.

Calculate OEE by multiplying the three factors: plant availability, performance efficiency, and FTT/quality.

overall equipment effectiveness (OEE)

Availability = Uptime/Planned Production Time

Run Time = Planned Production Time – Downtime

Performance = (Ideal Cycle Time × Total Count) ÷ Run Time

Ideal Cycle Time (Takt Time) = Ideal/expected cycle time that your process should achieve

Quality = Good Count ÷ Total Count

Total Count = Good + Defective + Scrap

Tracking OEE is beneficial because it allows local plant operations teams to assess their specific plant or process and analyze day-to-day, week-to-week, and month-to-month performance, to continuously identify and solve issues.

Data can be an incredibly useful tool – if you know what data to collect and how to use it. Contact us to learn more about what data you should track so you can improve productivity and profitability.