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6 Reasons to Use Process Mining in Manufacturing [2024]

Written by
Hazal Şimşek
Hazal Şimşek
Hazal Şimşek
Hazal is an industry analyst at AIMultiple, focusing on process mining and IT automation.

She has experience as a quantitative market researcher and data analyst in the fintech industry.

Hazal received her master's degree from the University of Carlos III of Madrid and her bachelor's degree from Bilkent University.
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Manufacturing companies can leverage process mining to collect and analyze process data based on the scanning and processing of products at different stations. Process mining can help manufacturers discover production paths, measure the performance of machinery, detect problems at any phase of production and understand the root causes of these problems. Yet, business leaders are not clear on applying process mining in manufacturing.

In this article, we cover 6 use cases of process mining in manufacturing. 

1. Measure and optimize machinery process performance 

Performance analysis, a process mining attribute, can be applied to measure the performance of the machinery used in production. Machine performance analysis provides insights on how long and how much each machine works. 

For example, in a process mining case study, Samsung Electro-Mechanics (SEM) Co leveraged process mining to understand the allocation of tasks and time they are active for each machine they utilize in their operations. They discovered that the factory had been using some devices more than others and longer.  

2. Understand and improve operations 

Manufacturing companies can deploy process mining to obtain insights about operation speed, throughput rates, and frequency of their processes, as process mining shows the workflow of a given process for a selected period. As a result, companies can identify deviations from target processes, inventory shortages, repeated production errors or bottlenecks in cross-departmental processes. With process mining, manufacturing firms can discover the root cause of these problems and eliminate them, which slows down the organization throughput. 

For instance, process mining analyzes the execution of a product processing that passes through various workstations with a target throughput rate and indicates the point throughput rate fell and the root cause of this problem. 

One example from an electronic manufacturer in the Netherlands shows that process mining detected an inefficiency prolonging the work at the subcontracting process. The company changed their initial step to avoid asking for more documents later, which reduced the wasteful activity by 85% and sped up the process. 

3. Plan production

Insights obtained from process mining can also be useful for production planning. Manufacturing companies can modify their plan by reallocating resources to generate processes that flow smoothly. In a global manufacturing company case study, process mining provided insights about:

  • The planning loops (e.g. planning material requirements and order processing) that occur twice or three times in production planning activities instead of once at the beginning of the planning.
  • The planning schedule instability (e.g. delays in performing tasks causing delays in order submission).
  • The effect of changes in the production plan on material management; materials were allocated to production units later than the preferred time, generating a longer lead time and, consequently, production release.

4. Resource management

Process mining allows manufacturers to understand their resources (e.g. financial, inventory, FTE, and production resources) and manage them efficiently as it can provide an overview of workflows and process flows.

For example, Veco, a micro-precision metal manufacturer from the Netherlands, mapped their process flows with process mining, which enabled them to reallocate their workstations. The company reduced delays, which decreased the lead time and number of people doing the same tasks.

5. Identify automation opportunities

Process mining enables companies to identify processes to automate and prioritize automation of some tasks over others by assessing their value and level of a tendency to human error. Manufacturing companies can primarily automate their invoice processes or bill of materials (BOM), a document with the list of all components relevant for processing and end product depending on the importance of these tasks.

For more, explore all automation use cases in manufacturing

6. Reduce operational costs 

Process mining provides information on activity costs in a process. Based on the insights, businesses can detect more costly activities than others and identify the reasons behind them. For example, if the activity includes any repetition or unnecessary task, companies can redesign their processes and lower their expenses. 

A case study, Vaisala, a Finnish company specializing in manufacturing and market products for industrial measurement, detected and corrected deviations in their operations, reducing operational costs while improving processes for each product with an average of around 59%.  

Also, predictive process mining enables businesses to predict the cost of remaining processes by analyzing historical and real-time data. Predictions allow companies to reduce expenses before the process is complete by changing the activities, causing higher expenditures.   

Further Reading

You can learn other process mining use cases in different sectors by reading our relevant articles:

If you believe your company can leverage process mining, you can check our data-driven list of software.

Check out our comprehensive and constantly updated process mining case studies list to learn more on process mining manufacturing real life examples.

And if you want us to find the right vendor for you:

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Hazal Şimşek
Hazal is an industry analyst at AIMultiple, focusing on process mining and IT automation. She has experience as a quantitative market researcher and data analyst in the fintech industry. Hazal received her master's degree from the University of Carlos III of Madrid and her bachelor's degree from Bilkent University.

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