Integrating Remanufacturing into PLM for Discrete Manufacturing
This blog post explores the role of remanufacturing and outlines how it can be successfully integrated into Product Lifecycle Management.
In our modern data-driven economy, organizations require flexible processes to be competitive. This flexibility only comes through deep insights of how things work and where the key challenges are. Tapping into these insights for your organization starts with shaping a plan.
By now, several companies recognize that they have opportunities to use process mining to enhance process efficiency, improve decision making, and gain competitive advantage. But implementing a process mining initiative is complex. You need to set a right goal, ensure that the infrastructure requirements are met, such as tools, systems and data sets, and tackle the intrinsic challenges, such as securing commitment, reinventing processes and changing organizational behavior.
One of the fundamental issues in the mining initiatives is that business processes do not produce data of appropriate quality to mine. This can be caused by missing data as well as poor data quality in event logs, problems with timestamps, event granularity, ambiguity of activity names, and some parts of a process that need to be modeled may not produce data at all. Every company today produces a massive amount of data, every day and in every business segment. Voluminous data needs to be handled in business areas such as sales, procurement, finance, etc. Furthermore, from our experiences, we have identified three core challenges that companies face when launching process mining initiatives.
Before organizations can tackle these challenges, they need to clarify fundamental questions: How to differentiate the necessary data from irrelevant data and how to provide the technical infrastructure for mining? For some companies, the starting point is to realize the accelerators such as data extraction and robotic process automation to speed up the preparatory phase of the process mining initiative.
Process mining represents a major opportunity for companies seeking to optimize processes, increase efficiency, and gain relevant insights. To capture it, they need to make a rapid shift from traditional approaches to data-driven automated models. Successful companies are embracing this shift as a priority in different industries. To master it, they are systematically investing in expertise and capabilities.
Camelot supports clients in their journey of identifying the overall purpose of process mining, to strategize and plan, implement the initiatives, and measure the outcomes.
We would like to thank Thilo Pufahl for his valuable contribution to this article.
This blog post explores the role of remanufacturing and outlines how it can be successfully integrated into Product Lifecycle Management.
No-Code technologies allow businesses to adapt their transport management strategies swiftly and flexibly without complex programming.
In this blog post, you will learn the important difference between CX software solutions and customer experience as a business orientation.
The importance of effective reference data management. We show how companies can significantly increase the quality of their business processes by optimizing their reference data.