Developing a proof-of-concept solution to reliably forecast turnaround times

A common problem in steel-product manufacturing is the significantly high throughput time of steel products in comparison to the sum of their process times. Manufacturers have similar production methods which, upon investigation, are likely to yield improved time efficiency resulting in a higher relative touch time per product. To lower production times, it would be optimal to introduce production planning with higher levels of dynamicity, granularity and detail.

KORT is a project working towards developing a proof-of-concept solution that can reliably forecast turnaround times. This is achieved by influencing the waiting time of products through detailed production planning. The focus of this project will lie in determining the factors that influence throughput time and identifying opportunities to manipulate them. It will help to recognise and categorise the similarities our industry partners possess, based upon their physical and digital infrastructure.

This will form the backbone of a decision model which will steer the planning process more accurately. Historical and real-time ERP data is used to develop a modular framework that supports detailed and flexible production planning, resulting in a new, robust planning and control solution. We can then use this demonstrator as a new industry standard, or an object lesson to guide steel-product manufacturers when adjusting and/or improving their production planning.

Industry partners

APPROACH

To address the correct challenges it was important to analyse and understand the problem statement by exploring underlying root causes. Although the challenge was similar for each company, it was also important to understand the differences; be it resources, infrastructure (digital or physical), process steps and/or capabilities.

We formed a fifth, symbolic company representing the usecase. Based on this use-case and previous analyses, throughput influencing factors were identified. Solutions were explored and proofs-of-concept for throughput time reduction were developed.

We generated a solution to reliably forecast turnaround by influencing waiting time of products through detailed production planning, including manipulation of buffer times. This will contribute to more detailed control, more foresight, and ability to action preventively on the production planning to allow for smarter adjustments and optimise production parameters, including smart prioritisation.

OUTCOME

The project resulted in a data-based user interface to find the optimal in-process buffer time in relation to in-production or touch time. This can then be used to optimise throughput times without loosing confidence in the planning. The algorithm used can be developed further and tailored to the unique production environment of the participating companies, to reliably forecast and decrease turnaround times at sheet metal production facilities, without directly changing the production processes or resources. Further benefits included better prediction of end dates, more agile production processes, and increased planning control. Overall, this project provided the companies with a step towards a smarter factory development with optimised efficiency within the production line.

The project resulted in a proof-of-concept that included:

A current-state assessment of all relevant production processes and infrastructure per company.
A modular framework for detailed production planning.
A control algorithm and architecture for smart prioritisation.
A knowledge transfer program to support company employees.
A digital demonstrator of the developed framework in context.

“It was a pleasure to work with Fraunhofer Innovation Platform at the University of Twente. They know how to switch between practice and science and to take you along with them in an enthusiastic way.”

– Arnold Hofmeijer
Managing Director, GS Metaal B.V.

For more information on KORT, feel free to reach out to

Maaike Slot

Research Engineer

Cheng Guo

Research Engineer

Hari Subramani Palanisamy

Research Engineer

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