Automate your sequencing with AI

Global trends such as mass customization are leading to high product diversity and increasing demands on delivery times and flexibility. To ensure that everything runs smoothly and as efficiently as possible, the sequence of orders must be planned precisely before production. Manual planning reaches its limits in this respect. AI-supported sequence planning provides a remedy.

Sequencing determines the production order of individual jobs with the aim of making the production process lean, time-saving and thus efficient. If your sequence planning of orders still functions manually, for example using spreadsheets or analog planning boards, and not automatically. Then factors such as processing, setup and delivery times, product specifications, materials or the reduction of effort must be taken into account individually. In implementation, this is very tedious: orders and sequences of machines usually cannot simply be shifted without having to manually adjust the rest of the planning.

The goal is therefore to optimize sequence planning with the help of Artificial Intelligence. For this purpose, a wide variety of data, for example ERP data and real-time data from production, can be evaluated to derive indications for optimal machine assignment and to use these findings for sequence planning.

A Decision Support System can help

A computerized decision support system can help analyze and prepare business data so that users can more easily make business decisions with the program. A Decision Support System derives information from data. Such systems can filter, interpret and evaluate the available data. The results of a Decision Support System can also be calculated by Artificial Intelligence.

How your company benefits from automated planning

Automated sequence planning by AI supports the decisions of production planners by generating reproducible and reliable plans that take all framework conditions into account. This optimizes the performance of the production system and at the same time saves time and costs for planning efforts. However, a high level of effort is required to implement such automated planning. After all, expert knowledge of the current processes must be acquired, a database must be created and the necessary know-how in the field of data science must be generated for the implementation.

The company Westaflex, for example, is implementing AI-supported production planning in the AI Marketplace. Until now, sequence planning in manufacturing has been done manually. With the AI Marketplace team, Westaflex is researching and developing an AI application for optimized sequence planning using product and production data. This is intended to optimize the useful output and thus increase value creation by saving time in production. In the process, Westaflex is also receiving support from ISTOS GmbH, an associated partner in the project, as part of the AI Marketplace. ISTOS GmbH, a subsidiary of DMG Mori, develops digital applications for the medium-sized manufacturing industry which are intended to network production steps across machines.


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