Episode 1 - Master data in the area of standard and purchased parts

Master data in the area of standard and purchased parts

In a production environment, Master Data Management (MDM) can be used to ensure that master data about standard parts and purchased parts is consistent and up-to-date. This may include managing information such as part numbers, descriptions, prices, manufacturers, suppliers, stock levels, and technical data.

1.? Description: A unique description ?for the part that distinguishes it from other similar parts.

2.??Manufacturer and part number: A unique number assigned to the part by its manufacturer or supplier.

3.??Norm & Standard descriptions: A unique description of the Norm & Standards assigned by the standards organization.

4.???Specifications 1: Technical characteristics of the part, such as power, voltage, amperage, pressure, etc.

5.???Specifications 2: Nature of the part: length, width, height, outer & inner diameter, coating, material, etc.

6.???Supplier Information: Information about the supplier or manufacturer of the part, such as name, address, contact details.

7.???Warehouse and management data: data necessary for the storage and management of the part, such as storage location, minimum and maximum stock, expiry date, etc.

8.???Price, terms of delivery and payment

Managing this data in a central location can ensure that it is accurate and up-to-date across all business applications and departments, and that tracking parts is not a problem.

MDM for standard and purchased parts can also help prevent duplicates and improve data quality. Better data quality can help increase the efficiency of business processes, support decision-making, and reduce costs.

Master data vs. movement data

Master data and movement data are both types of data in the field of enterprise information systems.

Master data refers to the static data that describes the properties of an object, such as the information about a customer, a product, or an employee. This data remains unchanged over time and is used as a reference for transactions and movements.

Movement data, on the other hand, refers to data that reflects changes over time, such as transactions, sales, or movements of goods. This data provides a record of the changes made and is used to update the master data.

Both types of data are essential for running a business and providing accurate information to make decisions.

Industry 4.0 and master data

Industry 4.0 and the management of master data for standard and purchased parts are closely related, as both are aimed at improving efficiency, quality and flexibility in production processes.

Industry 4.0 enables the use of advanced technologies such as Internet of Things (IoT), Artificial Intelligence (Kl) and Big Data to collect, analyze and use the data in production processes. This makes it possible to automatically control and adjust processes to improve productivity and quality. In order to control all these processes automatically, the master data must be of high quality and up-to-date.

With regard to the management of master data for standard and purchased parts, Industry 4.0 enables the use of technologies such as MDM (Master Data Management) systems and automated data validation (only works if the master data has been created correctly and completely) to simplify data management. It also allows automation of data ingestion and management to increase efficiency. Tools can help here, such as an intelligent ticket system, which guarantees the highest quality through naming catalogs, standards and manufacturer links while creation.

Industry 4.0 also enables the use of digital twins and digital threads, which make it possible to track and manage the lifecycle data of standard and purchased parts. This makes it possible to improve data quality and traceability and to support decision-making.

Overall, the application of Industry 4.0 technologies makes it possible to improve the efficiency, quality and flexibility in the management of master data for standard and purchased parts and makes it possible to optimally design production processes.

Best wishes

Sascha Hartung