SeizoMind Mas - Master Data Management System

The role of master data in DX

To successfully achieve digital transformation (DX) in the manufacturing business, it is critical to produce and manage high-quality master data using organizational data management. The proper management of master data enables faster and more effective gains in operational efficiency and data usage than previously.

BOM (Bill of Materials)

In the manufacturing industry, among the different types of master data, the Bill of Materials (BOM) is critical in controlling both production and the supply chain. A bill of materials (BOM), often known as a parts list, illustrates the hierarchical structure of the components that comprise a material. BOMs can be classified and maintained in four distinct categories: Engineering BOM (E-BOM), Manufacturing BOM (M-BOM), Purchasing BOM (P-BOM), Service BOM (S-BOM), etc. Each type of BOM comprises the information required for its particular area. For example, the M-BOM contains information about intermediate products that occur during the manufacturing process, as well as material information used in production.

BOP (Bill of Process)

The Bill of Process (BOP) offers information about the manufacturing processes for materials produced in a factory. Each process comprises information about the production process, work instructions, and the equipment needed for each stage. By integrating BOM (Bill of Materials) and BOP, you can describe the manufacturing processes for specific components. Combining different BOPs with the same BOM enables you to depict manufacturing methods that satisfy individual needs. Furthermore, by integrating BOP with work center data, you may describe the characteristics of manufacturing tasks done on the shop floor. Work center information is linked to resources such as equipment and personnel, allowing you to plan while accounting for differences in capacity and capabilities among work centers. By efficiently managing the mix of BOM, BOP, and work center information, you can centrally control different manufacturing processes for the same item, even if requirements or conditions change.

However, BOM and BOP data are quite complicated, and managing their numerous combinations in different versions is challenging. To fully realize the benefits of BOM and BOP, it is critical to solve the many difficulties around master data management.

Challenges in master data management

The key challenges in master data management are as follows:

• BOM duplications and variances are not consolidated.
• Searching for BOMs takes too long.
• Histories and snapshots are not maintained.
• BOMs are not consistent or integrated across systems and locations.

By tackling these challenges, companies can get closer to cost savings, inventory management, increased traceability, better data utilization, and global standardization.

Solution utilizing SeizoMind Mas

SeizoMind Mas is equipped with the features required to overcome each challenge. Companies who deploy SeizoMind Mas can address a variety of master data management concerns while also revolutionizing their production and supply chain processes.

BOM duplications and variances are not consolidated.

When registering a new BOM, it is required to determine whether an existing BOM is similar. If an identical BOM already exists, it should be used as is, and any changes in specifications should be registered as a variant. Properly constructed BOMs enable for more efficient progress in a variety of operations.

However, if duplicate BOMs or variations are not effectively claimed, the number of registered BOMs can significantly outnumber the actual number of components to be controlled. In sectors that produce a large number of new items or customized versions of current products, time for engineering is generally constrained. Under the strain of tight deadlines, engineers may proceed without thoroughly reviewing current BOMs. Registering a new BOM raises engineering costs unnecessarily, and it takes additional time to establish parameters for production, purchasing, and inventory management.

Based on all the data registered in the BOM, SeizoMind Mas's AI finds and recommends BOMs that already exist and closely resemble the necessary standards. You can increase the productivity of your engineering work by actively utilizing SeizoMind Mas from the outset and by keeping BOM structures in mind while you work. In addition, SeizoMind Mas can be used as a platform for concurrent engineering, enabling users to concurrently record design data together with manufacturing, purchasing, and inventory management data as they work.

Searching for BOMs takes too long.

It's critical to have fast search capabilities to locate required data quickly in order to use master data effectively. To look for master data based on IDs, names, attribute information, and other criteria, utilize keyword searches and filters. Searching is a crucial task for supply chain management and industrial management since it is regularly utilized to maintain operations.

Poor search performance has an adverse effect on a number of operations. Failing to properly search current BOMs during the creation of new items or orders can lead to avoidable extra expenses for design, manufacturing, purchasing, and inventory management. The master data for resources and equipment is no different. A basic search engine finds it difficult to manage synonyms, contextual variants, and variances in terminology, even when all recorded information is mirrored in the system. Furthermore, it is not enough to simply match keywords; consumers also need to be given relevant and useful information.

All information registered as master data is fully searchable thanks to SeizoMind Mas's indexing. In order to improve search results, it also extracts data from text files and attached images. It can efficiently infer semantically comparable words and circumstances by employing vector search, reliably obtaining pertinent material even in the absence of exact matches. When combined with SeizoMind Age, a specialized AI agent deciphers the data from the master data and gives users the information they need.

Histories and snapshots are not maintained.

Changes in design or production processes necessitate frequent updates to master data. Just the revised version of the data needs to be kept for data that hasn't been utilized in production yet. Manufacturing based on the outdated data and manufacturing based on the new data, however, might coexist when updating data for things that are already in production. Correct data operation through appropriate version control techniques is crucial to managing this complexity in production.

It could be difficult to obtain the required data and difficult to react appropriately to business needs if version control is not done correctly. If traceability is not guaranteed in after-sales services, responses to client requests or inquiries could not be appropriate. Moreover, the knowledge and insights collected in the master data may potentially vanish if crucial data is destroyed. Version control failure raises the possibility that modifications to the design won't be applied to the manufacturing process or other business operations. This might result in inconsistent practices between departments and a greater chance of problems with production and the supply chain.

For master data, SeizoMind Mas offers version control features. You can fully track and refer to all previous modifications with the help of the change history management function. The capability of multiple version management allows pre- and post-change data to coexist in a flexible way, facilitating the smooth implementation of specification and part updates. It is also feasible to run many versions concurrently in various factories or processes. You can address discrepancies in business information brought about by design modifications and take into consideration the integration of distinct version data with the version difference calculation and AI-driven difference analysis features.

BOMs are not consistent or integrated across systems and locations.

Multiple systems are frequently used to run plants and supply chain systems in the manufacturing industry. Additionally, particular aspects of these systems would need to cooperate across multiple locations in order to guarantee the efficient operation of the supply chain and manufacturing. The capacity to run and oversee numerous systems at various locations is a major source of competitive advantage for businesses with extensive supply chains and manufacturing operations.

Lack of standardization and integration of master data, such as BOM across systems and sites, is a frequent problem faced by businesses with multiple systems and locations. Although this might not be a challenge if every system worked completely independently, most systems and places are linked. It is challenging to track data across the supply chain, from upstream to downstream, or vice versa, if master data is not correctly linked. Additionally, businesses frequently have to pay for the modification of master data to match the format required at the new site when they relocate a product's manufacturing. This may also increase the chance of production stops brought on by inaccuracies or shortcomings in the manufacturing process modifications.

SeizoMind Mas facilitates the unified control of master data across all locations by allowing for the centralized management of global manufacturing plants. It has capabilities that make it easier to migrate production processes and integrate data between manufacturing sites, enabling seamless adjustments to manufacturing operations around the world. Interfaces for MES and ERP systems make it simple to accomplish smooth data integration across international systems.

Toward the Success of DX in Manufacturing and Supply Chain

The most essential function in manufacturing management is master data management, which is why most businesses should start with this area to ensure a successful digital transformation (DX) in manufacturing management. Businesses can only effectively drive the efficiency and optimization of other operations by optimizing master data. SeizoMind Mas is the best option for businesses starting their DX journey or wishing to intensify their ongoing DX operations because it has all of the high-performance capabilities required for manufacturing management DX.

As introduced in this article, implementing SeizoMind Mas can lead to the following benefits:

• Reduction in engineering cost.
• Reduction in parameter configuration costs for manufacturing, purchasing, and inventory management.
• Enhanced efficiency in BOM search and retrieval, leveraging AI to quickly identify relationships with existing data.
• The ability to detect patterns that traditional systems could not.
• Promoting data utilization.
• Improved data traceability.
• Enabling the management of complex manufacturing patterns.
• Adaptation to frequent design and process changes.
• Greater integration and standardization of master data across systems and locations.

If you are experiencing difficulties with master data management or related operations, we advise you to consider our SeizoMind-based solutions. For more extensive information, pricing, or casual consultations, please use the contact form on our website.

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