3. The emergence of customized demand brings multiple challenges to the operational value chain of discrete manufacturing enterprises

Siemens Avendar believes that the management and operation status of enterprises can be analyzed and evaluated through three value chains, namely, the business performance value chain, the product management value chain and the asset operation value chain.
• The business performance value chain shows the process from order acquisition and product design to upstream and downstream collaborative production, delivery and use of finished products.
The product Management value chain covers the whole life cycle of the product, including product definition, product design, production and product portfolio management.
• Asset operation value chain shows the operation process of the enterprise at the asset side from the level of plant, production line and equipment, which covers production capacity planning, plant planning, production line design, engineering debugging, equipment parameter optimization, equipment maintenance and equipment upgrading.

The three value chains describe the whole process of enterprise operation management, constitute the three value chains of dTAT digital transformation wheel, and provide enterprises with an evaluation tool for comprehensive consideration of management operation level and digital level. (Detailed description of dTAT digital transformation wheel can be found in Siemens white paper “dTAT Digital Transformation Steering Guide”, “State Machine Piloting Digital Transformation Manual”)

Business compliance value chain

With the increasing demand for customization, discrete manufacturing enterprises are faced with great challenges in cost estimation, product design, BOM generation, supply chain management, production and after-sales service of business performance value chain.
• Order acquisition and management: Due to the diversity of customization requirements, changes in any dimension and any link may affect product costs. Therefore, customization makes it impossible for enterprises to quickly and accurately measure costs and thus make accurate quotations;
• Engineering design: customizing products to customer needs means that they may need to be redesigned for each order, resulting in lower efficiency and higher error rates in the design process;
•BOM generation process: customization leads to the increase of optional items, parts and other material data surge, put forward a greater challenge to BOM generation and transformation, prone to time-consuming, often wrong phenomenon;
• Supply chain management: Customized scenarios increase the variety and quantity of parts required, and the upstream and downstream collaboration of the supply chain faces greater challenges. At the same time, due to the customization needs of customers, some parts also need to be customized, and the delivery time of customized parts is difficult to guarantee. In addition, if the customer’s customized order is changed, the problem of slow response to the change and increased order cost will occur;
• Production links: In the face of the production characteristics of small-batch and multi-batch customization, the current factory has a low degree of flexibility, low line change efficiency in mixed line production, and difficult quality control in the mixed line production process;
• Product delivery and use: In the face of after-sales service problems, customized products make enterprises need to prepare more non-standard spare parts, resulting in an increase in inventory costs. If the spare parts are not prepared, they need to be customized again, which will prolong the delivery time and increase the cost.

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Product management value chain

In highly customized scenarios, discrete manufacturing enterprises face challenges in the product management value chain, such as the inability to accurately grasp user needs, the inapplicability of traditional product verification methods, and the increasing complexity of product portfolio management.
• Product definition: Due to the diversity of requirements in highly customized scenarios, enterprises cannot accurately and fully grasp the differentiated needs of users in the process of product definition;
• Product verification: Due to the variety of products, it is impossible to carry out all physical verification, resulting in the traditional product verification method (physical verification, that is, the production of samples, and then through various experimental verification) is no longer applicable;
Product upgrading and portfolio management: Under the trend of customization, the number of product types has increased geometrically, the complexity of product portfolio management has increased rapidly, and traditional management methods need to be reformed.

Asset operation value chain

The asset operation value chain shows the operation process of the enterprise in the asset side from the level of plant, production line and equipment. The customization trend puts forward higher requirements for the asset operation of the enterprise, mainly in the aspects of flexible production, production line debugging and verification, equipment parameter adjustment and so on.
• Production line design: In customized scenarios, discrete manufacturing enterprises have the characteristics of small-batch and multi-batch production, so in order to adapt to this feature, the production line design needs to fully consider the flexible production line change needs.
• Engineering commissioning: customization of high requirements for flexible production, making production line commissioning and verification more complex.
• Equipment parameter optimization: Due to customization and the substantial improvement of product types, the product parameters of each order are different, resulting in the optimal equipment operation parameters such as quality and energy consumption in the production process are also different, which puts higher requirements on the equipment setting. The original parameter optimization method based on expert experience is no longer applicable, and it is difficult to achieve the optimization of equipment parameters at the order level.