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Smart Manufacturing Discussion


Smart Manufacturing Planning


Based on the experience of more than 200 Smart Manufacturing projects of planners and the evaluation of enterprise maturity, it plans the operation mode of enterprises that can carry out Smart Manufacturing.

The specific steps are to obtain the investigation form of the current situation of Smart Manufacturing by submitting the enterprise information, and pass the preliminary planning scheme after the review of the contents of the investigation form by experts; Further plans are obtained through online meetings and on-site research.

Smart Manufacturing planning focuses on the following areas:

  1. Overall planning and specific implementation steps of Smart Manufacturing

  2. Smart Manufacturing system architecture

  3. Intelligent factory design and planning (model and logic to avoid ignoring Intelligent Systems)

  4. Data structure and big data processing necessary for industrial data acquisition

  5. Technical composition and application of data modeling and digital twinning

  6. Industrial applications of digital virtual simulation, virtual reality and augmented reality technology

  7. A new generation of artificial intelligence applied in manufacturing industry

Smart Manufacturing Core Technology Consulting


Engineering experts have drawn a lot of diagrams, hoping that the IT industry can complete them! However, the IT industry is difficult to deal with a large number of Engineering logic. Each line of source program corresponds to engineering logic. The IT industry can't do it! "Who will do it"? This may be the reason why it is difficult for Smart Manufacturing industry to take off!


Our solution to "how to do" is engineering modeling + Machine Learning + intelligent system architecture development (a large number of scenario use cases), etc.


Firstly, engineering modeling involves many fields such as process, product, equipment and automation, which is difficult; The established model should be fully bound with the production line for machine learning! Therefore, we should not only have profound engineering technology, but also have a considerable computer background. In particular, the third point is that the architecture and development of intelligent systems involve large-scale software. It is really difficult for people who understand engineering to deal with such a large-scale software system. For the architecture and development of intelligent system, in addition to having the normal architecture and development of software system, it is also necessary to collect and develop all the scene use cases completely. For example, when there are 100 engineers on the production site, the work done by these 100 people should be sorted out completely, written into the software system and called the model to solve it, and the corresponding model should be developed in advance. This difficulty is beyond the competence of most enterprises. Although there are some enterprises developing common platforms, they involve individual applications in different production lines and industries. Therefore, these enterprises can't help. Large manufacturing enterprises, such as Siemens and GE, still focus on developing common platforms that can be sold in large quantities. Customized applications are not their advantages in terms of cost or technology!


The more than 200 cases we have completed in various countries are mainly customized development of this kind. This is also our most important area of planning, consulting and development!


Technical and business consulting involves many aspects of the team's business, See: Technical and business consulting field.

Smart Manufacturing implementation

Smart Manufacturing implementation scheme

  • Smart Manufacturing planning preparation

  • Smart Manufacturing outline planning

  • Smart Manufacturing detailed design

  • Implementation analysis of Smart Manufacturing

  • Design of Smart Manufacturing information physical system

Smart Manufacturing implementation field

  1. Smart mold Ecology: provide mold customization, cloud design, cloud simulation, Smart Manufacturing asset management, whole life cycle management and other one-stop solutions for mold manufacturing enterprises to meet the needs of mold manufacturing enterprises and enterprises, and help the mold industry realize digital, networked and intelligent transformation

  2. Smart chemical ecology: provide integrated platform solutions for the chemical industry; Provide intelligent solutions such as production management, production optimization, park management and control, and industrial collaboration for the three major users of the government, the park and enterprises, etc.

  3. Smart procurement enabling module: accurate, efficient and risk-free professional procurement services. Through platform connection, the resource party and the purchaser provide online solutions such as accurate sourcing, procurement financing and bill discount, and offline solutions such as cost optimization, quality assurance and warehousing logistics to help enterprises solve problems such as cost, efficiency and capital

  4. Smart supply chain enabling module: it is committed to using Internet of things, big data, blockchain, identity analysis, SaaS, AI and other technologies to provide enterprises, industrial clusters, governments and other relevant customers with supply chain intelligent SaaS platform solutions with the capabilities of five modules, including traceability management, network optimization, supply optimization, demand optimization and inventory optimization, Build a smart supply chain ecosystem, empower all excellent stakeholders on the platform, realize value-added sharing and create win-win results

  5. Smart Energy Ecology: Based on energy demand, help enterprises realize carbon neutralization, provide enterprises with scenario solutions such as power trading, power trusteeship, energy storage, gas triple supply, compressed air trusteeship and carbon asset management, create a green, smart and customized energy ecology, help enterprises save energy and reduce emissions, and achieve green, low-carbon and sustainable development

Digital Transformation Mass Customization

Scheme level: product customization, service customization, personalized customization, intelligent service and accurate delivery

Process level: lean improvement, process module, flexible production, intelligent detection and intelligent production scheduling

Technical layer: equipment, IOT, digital twin edge computing, artificial intelligence, identification analysis

Organizational level: Man-Order schedule, organizational change, lean training, corporate culture, digital management

Interaction layer: customization system, customization tools, user community, intelligent terminal and data platform

Emerging industry system development

Technical consulting is also conducted in the four major fields of technology development in new industries. See the following four major technology development areas. In each field, the scheme can be fine tuned according to the specific situation of customers. For example, in the field of business data modeling, the model and application can be adjusted according to the customer's industry, such as gene modeling (BGI) and clothing sales forecast model (Kaltendin).

  1. Production process optimization based on AI defect prediction model. This is to show the special report of Shenzhen Metal Data team on September 5, 2018 (Shenzhen quality month launch day): the scheme of manufacturing quality defect early warning system based on artificial intelligence.

  2. Metal Data Industry 4.0 brain - business data modeling pptx: as long as there is high-quality data, high-quality models can be established, such as genetic data (BGI), financial data, online sales data and inventory optimization based on accurate sales forecast (Kaltendin project), etc

  3. Metal Data quality management -- Defective Product Online Detection System: the defect level is 0-100. If it exceeds the upper limit, it is a defective product; Adjusting the safety factor can ensure no missing report of defective products; Eight optimization measures to ensure the high accuracy of the model (cooperative R & D project with Bosch / Wuxi Weifu)!

  4. Diagnosis optimization based on MES (or other data sourses): Data cleaning, closed-loop diagnosis and closed-loop control (single section, section group and the whole manufacturing process), weakness discovery based on MES to optimize the process

Smart Manufacturing Direction Guidance and Maturity Evaluation


Focus on the cost and potential planning of automation, digitization and intellectualization of small and medium-sized enterprises, with 30 years of factory site experience.

  1. Direction leading: choose German style of Smart Manufacturing or US style of Industrial Internet according to a series of factors

  2. Maturity evaluation: evaluate the maturity of factory Smart Manufacturing according to the site conditions; According to the comprehensive score, which grade does the enterprise belong to

  3. Evaluation areas: dozens of business areas of the factory for evaluation

See: Smart Manufacturing Training based on Project Cases.

Planning & Consulting

  Biz discussPlanningMaturity, Consulting Area, Predict Maint.
Defect Early WarningModelsManufacturingLi-BatterySteel

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