Policy Interpretation and Application Guide
⚠️ Disclaimer
This guide is intended to help enterprises understand how to connect the capabilities of StarWay Data Insight (StarWayDI) (an offline PCA/PLS/PLS-DA/OPLS data analysis tool) with relevant national and local policies and project applications.
Policy documents, application conditions, and links will change or be updated over time. The information on this page is a compiled reference and does not constitute a basis for application.
Before you actually apply, be sure to go to the relevant government official websites to verify that the documents are currently in force.
I. National-Level Policy Documents the Tool Fits
The following policy documents cover directions such as intelligent manufacturing, industrial data, quality control, and digitalization of the food industry.
📌 How to read this: The "Core Adaptation Points" column in the table describes the correspondence between this platform's capabilities and that policy direction. It is our interpretation, and is not a quotation from the original policy text. When citing it in application materials, please take the original policy text as authoritative.
| Policy Document Name | Issuing Authority | Release Date | Adaptation Direction with This Platform | Official Link |
|---|---|---|---|---|
| "Measures for the Gradient Cultivation and Management of Intelligent Factories (Interim)" （工信部联通装〔2025〕262 号） | MIIT, NDRC, MOF, SASAC, SAMR, National Data Administration (six departments) | Issued December 9, 2025 | Requirements on production process data analysis capabilities in the gradient cultivation of intelligent factories | View |
| "Implementation Opinions on the 'AI + Manufacturing' Special Action" （工信部联科〔2025〕279 号） | MIIT, Cyberspace Administration of China, NDRC, MOE, MOFCOM, SASAC, SAMR, National Data Administration (eight departments) | Drafted 2025-12-25 Released 2026-01-07 | Supports "intelligent quality control", and explicitly proposes promoting 500 typical application scenarios | View |
| "Implementation Plan for the Digital Transformation of the Food Industry" （工信部联消费〔2025〕129 号） | MIIT, MOE, MOHRSS, PBOC, SAMR, National Food and Strategic Reserves Administration, National Data Administration (seven departments) | June 10, 2025 | Quality stability analysis and batch consistency in the food industry | View |
| "Implementation Guide for the Digitalization of Manufacturing Quality Management (Trial)" （工信厅科〔2021〕59 号） | General Office of MIIT | December 30, 2021 | Tool and method support for quality management digitalization, including quality fluctuation analysis | View |
| "Notice of the General Office of the Ministry of Industry and Information Technology on Launching the Industrial Data Foundation-Building Action and Carrying Out Pilot Trials in Building High-Quality Industry Datasets for AI Empowerment" （工信厅信发函〔2026〕64 号） | General Office of MIIT | March 10, 2026 | Building high-quality industry datasets and processing multi-source heterogeneous data | View |
| "Guiding Opinions of the Ministry of Industry and Information Technology on the Development of Industrial Big Data" | MIIT | Drafted 2020-04-28 Released 2020-05-13 | Industrial data modeling and analysis, and application development | View |
💡 One practical tip: When citing policies in application materials, give priority to wording that actually exists in the original policy text, and note the document number. Writing "our interpretation" as "a policy requirement" is a common reason for application materials to be returned.
📎 About the link in row 1: The MIIT official website does not provide a separate original-text page for the "Measures for the Gradient Cultivation and Management of Intelligent Factories (Interim)"; the link in the table above is the 2026 annual action notice that quotes the document number of those Measures, and can serve as indirect evidence. If you need the full text of the Measures, you can consult the forwarded copies issued by provincial departments of industry and information technology.
II. Projects You Can Apply for After Factory Application
The following are common application directions related to this platform's capability areas. The specific application conditions, time windows, and support measures may all be adjusted every year; please take the official application notice of the current year as authoritative.
(1) Extended Applications Related to Smart Factories
| Application Project | Capabilities It Can Connect To | Adaptation Scenario | Policy Basis |
|---|---|---|---|
| Intelligent Manufacturing Typical Scenario Recognition | Quality prediction and control, process parameter optimization, anomaly detection | Use PLS to build a "process parameters → product quality" model, use PCA to identify abnormal batches, and form a replicable scenario case | "Promote 500 typical application scenarios" in the "Implementation Opinions on the 'AI + Manufacturing' Special Action" |
| Industrial Internet Innovation Application Cases | Data-driven quality control solutions | Connect to production line data to achieve offline review and process iteration, meeting the requirements for "quality control" cases | "Industrial Internet Innovation and Development Action Plan (2021-2023)" (that plan period has ended; please refer to the latest action plan) |
| Digital Workshop Recognition | Production process digitalization + quality analysis | As a supplementary tool to MES/ERP, improving the workshop's data-driven decision-making capability, corresponding to the "data analysis" indicator for digital workshops | GB/T 39116-2020 "Intelligent Manufacturing Capability Maturity Model" |
(2) Intellectual Property and Innovation Achievement Applications
| Application Project | Capabilities It Can Connect To | Key Conditions | Policy Basis |
|---|---|---|---|
| Invention / Utility Model Patents | Process optimization / quality control methods based on data analysis | Use the characteristic variables and parameter ratio rules mined by the tool to apply for a patent such as "A Multivariate Statistics-Based XXX Process Control Method" | "Patent Law of the People's Republic of China" |
| Enterprise Technical Standards (Enterprise/Group Standards) | Digital quality inspection and process specifications | Solidify the "optimal parameter boundaries" produced by the tool into the enterprise's standard operating procedures (SOP) or industry group standards | "Standardization Law of the People's Republic of China" |
(3) Quality and Management System Improvement Applications
| Application Project | Capabilities It Can Connect To | Adaptation Value | Policy Basis |
|---|---|---|---|
| Integration of Informatization and Industrialization Management System Certification | Data-driven quality control capability improvement | The tool supports the "data development and utilization" process domain and helps raise the assessment level of the integration of informatization and industrialization | GB/T 23001-2017 "Informationization and Industrialization Integration Management System Requirements" |
| DCMM Data Management Capability Maturity Certification | Data modeling and analysis capability development | Strengthen the "data application" capability domain and enhance the value of data assets | GB/T 36073-2025 "Data Management Capability Maturity Assessment Model" |
| Quality Benchmark Typical Experience Solicitation | Continuous quality improvement based on data analysis | Use the tool to build quality prediction models, reduce the defect rate, and form quality benchmark cases | China Association for Quality, "Notice on Carrying Out the Solicitation and Exchange of Quality Benchmark Typical Experiences" |
(4) Industry-Specific and Green Manufacturing Applications
| Application Project | Capabilities It Can Connect To | Adaptation Industry | Policy Basis |
|---|---|---|---|
| Green Factory Recognition | Data-driven efficient resource utilization | Use PLS to optimize process parameters, reduce energy/water consumption, and improve raw material utilization, supporting the "resource efficiency" indicator | GB/T 36132-2025 "General Principles for Green Factory Evaluation" |
| Typical Cases of Digital-Intelligent Transformation in the Food Industry | Digital-intelligent quality control solutions for specific sub-industries | Form a complete case of "data modeling + process optimization + quality improvement", in line with the key support direction of the seven-department document | "Implementation Plan for the Digital Transformation of the Food Industry" |
| Enterprise Technology Center Recognition | R&D capability improvement (development and application of data analysis tools) | The tool serves as a core technical achievement of the enterprise technology center, used for process innovation and quality improvement, raising the R&D strength score | "Measures for the Administration of the Recognition of Enterprise Technology Centers of the National Development and Reform Commission" (2025 年第 39 号令, effective 2026-02-01) |
(5) Science, Technology, and Innovation Award Applications
| Application Project | Capabilities It Can Connect To | Adaptation Conditions | Policy Basis |
|---|---|---|---|
| Science and Technology Progress Award (Provincial / Municipal / Industry Level) | Innovative application of industrial data analysis technology | Apply jointly with leading enterprises, using economic benefit data (such as reducing production costs by X% and raising the qualification rate by Y%) as supporting evidence | "Regulations on National Science and Technology Awards" and local implementation rules |
| QC Group Activity Achievements | Quality improvement projects based on data analysis | Use the tool to carry out QC topics such as "reducing the fluctuation of a certain indicator", forming digital QC activity achievements | T/CAQ 10201-2024 "Guidelines for Quality Control Group Activities" |
III. Application Strategy Recommendations
- Scenario focus strategy: Give priority to applying for digital transformation cases in specific industries (food, chemicals, new materials, etc.) and intelligent manufacturing typical scenarios. The tool is highly targeted in vertical industries and easily forms a differentiated advantage.
- Joint application strategy: It is recommended to apply jointly with upstream and downstream enterprises in the industry chain and with research institutes. Use actual application data (qualification rate improvement, energy consumption reduction percentage) as the core supporting evidence to improve the pass rate.
- Intellectual property mining strategy: Use the "golden batch" parameter rules and characteristic variables discovered by the platform to write invention patents or utility model patents. These process control methods derived from data are important support for applying for honors such as high-tech enterprise status.
- Standard alignment strategy: Benchmark against GB/T 39116-2020 "Intelligent Manufacturing Capability Maturity Model" and the relevant industry digital transformation indicators, to ensure that the application materials fit the policy requirements.
- Quantified achievement strategy: Quantify the application effects of the tool into core hard indicators that can be used for application, for example:
- Process optimization: Reduce energy consumption by X%, increase the target extraction rate by Y%
- Quality improvement: Raise the product qualification rate by Z%, reduce the quality fluctuation range by M%
- Efficiency improvement: Shorten data analysis time by N%, reduce labor costs by P%
⚠️ The X/Y/Z above are all placeholders; please fill them in with your enterprise's real measured data. Quantitative indicators in application materials need to be supported by traceable original records.
IV. Verification Notes and Disclaimer
- The names, issuing authorities, document numbers, and dates of the policy documents on this page have been verified against official channels (the MIIT official website, the National Data Administration official website, the Chinese government website, the National Standards Full-Text Public System, etc.).
- The "adaptation direction" in the table is the editor's interpretation, not a quotation from the original policy text. If you need to cite it in application materials, please go back to the original text and check the wording.
- National standards undergo version replacement (for example, GB/T 36132 has been updated from the 2018 version to the 2025 version). When citing, be sure to confirm that the version you cite is currently in force.
- Some application projects are organized by industry associations (such as the China Association for Quality) rather than government departments; their validity and application process differ from government projects, so please treat them differently.
- Policies and standards may be updated at any time. The content of this page does not constitute any application commitment or legal advice; in the end, please take the currently published official documents as authoritative.
🔗 Related Reading
- Factory Scenario Data Modeling Guide — how to translate policy requirements into concrete data modeling work
- Industrial Control Systems and the Data Insight Platform — the platform's position in the industrial system
- AI Intelligent Capabilities Overview — AI capabilities that can be used as case evidence