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Project background

 

XXX Electric Locomotive Co., Ltd. is the core subsidiary of China Zhongche, an important electric locomotive research and development base in China, and a leading enterprise in Hunan's 100 billion rail transit industry cluster. The company mainly focuses on electric locomotives, urban rail vehicles, inter-city EMUs, maglev vehicles, energy-storage rail/trolley cars and other new technologies, public transport vehicles, important components, proprietary technology extension products and maintenance services.

 

In 2011, XXX Machinery began the preliminary exploration of knowledge innovation. Based on the requirements of quality management system standards such as IRIS certification, the company has set up the Department of Knowledge Management and Standardization, which is responsible for the construction of the company's knowledge innovation system. In 2013, the company began to implement knowledge engineering projects in the R&D field. After two phases of construction, it spent a lot of money on the online knowledge engineering system platform. 

 

However, due to the lack of knowledge about knowledge innovation at that time, the knowledge innovation service providers did not have the ability to consult. At present, knowledge engineering system has many problems, such as incomplete knowledge attribute, unreasonable knowledge system, too few search dimensions, insufficient search engine function, and poor system operation interface. Quasi-search and query, knowledge can not be effectively applied, and the value of knowledge can not be fully exploited.

 

Programming process

 

With the issuance of the new international standard ISO/TS 22163, new requirements for organizational knowledge are put forward. With the standard certification, China Locomotive and Machinery Company has begun to promote knowledge innovation throughout the company. Learn from the previous experience, this time to determine the company's first demand research, diagnostic consulting work, and then consider the overall strategy of system platform optimization, transformation or development. 

 

Firstly, it makes an in-depth investigation and Study on the current situation of knowledge innovation of locomotives and locomotives, combs the demand for knowledge innovation in the company's business activities (excluding R&D areas), analyses the existing problems and their causes, puts forward improvement measures and countermeasures, and forms the Diagnostic Report on Knowledge Innovation of Locomotives and Locomotives in China on the basis of the above contents. 

 

Secondly, on the basis of the inventory table of knowledge assets of Zhongcha locomotive, the inventory table of knowledge assets of various business activities is supplemented and perfected, the top-level classification design suggestions and key knowledge list of knowledge of Zhongcha locomotive are put forward, and the Knowledge System and Key Knowledge Report of each business activity of Zhongcha locomotive is compiled.

 

Finally, the knowledge innovation concept introduction training is completed, and the diagnosis project results are conveyed and interpreted. The specific content is detailed in the technical specifications. The measures and Countermeasures of knowledge innovation improvement and suggestions of top-level classification design proposed in this diagnostic project should all respond to the provisions related to knowledge innovation in ISO/TS 22163-2017 Railway Quality Management System (RQMS).

 

Project results

 

This consulting project has gone through three stages: current situation assessment and diagnosis, overall design of system architecture, training and workshops. A total of 70 people from 32 departments were interviewed. 2818 valid questionnaires were distributed and effectively recovered. Two training sessions on knowledge innovation concept introduction and three thematic work on knowledge innovation were organized. Fang, finally completed the work on time and quality assurance.

 

At the project report meeting, the consulting results were highly recognized by all levels of customers (senior management, knowledge innovation department and various business departments). The diagnostic report of knowledge innovation is comprehensive, systematic and meticulous. It summarizes and summarizes from the bottom to the top, and elaborates on key discoveries from the top to the bottom. The problem summary is objective and in place, and the improvement proposal is operable.  

 

The architecture design of knowledge system is scientific and reasonable, and the extensibility of the future is fully considered. The design of navigation search and knowledge clustering of multi-dimensional facets "solves the problem of multi-dimensional classification of knowledge which has been considered for many years but has not been solved by knowledge engineering." (Comments from senior customer management) is a highlight in the work of this project.

 

In the process of the project, through the introduction of training, workshops, team co-creation and other ways, we have continuously created a field, which has trained a number of seeds to continuously promote knowledge innovation in the business sector. By systematically improving their awareness, ability and accomplishment, we can be the engine of knowledge innovation in the future.