Committed to becoming a global supplier of electrification solutions

Company Scale: Consolidating Market Leadership Through Long-Term Dedication and Building a Growth Curve Through Strategic Expansion

Founded in 2008, Ningbo Jingcheng Motor has long focused on the niche market of specialized motors for automotive window regulators. As of 2025, the company employs over 1,400 people, with annual revenue exceeding 1.4 billion yuan and per-capita output reaching 1 million yuan; It holds a market share of over 40% in the domestic passenger vehicle market and over 70% in the new energy passenger vehicle sector, firmly maintaining its position as the market leader in this niche segment. Looking ahead, the company adheres to a strategy of specialization, scale, and globalization, coordinating its efforts around two key growth drivers—overseas market expansion and the development of new product categories—to continuously build long-term competitiveness.

R&D and Innovation: Strengthening the Technological Foundation Through Continuous Investment, and Supporting Business Success with Systemic Capabilities

The company is committed to driving business growth through technology, with R&D investment consistently maintaining a level of no less than 6% of annual sales. The R&D system is divided into three major modules: product platform R&D, project application R&D, and process and equipment R&D. The R&D team comprises over 230 members, accounting for 15% of the total workforce, with more than 90% holding a bachelor’s degree or higher—a talent density significantly higher than the industry average.

Aligning closely with industry trends and core customer needs, the company continuously refines its technology capability matrix, covering key technical areas such as NVH simulation, CAE simulation, electromagnetic analysis, brushless control hardware and software development, 4 anti-pinch algorithms, the 8V platform, EMC, new materials R&D, precision manufacturing, precision tooling, and in-house development of core equipment.

Starting in 2025, the company will adopt the IPD (Integrated Product Development) process to establish a collaborative mechanism between product planning and preliminary technical research. With a total laboratory area exceeding 2,000 square meters, the company obtained CNAS national-level laboratory certification in 2020 and will complete the first phase of its EMC (Electromagnetic Compatibility) testing facility construction by 2026, thereby continuously consolidating its leading technological position in the industry.

Digital Smart Manufacturing: Building a Vertically Integrated Manufacturing System and Moving Toward Data-Driven Smart Factories

The company has established three major production systems: precision injection molding, precision metal processing, and fully automated assembly. The automation rate in production areas exceeds 95%. Supported by a complete set of precision mold machining centers and precision measurement centers, the in-house production rate for core components reaches 50%, creating a closed-loop, vertically integrated industrial chain.

Aligning with global “Lighthouse Factory” development goals, the company is fully committed to implementing “unmanned factories.” Building on highly automated production lines, it has comprehensively deployed digital systems—including OA, PLM, E-HR, SRM, ERP, MES, WMS, AGVs, and automated warehouses—to establish a seamless digital workflow spanning the entire process from R&D to delivery. Leveraging the deep integration of MES and IoT, we have achieved 100% connectivity of key production equipment, enabling real-time collection of equipment operating conditions, process parameters (temperature, pressure, torque, etc.), quality data, and material batch information, thereby forming a closed-loop system for data collection, analysis, and application. Through the intelligent workshop kanban system, we have built capabilities for data-driven insights and scientific decision-making, driving a comprehensive transformation of manufacturing management from experience-driven to data-driven.