Company Introduction
Shanghai Mathartsys Software Co., Ltd. (Mathartsys, referred to as "Mathartsys" or "MAS") was established in 2011. It is a high-tech enterprise specializing in complex supply chain planning intelligent decision-making general software for large manufacturing enterprises in various industries. It has been rated as a specialized and innovative enterprise, double-soft certified, and enterprise technology center.
Since 2013, Mathartsys has provided the industry-general IDEAS supply chain planning intelligent decision-making system for many large manufacturing enterprises such as SAIC-GM, SAIC Maxus, SAIC IM, BYD Auto, Foton Daimler, SGMW, Changan Auto, Chery Auto, SAIC Volkswagen, as well as Yanfeng Interior, United Automotive Electronics, Huayu Automotive, Yapp Auto, Audaque, Nexteer, FinDreams Battery, FinDreams Power, and Sanhua Intelligent Controls. Through various functional systems of IDEAS, efficient and accurate supply chain planning and optimal resource utilization have been achieved.
Starting from the automotive industry, Mathartsys has gradually expanded to new energy batteries, mechanical equipment, electronic manufacturing, metallurgical steel, chemical medicine, new materials, and many other industries.
Core Pain Points
- Delivery Cycle Challenges: Under traditional development models, customized projects have high development costs and long cycles.
- High Demo Costs: When conducting POC (Proof of Concept) demonstrations for customers, the original cost investment was substantial.
- Industry Complexity: Need to address deep business challenges such as end-to-end supply chain integration, production-sales coordination, and complex production scheduling.
Solution: Productization Reconstruction Based on Oinone
Mathartsys leverages the Oinone platform to transform years of practical experience into multi-modular products. The core architecture includes:
- IDEAS_APS Intelligent Decision Platform: Provides planning platforms, digital hubs, indicator systems, analysis platforms, and twin monitoring. Specific functions include management planning, production scheduling, demand coordination, risk warning, and sandbox simulation.
- Demand Forecast Analysis System (DFAS): Provides quantitative forecasting, qualitative adjustment, and other capabilities to guide OEMs and manufacturing enterprises in inventory, production, and procurement decisions.
- Full Business Module Coverage: Including supply chain network modeling, OTD (Order to Delivery), inventory management, algorithm orchestration, and intelligent scheduling.
- Function Implementation:
- Material Availability Dashboard: Supports monitoring of demand quantity and estimated availability by product dimension and region dimension, providing daily/weekly availability shortage lists and bottleneck material lists.
- Rule Configuration Tool: Provides a visual RSQL rule configuration interface, supporting entity attribute management, calculation rule setting, and indicator classification management.
Business Value
- Business Empowerment:
- POC Demonstration: Demonstration costs are significantly reduced while customer satisfaction is notably improved.
- Configuration-based Delivery: Achieved coexistence of standard product secondary development and customer personalized delivery.
- Market Influence:
- Automotive Industry: Successfully served multiple leading enterprises including SAIC-GM, BYD, Changan Auto, Chery Auto, and IM Motors.
- Manufacturing Sector: Has served enterprises such as Yanfeng Seats, United Automotive Electronics, Yapp, FinDreams, and Audaque.
Oinone Value
In the productization reconstruction process of Mathartsys, Oinone played an important role in promoting the productization of complex decision-making capabilities.
- Core Competence Assetization: Mathartsys has deep industry accumulation in supply chain decision-making, planning optimization, and intelligent analysis. Through Oinone, these capabilities that previously remained at the "project delivery" level have been reorganized, transforming algorithms, rules, scenarios, and interactions into modular, configurable, and productized digital assets.
- Fundamental Transformation of Delivery Model: The delivery process has transformed from being highly dependent on "consultant experience" and "deep customization" to outputting demonstrable, assemblable, and reusable product capabilities.
- Cross-generational Upgrade of Capability Form: Achieved a qualitative leap from "solving single project problems" to "outputting a category of industry-general capabilities", providing a standardized foundation for large-scale replication and cross-industry expansion.