Alps System Integration (Dalian) Co., Ltd., leveraging over 30 years of experience in manufacturing services, has launched a standardized product for APS (Advanced Planning and Scheduling) systems. By utilizing a SaaS platform, it delivers modular and component-based services, reducing the cost of customized development for enterprises.

The intelligent maintenance system of Alps System Integration (Dalian) Co., Ltd. (referred to as "ALSI") incorporates a dedicated performance management module, enabling managers to conduct multi-dimensional quantitative assessments based on system data.

Big data technology not only enables efficient device management but also allows device data to precisely serve the daily equipment management of smart factories.

It is essential to conduct a follow-up analysis of the root causes of equipment failures, as this constitutes a critical task for enabling effective maintenance and repair operations within a smart factory.

Establishing an intelligent factory information network to achieve the integration of informatization and industrialization is not only a necessity for societal development but also essential for enterprises to adapt to market dynamics and foster their own sustainable growth.

Inspection Standard Management. Inspection standards, developed in alignment with equipment technical standards, serve to guide inspection activities in smart factories and establish standardized inspections.

Fairness, justice, and transparency should be embedded in the performance evaluation of the equipment maintenance management system in a smart factory.

TPM advocates that the responsibility for equipment health management should lie with the equipment operators, who perform autonomous maintenance, thereby enhancing their familiarity with the equipment and reducing the occurrence of issues.

Smart factories and automated factories are two completely different concepts. From the perspective of a smart factory, automation is just a very small part of it.

The Smart Maintenance System enables intelligent early warning of equipment failures, fully leveraging the value of data to shift from a reactive to a proactive approach. This results in time, labor, and effort savings, while continuously reducing costs and improving efficiency.