Capabilities:

① Monitor and Synchronize Manufacturing Operations

Achieve comprehensive visibility across every production site, controlling product quality and production efficiency. The Manufacturing Execution System (MES) can monitor multiple production lines, manufacturing plants, and supplier networks in real time, communicating quality inspection information and monitoring output and other key performance indicators (KPIs).

② Enable Paperless, High-Quality Manufacturing

Communicate and utilize digital twins of products, Bills of Materials (BOMs), Lists of Processes (BOPs), and other critical production information to coordinate shop floor operations without paper documentation. Ensure efficient flow of raw materials, supplied components, and work-in-process throughout the production process. Notify and guide personnel to execute each step correctly in real time.

③ Model and Adapt Complex Processes

Overcome the complexities of today's products and manufacturing processes, ensuring products are produced on schedule, on time, and cost-effectively. The MES supports complex workflows, mass customization, stringent manufacturing traceability requirements, and extensive automated data collection.

④ Track and Trace Production

Learn detailed product and order information throughout the shop floor at any time. Track production batches, lots, equipment, or units. Acquire real-time status of production equipment and processes, while recording a complete history of executed operations. Quickly and securely access production documentation (from planning to completion information), including regulatory and standard operating procedures.

⑤ Identify and rapidly resolve manufacturing issues

Make evidence-based decisions based on recent executable performance data. The MES solution provides current reports on actual manufacturing operations and comparisons with historical and expected results. Use real-time feedback to perform root cause analysis and rapidly resolve production issues.

Accelerate the Development of Top-Quality Products

Leverage a quality management system to reduce costs and achieve high levels of customer satisfaction.

Capabilities:

① Define and Initiate Risk-Reducing Quality Planning

Simplify quality planning through a product development process from prototype to mass production. Monitor events and identify potential problems promptly to prevent quality issues from occurring. Support Advanced Product Quality Planning (APQP) and accelerate the quality development process. The quality management system planning phase includes Failure Mode and Effects Analysis (FMEA), control plan definition, and Production Part Approval Process (PPAP).

② Ensure High Quality Through Reliable Production Processes

Ensure expected quality requirements are met throughout the entire process from incoming materials and components to finished products. Quality management includes quality inspection planning and execution, analysis using Statistical Process Control (SPC) tools, and supplier quality management. Detect product and process deviations, identify root causes, and correct defects. Ensure compliance and automatically generate documentation to support quality audits.

③ Ensure Continuous Quality Improvement

Support continuous quality and productivity improvement for sustainable development through problem and complaint management capabilities. Obtain data and costs related to external and internal complaints and centrally manage quality-related operations. Insights gained from a quality management system can quickly identify weaknesses and prompt action to improve operational quality and productivity.

Capabilities:

Medium- to Long-Term Planning

Opcenter APS can handle long-term strategic planning spanning months or even years, as well as medium-term tactical planning lasting weeks, along with detailed sequencing and scheduling. Through its limited-capacity medium- to long-term planning capabilities, it maximizes capacity under limited resources, enabling more refined production task management. APS's medium- to long-term scheduling is based on limited capacity, simultaneously considering forecasted order demand and resource capacity to balance them and calculate the planned time for forecasted orders and remaining resource capacity.

Resource Capacity

Opcenter APS schedules production for each machine with limited or unlimited capacity, using various constraints such as tools, operators, materials, and energy/water consumption. It enables more precise scheduling at the machine level and assigns different shifts and operating speeds to each machine.

Order Prioritization

Opcenter APS allows for easy modification of plans based on delivery dates, priorities, or other attributes, such as adding new orders, changing priorities, increasing machine downtime, and ending jobs. It supports prioritizing products based on delivery dates, maximizing on-time delivery and improving customer satisfaction.

Sequence and Synchronization

Opcenter APS can synchronously update schedules based on material constraints and provide relevant KPIs for rapid analysis and evaluation of plan quality. It also helps companies maximize production operational capabilities based on production constraints. Using Opcenter APS for automated process-level scheduling can improve the synergy of tasks across different processes.

Production Changes

Opcenter APS can respond promptly to production changes, interruptions, machine failures, and scrap, and update production schedules. During execution, it continuously analyzes and optimizes based on the addition of new orders and feedback from the production workshop, providing updated production planning and scheduling results to guide specific production in the workshop.

Capabilities:

Basic Data Maintenance

Basic data maintenance is the cornerstone of intelligent warehouse management, involving the management of key information such as material master data, supplier master data, customer master data, inventory locations, and cost centers. This data is typically synchronized from the enterprise's resource planning system (such as SAP) to ensure consistency and accuracy. Through effective basic data maintenance, enterprises can ensure that the information in the warehouse system is up-to-date and accurate, thereby improving overall operational efficiency.

Inventory Management

Inventory management is a core component of intelligent warehouse solutions, including real-time monitoring of inventory levels, inventory quantity statistics, recording inventory changes, and setting inventory alerts. This module helps enterprises rationally plan inventory, avoiding overstocking or understocking, and facilitates the management of batches, expiration dates, etc., of inventory goods through scientific coding, ensuring the accuracy and timeliness of inventory data.

Inbound Process Management

Inbound process management involves various types of inbound processes, including purchasing, production, and returns, encompassing receiving and shelving operations. Warehouse staff can flexibly choose to perform batch or detailed operations using PCs or PDAs to adapt to different operational scenarios. Through an intelligent warehouse management system, inbound operations can be completed quickly and accurately, effectively shortening operation time and improving accuracy.

Operation Monitoring and Scheduling

Operation monitoring and scheduling is a crucial component of intelligent warehouse management. It provides intuitive, real-time warehouse operational data through real-time data capture and monitoring. This helps optimize warehouse layout and improve operational efficiency. The system can centrally monitor the entire warehouse network, including equipment status, personnel distribution, and vehicle scheduling, ensuring smooth and efficient workflows.

In-Warehouse Business Management

In-warehouse business management encompasses the management of goods storage locations, shelving layout, and goods classification within the warehouse, helping to improve warehouse space utilization and reduce damage and loss of goods. Through an intelligent warehouse system, enterprises can achieve refined warehouse location management, implementing "first-in, first-out" (FIFO) to prevent goods loss.

Report Management

The report management function can generate various warehouse and inventory management reports, including statistics and analysis of inbound, outbound, and inventory change data, helping enterprises understand warehouse operations and make informed management decisions. These reports are essential for monitoring warehouse performance and guiding business decisions.

Outbound Operation Management

Outbound operation management includes the generation of outbound documents, the entry and management of outbound product information, and the tracking and recording of outbound operations. Automated outbound processes improve the accuracy and efficiency of outbound operations, ensuring goods are shipped on time, in the correct quantity, and accurately.

System Strategy Configuration

System strategy configuration is the brain of the intelligent warehouse management system. It allows enterprises to configure system parameters and rules according to business needs and operational strategies. This includes, but is not limited to, inventory control strategies, safety stock levels, and replenishment strategies. Through flexible strategy configuration, enterprises can adapt to market changes, optimize inventory levels, and improve responsiveness and customer satisfaction.

Capabilities:

Formula Management

Formula management is a core business of chemical enterprise R&D, involving key aspects such as formula development and validation management. In traditional R&D processes, these aspects often rely on paper-based or Excel-based data recording, leading to ineffective data control, retrieval, and reuse, resulting in redundant R&D and resource waste. Digital transformation is an inevitable path for chemical enterprises. Formula management systems such as HF-LFMS provide information solutions for project management, electronic record books, laboratory management, formula management, and process management, helping enterprises achieve data-driven transformation.

Production Standard Management

Production standard management ensures that laboratory activities comply with industry standards and regulations. Laboratory Information Management Systems (LIMS) play a crucial role in this process, supporting functions such as test requesting, sample management, equipment management, application acceptance, task assignment, test items, test reports, and payment settlement by building core testing business processes, thereby supporting all stages of drug development and quality control.

Test Request and Sample Management

Test request and sample management is an important part of laboratory operations. The LIMS system, through its application acceptance function, enables test applicants to fill out drug testing application forms and provide test samples and technical information. The laboratory sample administrator receives samples, which are then reviewed and confirmed by the technical supervisor to ensure that sample inspection and management are carried out according to prescribed procedures.

Laboratory Instrument Integration

Laboratory instrument integration is the cornerstone of ensuring laboratory data integrity. The integration of modern LIMS with laboratory instruments enables automated data acquisition, storage, and analysis, improving data accuracy and consistency and significantly enhancing laboratory efficiency. This integration reduces the risk of errors from manual data entry, ensuring accurate data recording and audit trails, and compliance with regulatory standards.

Electronic Lab Notebook (ELN)

An Electronic Lab Notebook (ELN) is a secure and reliable software system that aggregates experimental data from multiple sources, supports the recording of the complete experimental process and results, and packages it into legally compliant documents. ELNs eliminate handwritten transcription, improve data recording and adjustment efficiency, enhance data quality and standardization, are suitable for long-term storage, and can be used by research teams located in different areas.

Laboratory Execution System (LES)

A Laboratory Execution System (LES) is an ELN for quality control laboratories, primarily used in analytical laboratories during the production phase. LES enforces Standard Operating Procedures (SOPs), ensuring testing conforms to SOP specifications. Analysts cannot proceed to the next step if the previous one is not completed. The main difference between LES and ELN is that LES focuses more on quality control and the execution of laboratory activities during the production phase.

Through the integration and collaborative work of these systems, laboratories can improve testing quality, efficiency, and quality control management, thereby accelerating time-to-market for new products while maintaining product quality.

Capabilities:

Enterprise and Multi-Factory Visualization

Enterprise and multi-factory visualization refers to the use of data visualization technology to graphically display the operational data of an enterprise and its multiple factories, providing a global perspective for monitoring and managing the enterprise's operations. This visualization technology helps decision-makers quickly understand complex datasets, uncover patterns behind the data, and improve decision-making efficiency and capabilities. For example, an industrial hoist equipment monitoring dashboard visualizes key equipment data and operational status, achieving a panoramic view of the equipment and providing monitoring and early warnings, reducing decision-making risks.

Self-Service Data Discovery and Dashboards

Self-service data discovery and dashboards are business intelligence analytics tools that allow users to explore and analyze data without relying on the IT department. Users can quickly configure and customize dashboards through drag-and-drop, delivering business data in an intuitive and vivid visual way, revealing data value. Dashboards not only display data but also include user insights, suggestions, and expected business impact, aiming to drive action rather than simply providing notifications.

KPI Calculation

KPI (Key Performance Indicator) calculation is a key tool for measuring enterprise performance. It includes various calculation formulas, such as Completion Rate = Actual Value ÷ Target Value × 100%, and weighted KPI indicator formulas. KPI indicators are widely used in areas such as corporate performance management and personal career planning, helping HR measure employee performance and conduct evaluations and incentives.

Problem Root Cause Analysis

Problem root cause analysis refers to identifying the root cause of a problem through data analysis techniques. In enterprise intelligent analysis, this typically involves data mining techniques, such as correlation analysis. Algorithms (e.g., the Apriori algorithm) determine the association rules between different events or items, helping companies discover the root causes of problems and develop corresponding solutions.

Advanced Data Correlation Analysis

Advanced data correlation analysis is a data mining technique used to discover interesting relationships between items in large amounts of data, such as frequent patterns, associations, and clustering. This analysis can help companies understand customer behavior, optimize inventory management, and improve marketing efficiency. For example, correlation analysis can reveal that certain products are frequently purchased together, providing a basis for cross-selling and inventory management.