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Industry Model, Intelligent Algorithm, Human-Machine Interaction, Scientific Scheduling

APS Intelligent Planning and Scheduling System

The APS (Advanced Planning and Scheduling System) considers constraints like resources, shifts, product processes, materials, and inventory. It creates detailed schedules based on limited capacity, aligning demand with planning and execution with materials. Utilizing TOC-DBR theory, it maximizes bottleneck capacity and optimizes output.
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Pain Points

Difficulty in Responding to Promised Delivery Dates

In the face of complex and variable orders and frequent order insertions, it is challenging to assess and confirm promised delivery dates. The provided delivery dates either lack market competitiveness or are difficult to guarantee.

Low Resource Utilization

Production planning relies heavily on manual experience and spreadsheets, limiting scheduling capabilities. This makes it challenging to allocate limited resources like equipment, manpower, and tooling efficiently, resulting in low resource utilization, inability to optimize bottleneck resources, and increased operational costs.

High Inventory and Excess Stock

To meet delivery commitments, planning often relies on experience to increase inventory levels of finished and self-manufactured parts. This not only leads to high and excessive inventory but also creates obsolete stock when orders change, increasing material costs for the company.

Frequent Equipment Changeovers and Low Production Efficiency

Planning struggles to optimize production by combining or splitting orders with the same specifications but different delivery dates, leading to frequent equipment changeovers and barrel cleaning, resulting in prolonged production cycles and inefficient productivity.

High Outsourcing Costs

Planning is unable to forecast globally across different production stages and equipment, causing bottleneck equipment to frequently outsource different tasks with compromised processing precision, leading to high outsourcing costs, long cycles, and low quality.

Functions

Industry Model
Demand Orders
Production Orders
Work Order Management
Material Planning: Includes three sub-modules

Industry Model

Offers seven major functions, including scheduling and planning, bottleneck optimization, intelligent algorithms, enterprise strategies, threshold boundaries, multi-objective optimization, and data interconnection. It digitizes enterprise process constraints and rules for scheduling and provides import of mature industry business models to quickly onboard planners using industry-standard data models.

Demand Orders

Provides functionalities for order batching, merging, enabling, freezing, and simulation. This is used to perform periodic capacity forecasting for large-scale, annual, and semi-annual product demands. It helps to achieve the breakdown of products, sub-products, and related products, establishing the most economical production order and material provision relationship for balanced production.

Production Orders

Provides production planning for three types of orders: formal sign-off, in-progress production, and simulation assessment. It also includes six sub-modules such as order/in-progress management, equipment management, manpower management, tooling/die management, resource/calendar management, and process structure management. This achieves static analysis and data management for demand and rated capacity, aiding in responding quickly to promised delivery dates and improving market competitiveness.

Work Order Management

Offers four sub-modules: production planning (Gantt chart), resource planning (graphics), resource load (graphics), and operation task details. It visualizes and graphically represents scheduling production plans, with data analysis functions in each sub-module to help planners locate, analyze, and adjust plans easily, including splitting, merging, LFT, EST, sequencing, priority settings, and candidate resource allocation for human-machine interaction and prompt intervention strategies.

Material Planning: Includes three sub-modules

material supply planning, material consumption details (graphics), and material purchase planning. It aligns data transparency for finished products, self-manufactured (parts), raw materials, and formulations with workshop production capacity. Each sub-module provides analysis functions to help planners understand the impact and demand of materials on production capacity, ensuring material requirements are met, procurement has a source, and material availability warnings are flagged.

Advantages

  • More Intelligent Scheduling Strategy

    Offers powerful industry models and intelligent algorithms, providing smart evaluation and analysis for delays, idle times, and waits. It enables automatic combining/splitting, overtime planning, external coordination, and changeovers to address bottleneck issues through multi-objective optimization, accommodating scenarios that simple constraints in traditional APS forward/backward scheduling cannot solve.

  • Stronger Analysis Functionality

    Provides a visual interface presenting planning associations for each operation, equipment, manpower, material, and tooling with intelligent analysis functionality. It presents results in seven states (delay, wait, idle, add, external, combo, split, self), each with deep intelligent analysis to quickly identify bottlenecks and suggest solutions with multi-dimensional dashboards/reports.

  • More Scientific and Efficient Scheduling

    Combines industry practice models with intelligent algorithms to produce plans aligned with real business processes and constraints, supporting iterative artificial interventions. This assists in creating the most satisfactory and appropriate production plans, aiding in knowledge base development, and reducing reliance on experience.

  • Cross-platform, Cross-service Deployment Scheduling System

    Supports cross-platform, cross-service, multi-factory, and multi-terminal operations with options for SaaS, cloud-native, virtual server, or physical server deployments. Facilitates scheduling and operations on PCs, mobile, and tablets. The combination of industry models and intelligent algorithms enables rapid computation, completing production scheduling for 5,000 devices and 800,000 operations within 35 seconds.

  • Easy, Flexible Data Integration and Good Performance

    Compatible with most mainstream third-party systems, including Kingdee, SAP, Yonyou (UFIDA) products, and various industry-specific ERP, MES, MOM systems. Provides an industry-standard MQ service component to support message pushing and consumption, achieving a business architecture for system isolation and data interoperability.

  • Simplified Operation

    Intuitive graphics and dashboards allow drag-and-drop operations for quick intervention in production plans. Unlike typical C/S scheduling systems, Eman's APS intelligent planning and scheduling system benefits from a B/S architecture, providing identical interactions with app operations for easy system onboarding.

Business Process Diagram

EMAN Intelligent APS - The process from requirement exploration to practical application.

 

Value

  • 20%~40% ↓
    Reduced production preparation costs
  • 28% ↓
    Shorter production cycles
  • 5%~30% ↓
    Lower production planning costs
  • 15%~70% ↑
    Improved quality of executable plans
  • 10%~40% ↑
    Increased on-time delivery rate

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