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The state space is a representation of all possible states that a system can be in. In the context of the intelligent manufacturing system discussed in the paper, the state space can be formulated as follows:
State Space:
Enterprise State (E): Represents the overall state of the enterprise, including key performance indicators (KPIs), production status, and market demand.
System State (S): Describes the current state of the intelligent manufacturing system, including the status of AI applications, production processes, and logistics.
Product Lifecycle State (P): Captures the state of products from design to production and logistics, considering factors like quality, defects, and customer feedback.
PEAS Properties:
PEAS stands for Performance measure, Environment, Actuators, and Sensors. It helps define the components and characteristics of an intelligent agent.
Performance Measure:
Objective: Improve enterprise profitability, competitiveness, and KPIs.
Criteria: Increase production efficiency, reduce defects, optimize decision-making, and achieve end-to-end integration.
Environment:
Intelligent Manufacturing Environment: Includes the enterprise, production facilities, market dynamics, and customer demands.
Dynamic: Changes over time based on market trends, technological advancements, and enterprise decisions.
Actuators:
AI Technology Implementation: Actuators involve the implementation of AI technologies such as machine learning, computer vision, natural language processing, and knowledge graphs.
Decision-Making Systems: Actuators drive decisions in demand analysis, KPI analysis, operation optimization, and product lifecycle control.
Sensors:
Data Sensors: Collect data on market demands, production processes, product quality, and customer feedback.
AI Technology Sensors: Gather information on the performance of AI technologies, including learning capabilities and cognitive functions.
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