ThinkIQ is a Model-Centric and Model-Driven system. A good model transforms data into information, making it discoverable, providing context and bringing it to life. The model gives information context and meaning. Good modeling drives the success of the entire project. All ThinkIQ applications actively use the model for visualization, navigation, analysis, expressions, scripts, and search. Therefore, it is important to understand the basic modeling concepts before building a model.
Modeling benefits
The model delivers many benefits:
- Gives manufacturing information meaning and context
- Enables discovery and exploration of complex systems without prior knowledge
- Makes it easy to perform calculations on the collected data
- Makes it easy to visualize, analyze, report and otherwise reuse the collected data
- Abstracts developers from the complexity of data ingress allowing them to write reusable code against an object model
- Reduces enterprise costs through re-use of models across industries and plants
Note that the word "Model" has multiple meanings. The ThinkIQ Model includes the naming, configuration, organization, logic, and relationships between physical and material objects. The ThinkIQ Model is different from Machine Learning Models, and digital twin models, but the ThinkIQ Model greatly simplifies the creation of machine learning algorithms and digital twins.
Modeling basics
The best way to model is to start with existing types and instances that others have created. ThinkIQ comes with built-in models and allows models to be built in a layered and collaborative fashion. If the built-in functionality does not fit your needs, you can create new content or extend existing content that can be shared and reused. Libraries allow models to be imported and exported. Certain industries or processes may have commercially available pre-built libraries.
Here are some fundamental concepts and definitions of terms used in ThinkIQ Models:
- A model will usually include several sub-models.
- The organizational model is a high-level overview of the business or supply chain. It consists of Enterprises, Organizations, Business Units, Sites, Plants, Places and Areas and also defines the relationships between these elements (for example the flow of goods between Plants). It is typically used to create the overview of the Supply Chain and it is a good idea to start here to create the "big picture" before modeling the details. Don't worry about getting it right first time, as modeling is usually iterative and you can add more details as your model matures.
- The equipment model is used to define the physical equipment in your process. This model describes your physical assets and defines how measured data from automation and quality systems applies to the equipment.
- Equipment Types are used to define the "shape" of the data for a type of equipment. As an example an Equipment Type of "Pump" is created once and is used to create all instances of individual pumps. This provides a template for all pumps. From a developer perspective an Equipment Type is a Class definition.
- Equipment Instances represent specific physical equipment. For example "Drinking Water Supply Pump" attached to a specific plant represents a specific pump in your organization.
- Equipment Types support composition. This means that you can define Types built up from other (smaller) Types. For example an Equipment Type called "Batch Tank" might be composed of several simpler Types such as Agitator, Heater, Inlet Valve and Outlet Valve.
- The material model is used to define the materials used the manufacturing process. These materials may be raw materials required to produce finished goods, or materials consumed that allow manufacturing to occur, such as power, water, et. al.
- Material Types are used to create Raw Material, Intermediate Product, Finished Goods and other materials consumed. The attributes on Material Types are used to define the specifications of the material. Instances of materials are created dynamically. For example an instance can be created for every batch of material. Relationships on Materials relate them to equipment, equipment types, and organizational nodes.
- The generic object model covers entities that don't fit into the above categories. These objects are represented by things like email notifications, work shifts, equipment nameplates, purchase orders, and material samples. Generic objects allow flexibility to create re-useable objects that can be unique to a particular manufacturing process.
- Attributes represent data that can change over time. When you create Types you will usually define the attributes of the type. Attributes are synonymous with what developers call Properties. Depending upon where the data values for the attribute come from (the Data Source), an attribute can be one of the following:
- Dynamic - The values are constantly updated. When you create an equipment instance with a dynamic attribute, you will specify if the attribute's data source is a Tag (the data is collected by an automated system, called a connector, and mapped to the tag) or Internal (the data may be calculated by a script, an application or manually entered). Multiple attributes can point to the same tag. For example, Tank Level.
- Configuration - These attributes define a configuration value. The values typically don’t change over time and are not treated as time-series data. For example: Tank Capacity.
- Expression - The values are calculated using expressions. They can be calculated on demand (very flexible) or periodically calculated and stored (usually higher performance).
- Relationships are used to define how nodes in the model relate to one another. This creates a Graph that can be used for many things such as:
- Visualizing how materials move through equipment.
- Showing how utilities such as electrical power, steam and air feed the equipment.
- Visualizing which materials are consumed and produced by equipment
- Visualizing the conversion steps that convert Raw Materials to Intermediate Products to Finished Goods
- Quantity Kinds and Measurement Units:
- The platform has a powerful subsystem of Quantity Kinds, Units of Measure and Conversions. This allows automatic unit conversion and advanced calculations.
- Scripts:
- The model includes code that provides behavior making the model smart. Code can be part of Types or Instances and can be triggered by schedules, events, or user interface actions. Code can be written in Python, PSQL, PHP, JavaScript, and HTML/CSS using the Mini-IDE.
- Tags:
- Information that is collected by an automated system, called a connector.