Automation & Process Control
The art of creating information from digital data sources.
The Sun Pays Automation can assist industry in data acquisition, storage and information display using the latest Internet of Things technology and in-house developments. We have an experienced team of engineers, data scientists and programmers to create a complete automation package customized to a client's needs.
Some of the great automation methods we can offer...
Use data collection and analytics to identify problems and causes.
Data can easily be obtained from systems, whether it is already accessible or need be be obtained by a device. Data can be processed, stored and used in custom designed algorithms to aid in problem identification. Various data processing techniques such as statistical analysis, graphical display and model fitting can be used to correlate the data with a problem statement.
Use data analytics and automation to solve issues at hand optimally and with full control.
Processing of data into information can be used not only to identify problems, but also to find solutions to these problems by means of indirect intervention (alerts, reports, suggestions) or direct intervention such (automation and control).
Indirect intervention usually involves a human element by means of feedback information such as alerts, alarms, reports or suggestions. Human intervention is then triggered by this information. Typical systems that utilise indirect intervention are businesses, medical industry, factories, agricultural and mining operations. Indirect intervention give assistance to decision making and the full responsibility of the actions still lies with the human element.
Direct intervention removes the human element in the decision making process and gives full control of the execution of the final actions. This can create an unbiased control mechanism whereby emotions, reaction time and human error is removed in the decision making and execution process. Typical systems that utilise direct intervention are more of a lower level environment such as specific tasks in a process or system. Some examples:
- control of a piece of equipment such as a central air conditioning for a shopping mall or office building whereby energy utilization is optimized while still achieving the overall goal.
- Procurement management in a business can be automated by means of statistical analysis and optimized to execute on time and without human error or emotions.
- Controlling environmental variables in a hydroponic farm such as humidity, temperature, carbon dioxide concentration, water temperature, water pH and water conductivity to optimize for produce yield.
Simulate a System
Create a model and simulate changes or monitor the effects of disturbances.
Simulations can be custom built to fit each problem scenario. The goal of simulations are to test the effect of changes or do sensitivity analysis on a system. This is useful as it minimizes risks involved and keep costs low. Simulations can also be used to train personnel on a system's current or future behaviour.
Monitor a System
Monitor and display a system's information online in a user friendly manner.
Information need to be displayed in a human friendly manner that can easily be understood. Remote viewing of the information can be done to ensure 24 hour access to historical and real-time information.
Some examples of how information can be displayed:
- trends on graphs from historical data
- events that occurred by means of logs or counters
- progress on a task or goal can be tracked and displayed using various graphical methods
- current real time system status and information can be displayed.
- Suggestions can be event based or automatically be generated based on system information
Control a system or process remotely
Issue commands to control a system remotely or make changes to the current operating principle of the system.
Remote control offers a great advantage to off-site operators, technicians, engineers or business owners.
Create, train and use artificial neural networks in complex decision making environments with un-biased outcomes.
Artificial Intelligence can be used for certain complex tasks by executing extremely fast decision making algorithms or predictions. The fast acting capability is due to the fact that a neural network was pre-trained with large datasets to ensure a high accuracy of execution. Obtaining and storing data is therefore critical for training of such devices.
Optimize a Process
With a system being monitored and controlled, optimization goals and algorithms can be introduced.
A process can be optimized to minimize loss or downtime, maximize energy efficiency or improve in performance. In order to achieve process optimization, a baseline of a process' current performance need to be achieved by means of obtaining key performance data.
Simulations can aid in optimizing a process by means of iterative changes and performance reviews. Automation and control can be implemented to achieve an optimization goal on a process.
Some examples of process optimizations:
- Energy consumption analytics, load balancing and energy integration for factories.
- Financial analytics of a business with high level, live reporting to executive members of a business to aid in daily/weekly/monthly decision making.
- Real time environmental conditions monitoring and control on a hydroponic farm to ensure optimal growth rate and healthy produce with repeatability.
- Reducing manufacturing plant emissions and effluents during production or reducing downtime by means of optimized process control.
Continuously monitor a system's condition, predict failure and recommend corrective actions.
Reduce human error by means of transferring the responsibility of monitoring operations on machinery to a dedicated online condition monitoring platform. Machinery can be monitored continuously by means of various inputs such as transmitters, visual inputs and events. This data can be used as input to a condition monitoring device that predicts a components failure and can recommend corrective actions.