Building management system (BMS) also known as building automation system (BAS) refers to a computer-based control system that needs to be installed within buildings to monitor and regulate the building's electrical and mechanical equipment such as power system, lighting, and ventilation to confirm sustainability.
The building management system (BMS) is an overarching control system that is responsible for the automatic regulation and control of non-GMP facility subsystems, maintaining predefined parameters (or set points) and the control of their functionality. The major aim of the BMS is to guarantee the safety of facility operation, while also monitoring and optimizing the use and efficiency of its supervised subsystems to allow more efficient operation.
SCADA (supervisory control and data acquisition) is a category of software applications for controlling industrial processes, which is the gathering of data in real time from remote locations in order to control equipment and conditions. SCADA provides organizations with the tools needed to make and deploy data-driven decisions regarding their industrial processes.
One of the most commonly used types of industrial control system, SCADA can be used to manage almost any type of industrial process.
SCADA systems include hardware and software components. The hardware gathers and feeds data into field controller systems, which forward the data to other systems that process and present it to a human-machine interface (HMI) in a timely manner. SCADA systems also record and log all events for reporting process status and issues.
OEE (Overall Equipment Effectiveness) is the gold standard for measuring manufacturing productivity. Simply put – it identifies the percentage of manufacturing time that is truly productive. An OEE score of 100% means you are manufacturing only Good Parts, as fast as possible, with no Stop Time. In the language of OEE that means 100% Quality (only Good Parts), 100% Performance (as fast as possible), and 100% Availability (no Stop Time).
Measuring OEE is a manufacturing best practice. By measuring OEE and the underlying losses, you will gain important insights on how to systematically improve your manufacturing process. OEE is the single best metric for identifying losses, benchmarking progress, and improving the productivity of manufacturing equipment (i.e., eliminating waste).
Industrial plants operating continuously and with a high level of constant emissions are often required to install a permanent, fixed, continuous emissions monitoring system (CEMS). CEMs must have the required performance for the gases present in the stack – correct ranges, response times and accuracy of measurement – as well as have a reliable uptime and operation life so that the plant can continue to run.
In order to monitor the emissions, increasing instrumental techniques are the preferred method and certainly where a continuous emissions monitor is needed this can only be from on-line analysers. Protea has developed our range of gas analyser to operate within the stringent levels of performance needed in order for industry to monitor the emissions as required by the regulations. This includes the need for certification or accreditation of the analysers against performance requirement.
Energy management systems (EMS) are automation systems that collect energy measurement data from the field and making it available to users through graphics, online monitoring tools, and energy quality analyzers, thus enabling the management of energy resources.
An energy management system (EMS) supports the reliable functionality of the microgrid, maximizes the penetration of renewable energy, and optimizes the cost and economic efficiency in the associated electricity market. To achieve such technoeconomic and environmental objectives, EMSs have to solve dispatch optimization problems for the available production and storage capacity, given market data, real-time state, and operational constraints of the microgrid, production, and consumption forecasting information.
Predictive maintenance is a technique that uses data analysis tools and techniques to detect anomalies in your operation and possible defects in equipment and processes so you can fix them before they result in failure.
Ideally, predictive maintenance allows the maintenance frequency to be as low as possible to prevent unplanned reactive maintenance, without incurring costs associated with doing too much preventive maintenance
