Saturday, May 04th

Last update03:25:23 PM GMT

You are here: Thought Leadership Articles By AIA From measurement, control to asset management: pathway for the water industry

Primary Members

  • adroit.jpg
  • autosys 2.jpg
  • axcent.jpg
  • bnr.jpg
  • chemtrol.jpg
  • cotmac.jpg
  • enconsystem.jpg
  • festo.jpg
  • gefran.jpg
  • hitech.jpg
  • ifm.jpg
  • lnt.jpg
  • mitsubishi.jpg
  • mvr.jpg
  • nish.jpg
  • omron.jpg
  • pari.jpg
  • Parker logo-01.jpg
  • pnf.jpg
  • precise-automation-and-control.jpg
  • rockwellautomation_pantone.jpg
  • schamersal.jpg
  • servilinks.jpg
  • siemens_logo_petrol_rgb.jpg
  • smc.jpg
  • spectrum2.png
  • titan.jpg
  • toshbro.jpg
  • turk.jpg
  • vsm.jpg
  • weildmuller.jpg
From measurement, control to asset management: pathway for the water industry Print Email
Written by AIA   

The water treatment plant in Dego, Savona, Italy is part of the CIRA consortium which operates within the consortium member municipalities of Cairo Montenotte, Carcare, Dego, Altare and the municipalities of Cosseria, Plodio, Bormida, Mallare and Pallare, spread over 200 sq.km. The plant caters for a total of about 50,000 equivalent residents, also treating wastewater coming from industrial sites, with an annual output of more than three million cubic meters of treated wastewater and a production of 1,400 tons of sludge obtained from the anaerobic digestion process.

Overview of the Water Treatment Plant in Dego, Savona, Italy

Operation of the city and industrial sewage treatment plant is based on the activated sludge biological process, which is broken down into two distinct lines: one for sewage treatment, the other for sludge treatment.

All process compartments of the water treatment plant are currently operating, The water treatment plant is entirely equipped with intelligent devices with Profibus technology, which include in-line analysis measurements, ultrasound and magnetic flow rate measurements, ultrasound and water head level measurements, temperature measurements, automatic samplers, etc.

The main functions of the system are connected to the control of the intake works lifting system, to the control of motor-operated by-pass management valves, to local station management, to blower regulation via inverter and to the control and management of instruments and motors by acquiring the measured val ues, diagnostic parameters and configurations.

A supervising and asset management system has been developed on the basis of this architecture, which can be used both at the water treatment plant and from remote stations through web access.

Asset Management System:

In addition to the automation and supervising system the water treatment plant has also been equipped with an asset management system. The installed system is based on the FDT/DTM software technology which constitutes a multi-vendor standard and ensures openness and performance with the following provisions:

  • Sensor setup and configuration saving
  • Download of source configuration if the device is replaced
  • Technical documentation and maintenance management
  • On-line diagnostic activity execution

Download via web of the instrument production certificates so as to directly find spare parts, any substitutes of obsolete instruments, certificates and technical documentation in general

Autonomous management of engineering and purchase via e-shop.

Basic Requirements:

The circulation of information is the key to everything. The actual challenge is to create open and high-performance architectures. An architecture declared open is actually multi-vendor at all levels and that the customers can actually select the most important information to manage their process efficiently.

The ability to select the data that actually contributes to giving added value to management among a large quantity of data available is all important. We ask ourselves three simple questions:
1. Do we know exactly which assets of our plant are critical and how to maintain them efficiently?
2. Are we sure that the current operational maintenance choices minimize the risk of unscheduled downtime?
3. Are we sure that the current preventive maintenance activities are the most effective in relation to their cost?

Digital Protocols:

The advent of digital protocols in process signal transmission has revolutionized information processing modalities for plant management and automation. First of all, consider the improvement in terms of accuracy of the processed signal: a traditional 4.20 mA signal requires multiple analog/digital conversions that deteriorate the signal; a native digital signal is processed and transmitted as it is, maintaining high quality resolution characteristics.

Furthermore, a 4..20 mA signal brings one single piece of information connected to the trend of the physical value that represents it in a directly proportional way; instead, a digital signal can bring multiple pieces of information depending on the coding that defines the used protocol; for example, not only does the main measured value transit on the backbone, but so does other process information as well as the diagnostic status of the device that makes the measurement. The huge increase in efficiency due to this macroscopic difference is already apparent.

Another revolution deriving from the nature of digital communication is signal Bi-directionality: the same backbone allows data not only to be acquired but also to be sent, thus allowing the desired control actions to be performed directly and effectively.

From the installation viewpoint digital innovation has allowed cabling structures to be simplified and electrical and instrumental boards to be considerably reduced, thus resulting in an overall saving of approximately 15%.

Information for better management:

In a system like the one analyzed the information content is vast and making all the information available does not automatically mean optimum management.

Only an exhaustive study of the plant allows us to fully understand which instruments, and consequently which information among that available, can effectively contribute to optimum management.

In fact, optimizing management costs does not have one single solution since there are many variables at stake, such as plant layout, the type of sensors and actuators installed and the management logics. Below is an example of a study carried out for the water treatment plant in Dego, which points out that only a part of all the devices to be managed is actually at high risk, and only half of them needs specific maintenance.

 

Asset Risk Analysis - Example:

Cost optimization can therefore be achieved by controlling the critical "areas", which makes a direct impact on maintenance budget control, spare part warehouse control, decreasing plant downtime risks, technological adjustment of the plants, plant standardization and maintenance activity planning.

 

 

Conclusion:

According to studies, a Plant Asset Management system can decrease the costs associated with maintenance procedures by 30%, that is to say increase the efficiency of the resources available; besides the macroscopic reductions in plant downtime costs, which arise due to insufficient or improperly targeted maintenance activity.

Among all the installed components, the field components were the most critical ones from a maintenance point of view, since there were higher percentages of sensors, remote I/O, positioners and actuators, which were also broken up and scattered over a wide area; such devices are typically subject to greater wear and require periodic maintenance since they are associated with plant safety.

What has been implemented is actually a system that we call "Life Cycle Management", whose purpose is to enable the user in managing the entire life cycle of the plant. Now that the first year of management has passed, the user can start reaching conclusions and make the first assessments.

We have seen how much information can come from the field thanks to modern technologies and "real" system openness. Wastewater industry can migrate from cost saving during installation and startup to cost saving during operation with improved functionalities.

- Casiraghi, Shrikant Kulkarni,
- Provesi, A. Icardi