A DCS (Distributed Control System) can generate a very
high number of alarms and events. Control engineers or
control room operators often cannot deal effectively with
this number of alarms.
When alarms proliferate their collective value as a tool
for diagnosis and preventing problems declines so the
overall effectiveness of the alarms system suffers with
risk of incidents and/or relevant economics losses.
Today for many advanced control systems it is becoming
essential to have a system to identify and eliminate all
nuisance alarms generated by a DCS, a system that allow
to manage the alarms and to enhance its reliability.
One useful method for alarm improvement activity is Six-
Sigma methodology based on teamwork. The Six-Sigma
approach includes the following phases:
?· Define: Identify opportunities and Project scope
?· Measure: Analyze current process and define
?· Analyze: ID root causes and proposed solutions
?· Improve: Prioritize, plan & test proposed
solutions. Refine and implement solutions
?· Control: Measure progress and hold the gains.
Recognize team & communicate results.
Statistical tools provided by Six-Sigma methodology and
a suitable system to detect all nuisance alarms generated
by DCS represent a useful guide and support to fix
existing alarm system and to establish a well managed
system that provides to the process controllers with the
appropriate information in a timely manner. In this way it
would be possible to easily identify cause of abnormal
process conditions and restore the plant to its normal
Scope to establish a well alarm management system
?· Enable and empower operating teams to manage
?· Maximize the safety avoiding hazardous
?· Minimize environmental impact avoiding
release in ambient.
?· Push the processes to their optimal limits.
?· Avoid equipment failure decreasing
II The Termoli Momentive Performance
Materials Specialties Plant.
A. Process Description.
Momentive Performance Materials Termoli (Molise-
Italy) plant produces chemical specialties like Silanes
Orgafunctional Liquid, Urethane Additives Copolymers
and Silicone Fluids Antifoams and Emulsions. All these
products are based on Silicon chemistry.
Final applications of these specialties are in the
automotive, personal care, healthcare, electronics,
construction, textile and leathers, pulp and paper,
Raw materials and intermediates as well the finished
products sometime represent dangerous or toxic
Main equipment used in the several production
(continuous and batch) processes are reactors, pumps,
heat exchangers, distillation columns working under high
vacuum, incinerator unit, boilers and waste water
treatment system. So the control system of the different
processes must be very effective, efficient and reliable to
avoid the risk of incidents, emissions out of the law limits
and quality problems of finished products that will create
problems in final applications.
B. Automation system description.
Termoli DCS system, provided by ABB, includes a
control network connected to 15 Process Control Units
(PCU). The signals from/to the production units (field)
are governed by these PCU??™s. On the same loop operator
interface stations are connected. These stations include 12
computers, called Conductors, installed in the control
room governed by control room operators assigned to the
process control of the production units. Other interfaces
connected to the same loop are the EWS (Engineering
Work Station called Composer and used for programming
the control logics), LPM (Loop Performance
Management) and EAM (Enhanced Alarm Management).
C. Pre-project situation
About 6000 tags are defined on Termoli DCS, either
digital tags or analog tags. The type of analog tags could
be temperature, pressure, level, flow rate, pH, electrical
input. The type of digital tags could be ON/OFF valve,
ON/OFF switches, interlocks, etc??¦
For each of these tags an alarm is defined. An alarm is
generated by when the values of process variables
detected by the tags exceed the alarm limits in case of
analog tags, or by when the tag change its state in case of
digital tags. In this case a signal is sent on the consoles in
the control room advising by a sound the operators about
the process upset.
If the alarm limits are not well defined or configured we
can have way too many signals sounding continuously on
the consoles of the control room so the operator is unable
to track the status of the process, with risk of incident,
equipment failure, process out of control and out of spec
Each alarm signal is also recorded on a printer, so in
case of alarms proliferation a lot of indecipherable paper
The process of an alarm management on the ABB
control computers (Conductors) includes the following
1. An alarm sounds on DCS computer in the
alarm panel due to a process upset.
2. The control room operator silences the alarm.
3. The control room operator acknowledges the
4. The control room operator recall the graphic
(plant) where the tag alarming has been
5. The control room operator takes the necessary
actions to restore normal process conditions.
6. A new alarm will be generated by DCS when
the tag returns to normal.
If the alarms proliferate it is evident that this process
cannot be applied in the right way.
D. Problem statement
A large number of overall system alarms are more
intrusive than individual process alarms and arguably of
lesser value to operators; thus they are unable to track the
state of the processes and production status.
The number of alarms generated by DCS during a
certain period of time can be measured by EAM
(Enhanced Alarms Management).
EAM is a powerful software tool developed by ABB by
a devoted team in Genova, first of all, to replace the
alarms printing system; it also provides additional
functions for intelligent alarms monitoring, alarms
archiving, off-line alarms and statistical event analysis. A
detailed description of this software is in the following
III Project Scope and Development
A. The DMAIC approach
A Six-Sigma study started in May 2008 to monitor the
alarms generated by Termoli Plant DCS. Using the EAM
tools and DMAIC approach, for 31 days all the alarms
have been collected and analyzed statistically to establish
the process baseline.
Particularly the team put the attention on the Silane-1
production area that includes critical processes and
First of all the team introduced on DCS a site Specific
Alarm Philosophy as (work practice) based upon alarm
levels priority reduction from 16 to 5 as following:
1. ALARM PRIORITY = 1 (red signal on the
Critical COP/NEL Alarm – Critical Operating
Parameter (COP) at the never exceed limit (NEL)
requires immediate, predetermined action as specified
in COP documentation or an alarm identified in an
Operational Safety Standard that is needed to control a
risk associated with a Major Process Hazard. These
alarms are associated with a critical instrument.
2. ALARM PRIORITY = 2 (yellow signal on the
Serious Alarm – An alarm that warns of a condition
that if not corrected may lead to personal injury,
equipment damage, environmental pollution or
substantial economic penalties.
3. ALARM PRIORITY = 3 (green signal on the
Operator Guide Alarm – An alarm that warns of a nonoptimal
process condition, and directs the operator to
look in a certain area of the process.
4. ALARM PRIORITY = 8 (light blue signal on
Bad quality signals arriving on DCS.
5. ALARM PRIORITY = 16 (fuchsia signal on the
Return to normal, second/third levels alarms, high
By applying the Six-Sigma methodology we then defined
the Performance Standards of the process as following:
Project Y: number of alarms generated by DCS.
Project y: number of alarms generated by DCS in Silane
Unit definition: N?° of alarms generated by DCS per 10
Defect Definition: N?° of alarms generated by DCS > 10
alarms per 10 minutes.
Operators Target: N?° of alarms generated by DCS
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