Engineering

I. INTRODUCTION 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 desired outcomes · 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 operations. Scope to establish a well alarm management system should be: · Enable and empower operating teams to manage their plant. · Maximize the safety avoiding hazardous situations. · Minimize environmental impact avoiding release in ambient. · Push the processes to their optimal limits. · Avoid equipment failure decreasing maintenance costs. 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, domestic applications. Raw materials and intermediates as well the finished products sometime represent dangerous or toxic materials. 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 production. Each alarm signal is also recorded on a printer, so in case of alarms proliferation a lot of indecipherable paper is generated. The process of an alarm management on the ABB control computers (Conductors) includes the following steps: 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 alarm. 4. The control room operator recall the graphic (plant) where the tag alarming has been configured. 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 paragraph. 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 equipment. 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 consol): 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 console) 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 console): 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 the console): Bad quality signals arriving on DCS. 5. ALARM PRIORITY = 16 (fuchsia signal on the console): Return to normal, second/third levels alarms, high deviations, etc. 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 1 area. Unit definition: N° of alarms generated by DCS per 10 minutes. Defect Definition: N° of alarms generated by DCS > 10 alarms per 10 minutes. Operators Target: N° of alarms generated by DCS