Operational Excellence Methods and Tools

The discussion continued. Bill emphasized that the purpose of the company's operational excellence program was to make Proclndustries more agile in its operations and more profitable as a business to ensure its long-term survival in a competitive marketplace. "The key is to simplify our communications about the basic metrics everyone uses," Bill said. "The digital data infrastructure system will be the refinery's window into these basic metrics."

"To embed knowledge in a modern digital data infrastructure system, we need to use templates," said Peter. Templates set parameters for process analysis in the refinery. And the insights can be applied to improve process performance locally at the refinery level and strategically at the enterprise level.

Continuous improvement, they all agreed, required a structured approach with seven key elements of real-time performance monitoring and control systems:

  • 1. Agreement on critical metrics for production monitoring, product quality, assets, process inputs, and environmental and safety conditions
  • 2. A method for measuring performance
  • 3. Corrective action planning
  • 4. Clarification of roles and responsibilities
  • 5. Regular process reports and review meetings
  • 6. Recognition of progress and achievement
  • 7. Collaboration among different roles at the refinery, including production planning, process, engineering/maintenance, and management

It is particularly important for the company to define measurement methods and continuously monitor them (Bascur and Kennedy 1995).

Workflow Management

Peter next explained the importance of workflow management in continuous-improvement programs. "We can improve company performance by combining workflow management with the analytic capabilities of the digital data infrastructure system," he said. "Once we set up the system to collect data and analyze performance, the workflow will be initiated by the digital data system."

Currently, Proclndustries can track transactions and dollars spent in the refinery, but their existing systems were unable to analyze operating problems that needed to be addressed. Although some of his colleagues were using an enterprise resource planning (ERP) system, Peter wanted to educate them about the benefits of the digital data infrastructure system. "The function of a real-time digital data infrastructure is to support continuous improvement," Peter said. "This is quite different than the ERP system. With the EIDI, we can identify, analyze, and correct operating problems."

Peter showed an illustration that he said was an adaptation of the traditional Define, Measure, Analyze, Improve, and Control (DMAIC) loop for real-time process improvement (Figure 2.3): "To achieve true change, we need two loops. One is tactical and one is strategic. Metaphorically speaking, the two loops are how the human brain works. The left side does all the

FIGURE 2.3

Real-time continuous improvement and innovation loops.

hunting and linear things. The right side integrates our values to plan and look for ways to get out of trouble if a problem arises."

The figure also shows the post-analysis and improvement workflow activities by the support teams. Together, these series of actions reduce the time required to convert data into answers that support continuous improvement for the organization. Operational continuous improvement is based on two separate loops:

  • 1. Are we on target? (the system monitoring loop)
  • 2. Are we satisfied? (the continuous-improvement and innovations [CII] loop)

The First Loop: Are We on Target?

For a typical plant, the first loop (Figure 2.3 left side) compares the plant unit targets with the current unit metrics daily schedule and uses realtime analytics to generate events that mark the start and end time of operational events. These events are defined by metrics that show activity outside statistical control limits. The first loop is a comparison between the current metrics and target levels expressed at the desired degree of detail. This loop can be performed by the EIDI to catch variances outside the normal targets.

Peter went on: "A fundamental differentiator of a real-time digital data infrastructure or EIDI is that data can constantly be reused as a time-derived variable. We do not use a static variable or a snapshot variable for analysis. A time-derived variable is a critical concept in the way the digital data infrastructure supports our analysis because the time-derived variable enables us to determine conditions in the production process at a specific moment in time. We observe when these events begin and when they end."

Imagine a pump breaking down. The sensors can detect an abnormal activity in the production process and trigger an event through the digital data infrastructure system. Once the digital data infrastructure system triggers an event, the system generates a workflow for the team to resolve the issue and to assign a root cause. Therefore, the digital data infrastructure system is connecting the people in charge of a resolution to the metrics of an unusual event. This triggered event can also send a notification via email, text, or phone call to those in the workflow. This triggered event can be escalated to other teams if so desired.

Peter cited three potential examples:

1. The plant manager, Tom Jordan, receives a notification when the crude unit has been operating below production targets for more than 30 minutes.

  • 2. The process engineer, Alex Moretti, is notified if the crude unit starts moving into "trouble" mode.
  • 3. Chen Wang, the laboratory manager, receives a notification if there is a large variation in the production process.

The Second Loop: Are We Satisfied?

Peter said the second loop (Figure 2.3 right side)—Are we satisfied?—is about process improvement and innovation. This is a people-centric loop.

In this part of the process, Peter explained, people use their time differently than Proclndustries staff members have done in the past. Instead of fighting crises or doing busy work like gathering data, they are defining better performance metrics using process models. The loop provides the opportunity to improve a process, to solve a current problem. It is here that people need to question the status quo. Is there something else that we could do to improve outcomes? Ultimately, Peter explained, work on the "Are we satisfied?" loop helps improve the bottom line.

Peter said the "Are we satisfied?" loop is handled by support teams (engineering, maintenance, production, quality, environmental, and safety). These teams act as guides to people in the trenches. They are the process, quality, or maintenance engineers who continuously evaluate long-term performance trends of the operations, instead of receiving incomplete and outdated reports, as in the past. These teams are in charge of recommending suggestions for changes based on their insights. With the EIDI, teams can analyze data at the desired degree of detail and see problems and opportunities that had previously not been able to be detected by the operating teams. For example, the EIDI makes it possible to calculate electricity consumption during an equipment problem. This enables workers to analyze the problem in a finer degree of detail than in the past, and to quantify benefits (such as reduced electricity costs) for improving the situation.

Peter explained that the two loops provide a strategy for process improvement (Table 2.1). The first loop focuses on the day-to-day operations and checks whether they are on target. The second loop seeks improvement strategies based on the belief that performance can always get better. Together, these two loops embody continuous-improvement methodology:

  • 1. Provide operators with consistent quality data and performance indices by checking mass balances, energy balances, and correct flow rates for temperature, pressure, and in some circumstances, chemical composition or specific gravity.
  • 2. Display key metrics for refinery personnel that raise their awareness of overall refinery performance (production, energy, asset, safety, and environmental conditions). These displays, on monitors in areas where people gather, can augment traditional daily reports.
  • 3. Continuously evaluate overall refinery performance that impacts profitability.
  • 4. Quantify a refinery-wide penalty cost when metrics fall below performance targets.
  • 5. Monitor performance of all critical equipment to improve maintenance planning and reduce equipment disruptions, thus enhancing overall refinery availability.

TABLE 2.1

Target and Improvement Loops: Analytic Tools and Bottom-Line Benefits

  • 1. Target or control monitoring loop: Are we on target?
  • • Provide operations with cause-and-effect diagrams.
  • • Provide visibility into operating processes through email notifications, online video conferencing with engineer-mentors, and other enablers.
  • • Organize data and documents to find root causes.
  • • Enable teams to interpret results using tools such as fishbone diagrams.
  • • Review process, production, and quality variances.
  • • Provide energy, water, and utilities connected to local smart grid activities.
  • • Provide safety and environmental notifications.
  • • Improve operator morale through process ownership.
  • • Use Pareto analysis to evaluate the most important root causes to eliminate.
  • • Use process matrix analysis to identify opportunities for improvement.

2. Improvement and innovation loop: Are we satisfied with the current

performance? Review variances and collaborate with planning and economics personnel

to modify targets and business rules, where applicable.

  • • Identify unnecessary energy costs and implement utility process improvements.
  • • Identify operational losses and profits.
  • • Identify conditioned-based equipment monitoring strategies.
  • • Evaluate mechanical integrity and economic risks.
  • • Use business intelligence tools to visualize data as actionable information.
  • • Improve employee satisfaction by empowering them to create new solutions with the right data and visualization tools.
  • • Drastically reduce the time needed to resolve problems or identify business opportunities.
  • • Define short- and long-term process improvement plans and provide proposals to management.
 
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