Multi-Variable Predictive Control

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Key areas for Operational Excellence Transformation

Operational Excellence Transformation is Yokogawa and KBC’s co-innovated portfolio of solutions and services.We provides comprehensive solutions for business automation in all four areas using consulting and digital technology.

 

Asset Operations and Optimization

Asset Operation and Optimization deals with realizing the potential of physical assets by pushing throughput and maximizing the production of the highest-value products, while minimizing variable costs, such as energy. It ensures small and large capital expenditure projects are delivered on time and on budget, to achieve growth and meet environment requirements. Through these competencies, it will be possible for companies to take full advantage of their physical assets. Yokogawa’s Asset Operation and Optimization solution leverages industry-leading technology to generate precise operating information to increase operator insight, ultimately leading to improved performance and profitability.

Key Operational Competencies in Asset Operations and Optimization

  • Asset Strategy: Define the requirements of plant capacity, operability and production to align with corporate strategy.
  • Asset Improvement: Improve plant profitability by expanding plant operating window and/or adding/modifying plants
  • Asset Optimization: Optimize the plant by enabling shift teams to execute activities as per plan and within operating window boundaries
  • Asset Operations and Process Control: Operate the plant by enabling shift teams to implement plans effectively,stabilize process control beneficially and manage abnormal situations
  • Capital Projects Delivery: Screen options, engineer and deliver capital projects that are cost-effective, timely and fit for purpose 

With our track record of providing project execution and thorough lifecycle services and KBC consulting, our customers can obtain practical and deep insights on maximizing their physical assets. Together, we aim to contribute and actualize improvements not only for profitability, but also for overall safety, operability and reliability.


·Supply Chain Optimization
- Optimize management of supply, whether oil in the ground or feedstocks for a refinery or chemical asset, in light of product market demands. This provides operators with the agility to take full advantage of market conditions.
·Operational Risk Management 
- Reliably control safety, health and environmental risk at a personal and process level. This assures the robustness required to avoid catastrophic losses.
·Asset Management and Integrity
- Confidently ensure asset reliability and availability, whilst controlling maintenance costs. This assures the asset always meets expectations and is always available to capitalize on short term market opportunities.


Multi-Variable Predictive Control

A product of Yokogawa's alliance with Shell, Exasmoc was jointly developed - and is in continual development - to meet the demanding necessities of industry. Designed for use by a process engineer in a process plant with minimal advanced control theory knowledge, Exasmoc is a multi-variable control APC suite built by the user for the user.

What better way to improve business and operational performance than to implement Exasmoc?

Exasmoc image

Exasmoc image

A product of Yokogawa's alliance with Shell, Exasmoc was jointly developed - and is in continual development - to meet the demanding necessities of industry.

Designed for use by a process engineer in a process plant with minimal advanced control theory knowledge, Exasmoc is a multi-variable control APC suite built by the user for the user.

Key Characteristics of Exasmoc

  • Easy-to-use design and simulation kit (off-line)
  • Scenario based simulation tool that encompasses all possible plant situations - in short, a "real simulation tool"
  • Highest uptime in industry
  • Use of unmeasured disturbance models, includes a-priori process know-how resulting in high robustness
  • Grey box models to facilitate easier debugging of control responses, also enables a higher confidence level
  • Easy embedding in DCS
  • Easy integration with other plant information networks

Exasmoc Shimulation PlotExasmoc is a multi-variable control suite that is able to compute sequences of manipulated variable adjustments for the purpose of optimizing future plant behavior with the use of models to evaluate the effects of control strategies.

Able to deal with explicit constraints, Exasmoc goes in pursuit for an ideal strategy for one control step, and then re-evaluates its strategy based on the plant's response. It also simultaneously copes with amplitude constraints on inputs, outputs, and states.

Having reduced oscillations in the controlled variables, Exasmoc allows the operator to work the plant to its optimum, raising the plant's profitable operating point without violating quality specification.

Advanced Features of Exasmoc

  • A unique, unmeasured disturbance model that can be updated, filters out noise to bring about more robust control, and also includes an Observer that permits the introduction of intermediate variables for better smoother control
  • Optimization to derive greater economic benefits with extra degrees of freedom is available
  • A separate disturbance model
  • Use of long control horizon for processes with long dead times to minimize disturbance
  • On-line tuning
  • Tried, tested, and proven in more than 400 applications worldwide in different process units
  • Adjudged as "Controller with Highest Uptime in Industry" by autonomous body Solomon Associates

What better way to improve business and operational performance than to implement Exasmoc?

Exasmoc logo

AIDA Advanced Identification and Data Analysis
AIDA is a complementary identification package that goes together with Exasmoc. A fundamental requirement for an ideal predictive controller is the "model". A user-friendly package, AIDA helps to constantly engineer the model.

Key Features of AIDA

  • Model estimation via constrained or non-linear optimization
  • Model types include first order with delay; second order with delay and ramp models
  • Prediction horizon concept to capture long-term dynamics in modeling a process
  • Unmeasured disturbance and noise model
  • Correlation analysis of residuals to judge quality of data and models
  • Able to handle multiple data sets
  • Cross-validation - using a model from one data set to predict the behavior of another data set.

Coupled with a user-friendly interface, the mentioned features make AIDA an ideal tool on which the model can be built.

AIDA Model display

Overview:
  • Provided a better way to transfer its manufacturing know-how to the next generation
  • Reduced energy consumption and operator workload by implementing Advanced Process Control (APC) and Advanced Operator Assistance (AOA)
Industrie:
Overview:
  • HMEL selected an integrated solution from Yokogawa
  • Yokogawa India oversaw and implemented the engineering, installation, and commissioning of the refinery
Overview:

A Malaysian Gas Processing and Transmission Company a subsidiary of the national oil & gas major, plays a prominent role in the gas business value chain. The company operates as a throughput service company providing the services of processing and transmission of gas to the power generation sectors and various customers. 

Industrie:
Overview:
  • Operational Excellence by Asset Maximization, Utilizing Yokogawa's DCS, SIS, Analyzers, and Field Instruments.
  • The CENTUM VP PCS and ProSafe-RS SIS were integrated using the same engineering environment.
  • Nearly 60 gas chromatographs and a large number of other types of analyzers in several analyzer houses.
Industrie:
Overview:
  • Kaneka Corporation has urgently needed to implement countermeasures that would reduce this facility's energy costs.
  • Optimization of control strategy helps BTG plant save energy and operate more efficiently.
Industrie:
Yokogawa Technical Report
Overview:

In 2000, we formed a technical tie-up with Shell Global Solutions (SGSI) to enter the advanced process control and optimization solution business. At the same time, we started marketing a solution based package comprising an Exasmoc multi-variable model-based predictive control function, an Exarqe property estimation function, an Exaspot online real-time optimizer and an MD control monitor & diagnosis function by taking full advantage of the SGSI advanced control and optimization technology (APC&O).

Overview:

Yokogawa has formed an alliance with Shell Global Solutions International B.V. (SGSI) for advanced process control and has been jointly developing related products since then. As part of this collaborative work, we commercialized the Exasmoc multivariable model predictive control package and the Exarqe robust quality estimator package in 2000, which are used to control DCS and PLC systems based on SGSI's multivariable predictive control and quality estimation algorithms—namely, SMOC (Shell Multivariable Optimizing Controller) and RQE (Robust Quality Estimator).

Yokogawa Technical Report
Overview:

In 1999, Yokogawa Electric Corporation formed an alliance with Shell Global Solutions International B.V. (SGSI) in Advanced Process Control (APC), and both companies have since jointly developed products. This alliance successfully combined SGSI's experience gained through more than 800 projects in more than 30 years and Yokogawa's great deal of experience with the process control market, and strengthened the scheme to provide the APC technology.

Yokogawa Technical Report
Overview:

For a coal fired power generation plant (hereafter referred to as "BTG facilities," in which "BTG" stands for boiler, steam turbine, and generator) supplying power to a large-scale production plant, the CO2 emissions from such facilities are a critical issue today.

Overview:

Due to emerging competitors from the rapidly growing countries such as India and China and the global economic downturn triggered by the Lehman shock, many companies in the process industries are struggling to survive the severe global competition.

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