Princeps
Overview
HQ Location
France
|
Year Founded
2000
|
Company Type
Private
|
Revenue
$10-100m
|
Employees
11 - 50
|
Website
|
Company Description
PRINCEPS is an R&D intensive company. We have conducted a significant R&D effort in cooperation with academic organisations in Europe (PRINCEPS is the initiator and coordinator of several EU funded projects).
Strong with more than 15 years field experience through planning and scheduling projects worldwide, we have developed an innovative software suite which introduces a new paradigm in this domain.
Most importantly, PRINCEPS has developed over the years, a strong working partnership with its clients, which is at the foundation of its customer oriented culture.
The Oil industry is one of the pioneers in the widespread adoption of optimization techniques. The term “Refinery optimization” has consequently evolved to become a multi-faceted concept.
At an abstract level, refinery optimization is about getting the most from the existing assets; by extension, it can also refer to the most profitable investments in new equipment or new assets. This first distinction gives rise to 2 horizons of application to refinery optimization: long term, structural optimization, and short term operations optimization. Moreover, operations management itself can be addressed in a variety of ways, depending on whether the approach taken to refinery optimization is bottom-up, or top-down:
The top-down approach is based on hierarchical optimization: the refinery optimization problem is addressed as a succession of optimization problems of different time magnitudes and granularities. The first problem is a mid-term planning problem and is concerned with the refinery as a whole and a time frame of one to several months. Subsequently, the time frame is subdivided into finer time intervals. At the lowest level, the theoretical goal is to achieve operations scheduling on a day to day basis.
The bottom-up approach is one that starts with local problems and tries to aggregate them into a consistent solution at the refinery level.
In contrast to traditional bottom-up approaches – which attempt to build an overall solution by aggregating local solutions – we start by achieving a feasible, “good quality” overall solution using our smart simulation engine. Then, guided by the consistent overall solution, we seek to optimize local operational challenges.
Our innovative approach to refinery optimization takes account of 2 crucial facts:
- Day-to-day operations are subject to uncertainty,
- Regardless of the inherent formal difficulty of achieving an overall refinery schedule optimization, an overall optimized schedule is of little use.
This is simply because an overall solution achieved that way is inherently unstable: the slightest change or unforeseen event means that the whole schedule must be rebuilt. And given the huge amount of inertia in such a large system, any sudden change of trajectory consumes an equally huge amount of energy.
Under this pragmatic perspective, refinery optimization appears as the search for a maintainable globally feasible, locally optimized schedule. Optimization is applied to sub-systems where a high economic impact is achievable.
Strong with more than 15 years field experience through planning and scheduling projects worldwide, we have developed an innovative software suite which introduces a new paradigm in this domain.
Most importantly, PRINCEPS has developed over the years, a strong working partnership with its clients, which is at the foundation of its customer oriented culture.
The Oil industry is one of the pioneers in the widespread adoption of optimization techniques. The term “Refinery optimization” has consequently evolved to become a multi-faceted concept.
At an abstract level, refinery optimization is about getting the most from the existing assets; by extension, it can also refer to the most profitable investments in new equipment or new assets. This first distinction gives rise to 2 horizons of application to refinery optimization: long term, structural optimization, and short term operations optimization. Moreover, operations management itself can be addressed in a variety of ways, depending on whether the approach taken to refinery optimization is bottom-up, or top-down:
The top-down approach is based on hierarchical optimization: the refinery optimization problem is addressed as a succession of optimization problems of different time magnitudes and granularities. The first problem is a mid-term planning problem and is concerned with the refinery as a whole and a time frame of one to several months. Subsequently, the time frame is subdivided into finer time intervals. At the lowest level, the theoretical goal is to achieve operations scheduling on a day to day basis.
The bottom-up approach is one that starts with local problems and tries to aggregate them into a consistent solution at the refinery level.
In contrast to traditional bottom-up approaches – which attempt to build an overall solution by aggregating local solutions – we start by achieving a feasible, “good quality” overall solution using our smart simulation engine. Then, guided by the consistent overall solution, we seek to optimize local operational challenges.
Our innovative approach to refinery optimization takes account of 2 crucial facts:
- Day-to-day operations are subject to uncertainty,
- Regardless of the inherent formal difficulty of achieving an overall refinery schedule optimization, an overall optimized schedule is of little use.
This is simply because an overall solution achieved that way is inherently unstable: the slightest change or unforeseen event means that the whole schedule must be rebuilt. And given the huge amount of inertia in such a large system, any sudden change of trajectory consumes an equally huge amount of energy.
Under this pragmatic perspective, refinery optimization appears as the search for a maintainable globally feasible, locally optimized schedule. Optimization is applied to sub-systems where a high economic impact is achievable.
IoT Solutions
PRINCEPS’ scheduling technology represents a technology leap through a variety of innovative features, such as:
- The capability to dynamically modify events during simulation, making a schedule self-adjust its events to the simulation results
- Schedules and models archiving and “versioning”, merge different branches from different users, or rolling back schedule changes as needed
- Smooth and continuous transition between model versions within the same schedule
- The capability to dynamically modify events during simulation, making a schedule self-adjust its events to the simulation results
- Schedules and models archiving and “versioning”, merge different branches from different users, or rolling back schedule changes as needed
- Smooth and continuous transition between model versions within the same schedule
Key Customers
Bayernoil, BP, Total, Saudi Aramco
IoT Snapshot
[Vendor_Name] is active in the oil and gas industries.
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