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Engineering or asset information?

2015 February 04, 09:00 CEST

How technology, regulation and efficiency requirements transform technical knowledge management

AUTHOR: Valentijn de Leeuw, Vice President, ARC Advisory Group

The Vision That Triggered Transformation

In 2005, Thomas Tauchnitz of Sanofi-Aventis, a leading pharmaceutical company  published an article in a German edition of Automation Technology in Practice, titled ‘It’s time for an Integration of the Process Design, Engineering and Plant operation processes’.  The article consists of a vision and strategy for implementation the concept using computer software.  Dr. Tauchnitz explains three basic requirements shall be respected: every information is generated and maintained at only one location, existing knowledge is reused where possible and the software tools stay interfaced while the production plant is in operation.

Tauchnitz sketches the workflow from process design using process simulation software, the transfer of the resulting process information to an computer-aided engineering tool (CAE), common to all engineering disciplines involved in front-end and detail engineering.  He explains how modular engineering  - concept known since many years – should be implemented: standardised modules comprising all its functions are built, maintained and instantiated for a particular engineering task.  As an example a reactor module would contain temperature and pressure measurement and control, valves for material transfer, level control, safety equipment and automation, stirring etc.  The corresponding equipment lists, design documentation, safety procedures, testing and qualification procedures would be part of the template as well.  Instead of engineering every new equipment, replacement, modernisation or repair action from scratch, the engineer would only deal with adaptation, and integration in a larger system and have more time for optimisation of the design and improvement and maintenance of the modules.

Concurrent or Collaborative Engineering?

Today several intelligent CAE systems provide the possibility for several disciplines during plant engineering to work on the same equipment, from their own perspective and using their own typical way of viewing their work: process flow diagrams (PFD) for process engineers, piping and instrumentation diagram (P&ID) for automation engineers, isometrics for piping, etc.

When several engineers work on the same item, this type of tool helps in maintaining the integrity of the engineering data.  For example if a process engineer changes the maximum temperature or flow rate in a tube, then the pump that should displace this fluid should have specifications that can handle these maxima, and if it cannot, the tool will create alerts for the pump specification. Similarly the pipe diameter should be able to handle the flow rate, and so on.  Beyond handling rules, these systems can also handle authoring workflows, including submission, review and validation statuses for changes.

While for engineering procurement and construction companies (EPC’s), concurrent engineering may have been a standard practice since the beginning of the use of CAE tools, in some owner-operator (OO) companies a sequential engineering was the norm.  Enabling multiple disciplines to work on the same design item has economical, organisational and social implications.

Social and Cultural Aspects

When introducing concurrent engineering, or collaborative sequential engineering using a single engineering data repository, people need to become familiar with new processes and technology.  What could be more challenging is that they are required to share their information, their ways of working, and their rationales for making decisions.  They sometimes have to learn to collaborate, which includes listening to other’s opinions, defining agreed upon on rules and responsibilities for the different contributors, negotiating, collaborative problem solving and resolving conflict constructively.  This transformation can create some disturbances, as people have to leave their comfort zones.  It can create conflicts and fail, if it is not properly managed.  The engineering managers, who are ultimately responsible for a successful change need to have people and change management skills.  They can be assisted by change consultants, but for a sustainable implementation they will need to acquire these skills to coach their collaborators long after the change has been implemented.  This is not optional, because not only the work climate, but also the productivity depend on it.

The people in an organisation behave according to collective beliefs and rules.  In teams these are called norms, for the organisation it is referred to as culture.  Some of these rules and beliefs are implicit, that is, they are not explicitly stated although they are operational; some may be unconscious and several may be conflicting with the formal rules and principles of the company.  Changing culture successfully requires discovering the reality and making it explicit, then creating a vision that bridges the business objectives and the collective needs, and gradually implementing a new culture and sustaining it.  A handbook or a training can help with this, but it requires the leaders to meet with people, listening to their ideas and concerns, explaining, acting on their feedback, involving them in work design, and recognising their efforts in making the change happen.

Organisational and Economic Impact

Although intelligent CAE may enable concurrent engineering, not all engineering organisations use it. ARC did an informal study a few years ago among subsectors of the process industries, ranging from large continuous petrochemicals to pharmaceutical manufacturing on several continents.  The survey indicated that around half of CAE users are organised for a fair or high degree of concurrent engineering, but that a third prefers to use sequential engineering. The purpose of several engineering disciplines working concurrently on the same design item is to shorten project time.  However users agree that this increases error and iterations that ultimately increases the total effort.  EPC’s may not have the choice when under great time pressure, but for OO’s conceptual engineering design is not on the critical path, and can afford to have longer project duration to save engineering effort.  An economic optimisation that balances project cost with value from earlier operational readiness would probably show an optimum at an intermediate degree of concurrent engineering.  Users indicated during the same survey that increased engineering productivity of 5 up to 50 percent can be achieved, related to time gains and increased data accuracy, depending on the degree of concurrent engineering used, however this comes at the cost of a significant investment in modular engineering and workflow modeling (see below).

Concurrent and collaborative engineering may cause small detail adjustments to workflows, and definition of responsibilities of individuals that may also surface as frictions on a human level (see above) but technically the organisation would not be affected in a major way.

Modular Engineering and Modular Process Technology

Reuse of information and knowledge is a way of increasing engineering efficiency.   The second ‘Tauchnitz principle’ to reusing knowledge as much as possible (see page 1) implies standardisation on proven modular designs.  These are ready to use engineering information for process units or sections, composed of process equipment, instruments, control, piping, pumps, mechanical agitation, etc.  An engineer picks such a unit or process section, rather than have to re-engineer the sections, and can concentrate on the performance of the process.  When standard modules are lacking, documentation should describe solutions for the engineering task that have been used.   Challenges related to modular engineering are the considerable investment in creating the modules.  For OO’s this is an investment that can pay off over time but for EPC’s this could be uneconomical unless the EPC can standardise on a single tool and has the capability to export designs to the CAE tools their clients prescribe.

The F3 Factory project, financed by some 25 companies and the EU, and comprising seven industrial case studies, ran from 2009 until 2013, with the goal to overcome the disadvantages of large-scale continuous processing (high capital investment and rigidity) and small scale-batch processing (inefficiency) and combine the respective advantages by introducing efficiency to multi-purpose, multi-product facilities; and flexibility to world-size continuous facilities.  Research objectives included:

  • Provide more compact and less costly process designs that lower environmental impact to support ‘process intensification’
  • Develop standardised, modular, plug-and-play chemical production equipment capable of handling many chemical processes
  • Develop engineering methodologies for intensified processes
The project has delivered many promising results and several modular processes have been developed.  All have demonstrated significant gains in both cost and sustainability.

The idea is that, to scale up production capacity, a manufacturer needs only to add standardised, small-sized units; rather than engineering a larger plant.  This reduces engineering cost and time, and reduces equipment cost even further because larger series of equipment can be built.  The concept requires a new engineering approach that optimises the process within the constraints of a choice of standard modules, rather than tailoring equipment to the process.

The trend is to produce smaller quantities, introducing gradual improvements in product and process and responding flexibly to market demands.  This provides the potential to exploit the flexibility of a plant designed for a range of operating conditions, and thus for designing equipment to fit an expected range, rather than a single optimum.  The use of adaptive production optimisation and quality management systems in line with the latest FDA cGMP guidelines will be favorable in these conditions since they will absorb process modifications and variability in processing conditions when some or all of the end-product remains identical.

The use of the modular production concept would eliminate a range of engineering and validation tasks, since varying production rates can be handled by adapting the number of production lines required to produce the required quantities.  Similar projects have been done at the Massachusetts Institute of Technology (MIT), in the USA in collaboration with manufacturers.

Industrial Internet of Things initiatives such as Industrie 4.0, or the Industrial Internet Consortium, have led the industry, in particular the sector producing by batches, to think about how to implement reconfigurable production lines that can respond to varying demands and constraints.  This requires new concepts and standards to integrate equipment ad-hoc and in close to real time, including their automation and operations management software components.  Modular engineering approaches discussed above, greatly facilitate the engineering of modular process technology and we expect the usage of modular engineering to increase sharply in the near and mid-term future.  The batch-oriented industries will be the first ones to adopt the approach, and we expect that also large continuous processing companies will start thinking about rationalising their engineering, construction and operational paradigms and applying these concepts.

e-Qualification and e-Compliance

There is more to Dr. Tauchnitz’ vision.  The analysis of risks related to the process and the equipment on the product quality, should be reflected in requirement specification, testing and qualification plans.  This analysis can be done systematically based on information in the CAE tool, and its workflow can be fully automated in such a system.  Test and qualification results can be linked to equipment requirements via the risk analysis and so the process reaching from specification to compliance can be executed in a paperless manner, and can be built efficiently as an extension to intelligent CAE systems.  Some providers are pioneering this approach with visionary companies today, creating significant benefits from efficiency and accuracy. ARC expects that this functionality will become mainstream soon, as the compliance pressure for all industries increases constantly, and companies need to respond to this pressure by creating additional efficiency.

Integrated Engineering

The Integration of the Process Design, Engineering and Plant operation processes and third Tauchnitz principle: ‘the software tools stay interfaced while the production plant is in operation’ have also major implications, both for EPC’s and OO’s.

During design and build phases our customers tell us that the exchanges between EPC and OO have become more frequent and intense over the past years.  OO’s want to stay on top of choices made by the EPC during the design trajectory, review progress and co-manage and co-own the work.  More and more these exchanges use common intelligent CAE tools that enable parties to share, visualise and discuss design work.  Even more significantly, the so-called handover from EPC to OO at commissioning happens more and more in electronic formats.  The traditional paper documentation was cumbersome and time consuming to discover and master, and close to impossible to keep up to date.  Today more and more OO’s want an electronic, intelligent asset information data set, reflecting the ‘as-built’ situation, to be able to keep it up to date during the plant’s life cycle. This is not only efficient from a resource point of view, but it is also more and more a regulatory requirement to be able to produce up to date asset documentation, and demonstrate compliance.

From the point on that the plant starts up for the first time after being built or revamped, at least two distinct, complementary activities use asset information.  Engineering uses plant information to plan for changes or improvements such as debottlenecking, heat integration, quality improvements or other projects.  Simultaneously, maintenance uses the data to trouble shoot, repair, order spare parts, and so on.  If asset information is not maintained during operation and maintenance of the plant, its accuracy gradually degrades over time, and when engineering need to start a project they loose precious months in discovering what the actual state of asset is, rather then working on the engineering task.  A major benefit of using intelligent CAE tools is therefore their usage across the plant lifecycle, and the integration of engineering, operations and maintenance processes using a single, up-to-date asset information data.  Hence, engineering and asset information become indistinguishable and ‘as-built’ information is transformed into ‘as-maintained’ information.

Processes and work design need to be adapted, to make sure that engineering and plant changes are captured in the CAE or Asset Information repository.  Also here a culture change is necessary, along the lines of what was described above for engineering organisations.

Based on client testimonials, we believe that users can gain several man-months of engineering and maintenance time per plant.  Benefits related to safety incidents and emergency situations are more difficult to quantify.  In major accidents the availability and quality of information to base decisions have proven to play a critical role in making correct decisions and reducing damage, injuries and fatalities.  The opportunity cost alone of production stops related to asset information will easily justify the effort of implementing integrated engineering.

Interoperability With Control and Other Systems

But this is not all.  Dr. Tauchnitz pushed the vision further by stating that a generic model for DCS and PLC programming should be part of the CAE tool.  Via a universal interface the programs could be exported to various automation brands, and be compiled within the equipment, with the goal of reusing standardised programming modules within different types of equipment.  The author also extends his concept to configuration of production systems, such as MES or Operations Management.

Both for EPC’s and OO’s this creates major time savings in engineering control systems.  For OO’s, during the operate-maintain phases of the plant, the benefit would be even more important.  OO’s generally use several control system brands and could benefit from a uniform engineering approach for multiple brands.   As control systems are updated and changed in the field, a challenge arises in keeping the asset/engineering information accurate.  The user organisation NAMUR ( has responded to this challenge by defining a standard data format for exchange between process control systems (PCS) and CAE tools (NAMUR Recommendation NE 150, published in October 2014).  Dr. Tauchnitz recently reported about a set of demonstrators implementing this data exchange format for a DCS tag, between four CAE systems (Aucotec, Bentley, ESP, Siemens) and three PCS systems  (ABB, Siemens, Yokogawa).  This opens a highway of possibilities and benefits for users and system vendors alike.  The initial momentum used to create the demonstrators should be maintained.  Users should require their full implementation by an even larger number of vendors, and its usage should pay off for users in terms of engineering efficiency, for CAE vendors by an increased market size, and by PCS vendors, because of a more favorable life cycle cost.

The interoperability with MES or Manufacturing Operations Management (MOM), is still a dream for the future, as is also a bidirectional exchange with process simulation.  If those subjects would be pursued, another wealth of benefits would be in reach.  The work on the bidirectional interface between CAE tools and PCS shows that what was regarded as unlikely can become reality very quickly, when vision, interpersonal skills and multi-party cooperation coincide.  The same is true for interoperability between CAE and MOM or process simulation.


Finally, Thomas Tauchnitz develops the vision for enterprise-wide standardisation and implementation, reduction of the number of systems and interfaces, organisation for centralised maintenance and support and promoting company wide knowledge management.  This aspect of the vision has not received much attention yet, but from experience and client case studies on implementation of MOM applications, we know that this approach decreases the total cost of ownership of an application, and thereby shortens payback periods, and increases net added value.  We therefore strongly recommend paying attention to this point.


Up-to-date, accurate, easy to access engineering and asset information during the full plant life cycle brings significant engineering efficiency benefits for EPC’s and OO’s, that users of these systems estimate to be between 5 and 50%, depending on their initial efficiency and the degree of concurrent engineering.  Users were spread across various process industry subsectors ranging from petrochemicals to pharmaceuticals.

Intelligent CAE systems enable concurrent and collaborative engineering.  Engineering efficiencies are obtained because of an accurate, up-to-date, data repository that all engineering have access to at any point in time.  These systems help maintaining engineering information integrity.

Concurrent engineering reduces project duration but diminish the engineering efficiency gains.  Every company or organisation should determine its optimum ratio of concurrent versus sequential engineering.

The ‘as-built’ (or ‘as-revamped’) asset information can be maintained in intelligent CAE systems, that become an ‘as-maintained’ asset information repository, that both engineering, operations and maintenance use and update, to make optimal decisions.  This so called ‘integrated engineering’ practice increases operational efficiency and safety.  ARC estimates that companies will several up to several man months engineering time per plant per year..

Major efficiency gains would be obtained when users would stimulate CAE and PCS vendors to implement the recently published standard NE 150 for bidirectional data exchange between the two types of systems.

Standardisation on systems, methodologies, modular engineering and processes, reduces the total cost of ownership, increases productivity, and reduces training costs.

Bio: Valentijn de Leeus, Vice President, ARC Advisory Group

Valentijn is an independent expert-evaluator of research projects for the European Commission in information technology and communication, social sustainability and worker attractiveness in manufacturing domains. Valentijn holds a PhD of technical sciences from Delft University of Technology (NL) in cooperation with Ecole Nationale Supérieure des Mines de Paris and IFP and also holds a Masters in Chemistry from Utrecht State University located in The Netherlands. Founded in 1986, ARC Advisory Group is the leading technology research and advisory firm for industry and infrastructure.

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