INTRODUCTION:

Engineering, Procurement and Construction (EPC) in various streams is matured to have sufficient stability. Tender wordings are fairly standardized and General Conditions of Contract are established. Costs are fairly established. Information is gathered and processed at an unprecedented rate. Cheaper computing and storage facility collect data has been a prime mover for the same. While knowledge and expertisein a particular domain is present, pooling of the same faces challenges. Communication often fails because what is perceived by the individual trying to communicate an idea and as perceived by the person trying to understand the same is based on the yard stick and experience they have. It is well established that to ensure relevance of data present, there is a need to classify the same.

Standardisation in Construction Industry

Construction contracts have become more efficient because of standardisation of most activities involved between the owner and the contractor¹. Standard forms of contracts, dispute resolution mechanisms, localising to requirement for various regions have helped productivity of organisations as both the contractor and owner or employer have defined roles, responsibilities and working mechanisms in place.

This has led to the deliverables quality of an organization to distinguish it from another. It was predicted that by 2020, quality will define the 21^st century, just as how the 20^th century was known for productivity². Quality circles call for Plan-Do-Check-Act (PDCA), Plan-Do-Review-Improve cycles (PDRI) and such for improving processes. Every serious EPC Contracting Firm has audited systems in placefor the same, generally, along the lines of ISO9000 or ISO 9001.A standard across industries which will ensure relevant information is captured requires to be put in place. What is put in to the system will be the outcome of lessons learnt.

Factors external to the organisation are well established, however, every organisation has a differing standard of addressing knowledge. However, the knowledge within the organisation is often unstructured. This is because every organisation develops systems which is deemed the best fit at the point of time they are set up. However, when as the organisation scales up in terms of the size of teams, domains of expertise, diversification into new business, mergers with larger partners, it will quickly find that the systems developed will not suit and may even become irrelevant.

In the same light, procurement management, procurement schedule, optimum procurement levels are well established³. These are external to the contractor. The organisation is able to effectively communicate its specification and needs.Standardisation of communication protocols with definition has been established in this case also. The standardisation is across individual organisations. Even when the format across organisations may not be the same, what is to be done, how and where for different items are well established.

Challenge of Knowledge Management

EPC projects typically have a large number of teams of temporary virtual teams. These are dynamically created as a process requires or as a situation emerges. They may be teams assembled to do a particular task that will be relocated between various WBS within a project.They could also be shuffled within the project within a WBS for more effective utilization. Not to mention that taskforce teams could be created to address a specific nature of problem across the organisation.By the end of the project, a team member might have served in various capacities in different teams. The members are de-mobilized in stages. The employee ownership on a process shifts to the new task at hand. With passage of time, the individual may fail to remember and the reports will lose relevant information.

This paper views data as pieces of information that has to be collated and transforming it. Knowledge in the light of data mining has been described as “A pattern obtained from a KMD process and satisfied someuser specified threshold is known as knowledge.”⁴

A Learning organisation has certain attributes⁵:

· Scheme to solve Problems Systematically

· Learn from their experiences

· Incorporate best practices from peers

· Have mechanisms to disseminate knowledge quickly and efficiently

· Encourage experimenting new approaches

Quality systems and standards of the organisation that are in place will ask these questions as part of the Lessons Learnt from incidents.This necessitates determining the definitions which enables an individual to decide

· What is valuable

· What should be re-used

· What should be highlighted

· What should have been done

· What should be discarded and why

· Where should the aggregated data be stored

· Who will benefit from the data which has been collated

· From whom the data Who should be kept away and for how long

· What should the importance or weightage should be given to what is collected

Systems are normally in place to allow all or most of the above questions to be answered. These questions would be stored according to the protocol set. The protocol records into systems which may hide it among other records. Data is available which is not readily available. Such a situation is illustrated in the case study below:

Case Study of a design incident

Often, to develop skills, structures requiring special design is given to an engineer with relevant experience, but not with domain expertise. Conveyor supporting structures have stringent design requirements. Underground structures are constrained by crack width in the structural elements. To a new entrant to this domain, these might seem unrealistic considering the load and serviceability parameters imposed. Existing talent pool will not have the time to hand hold with all relevant information. This will also be restricted to the projects that have been experienced by the mentor.

This is a case where there will be a clear break in communication because of the priorities. When the explanation is not clear to the person being mentored, accepting a statement made is difficult. This leads to the situation where what should have been a lesson learnt is not being applied. The design engineer would not have had independent access to information. The facts and interpretation was based on the limited input available from the experience and what was shared by one individual.

Current Scenario in Knowledge Management

Every organization has some Local Area Network (LAN) or Virtual Private Network (VPN) for the exclusive use of its employees. Data security of both clients and its own are secured by measures that are in place. Most of these systems

Knowledge Standardisation in EPC Project

Construction Specifications Institute (CSI) and Construction Specifications Canada (CSC) have developed the Master Format which is another area where the standardisation is in place. However, multi-disciplinary standard is not in place which will be usable across the boundaries of a company. This system has enabled incorporation of many of the items directly into Building Information Modelling (BIM) systems. The BIM system is now usable because, there is a standard format available across institutions using the system. The data about data stored is a standard however, projects in which the tool is used is as different as the organisation using the product.

Extending this principle, when key areas of knowledge are identified and kept in place, software tools will expect users to populate the fields of the same. This will enable different systems to be able to identify projects of similar nature. For instance, in a truly multi-disciplinary project as an EPC project in Oil and gas project, communication between disciplines is further limited because of division, discipline differences.

For instance, when clear indications of foundation for proposed smaller pumps are indicated, provision for the same will be considered by the civil engineer. There is also the case where the locations of very small foundations as for supporting load is not available at the onset. If the working piping engineer will have comments made by a civil and structural engineer in past projects, potential areas he can keep an eye on is known. This would reduce rework and goes a long way in improving quality and productivity.

The engineer from the other discipline will require relevant information from similar jobs executed. In most of theorganisations, one of the seniors direct the team member to relevant projects. There is also the probability that the engineer will be asked to choose the topic. In such a case, the individual may choose a similar structure which may not be the best fit. In load test of foundations, it will be wrong to test the foundation on similar lines as a pile foundation.

The cases demonstrate the need for relevant data in the EPC sector.

The Minimum data to be classified

As a first step, every organisation will already have already classified data to a minimum of the following areas. These are the areas where the cost impact will be there when knowledge is re-used.

1. Goal of the project –Goal should be clearly understood and agreed upon by all the planning participants, including top management, before the commencement of actual planning. Great attention should be paid to accurately defining the scope of the project. A project may be bid for at a loss to gain pre-qualification for a nature of job that is unique to the organization.

2. Equipment involved- Some special equipment may have been used. Use of diaphragm walls and tunnel boring machines will distinguish one project to another and one organization from another. Capturing such data will be of significant advantage in planning. The type of crusher used in a project impacts the supporting structure, number of levels and bracing system required.

3. Specifications designed to – Specifications vary between countries, regions, hazard level and material properties. A much lower tonnage of steel may be sufficient for safety and serviceability, however a minimum thickness criterion in the specification could impact the estimate adversely. Hence to maintain reusability of information, knowledge management systems should capture this aspect of data.

4. Soil and terrain consideration- Different project locations with similar equipment and specifications will require a different treatment if the same is to be constructed in a different area with different wind, earthquake criteria. The foundation requirement will be an important aspect determining the overall cost of the project.

5. Type of contract- The mode of contract plays an important role in pricing and generation of Bill of Quantity. The route the project used is important.

Data Management Strategy

Each of the item mentioned should be assigneda unique code. The broad areas in data classification should be simple, intuitive and encompass all similar fields of work. Increasing complexity will defeat the process as employees will find filling the data challenging and probably intimidating. Under each of these headings other specialization should be added.

When this is done across the industry, relevant fields will be updated by the employees. When a structure in a project is to be estimated, the person estimating will have a look at what he has in hand and classify it. This classification may be validated by his superior and the problem reduces to searching tags matching what has been given. When the backend has sufficient data, it will be able to suggest similar jobs that the employee may be interested to refer.

The system can learn the different projects that have been accepted as relevant and related to a set of key words. This will be returned when another search is made. In working on the current project, the learnings will be updated, thus adding to the data pool.

When the data is collated so, the design engineer in the case study will not depend on his superiors or peers for finding what would be the best strategy that he will adopt. His problem reduces to codifying the structure and showing it to his superior for concurrence of coding adopted. A simple search will yield all matching and relevant designs of the past. The lessons learnt and Do’s and Don’ts for his project is simply and clearly got. He will perform his design incorporating all the past experience that the company already has and will be adding to the existing data for use in the future.

Every bit of information added as Lessons Learnt will add value to the knowledge of the organization. Every bit of information that goes in should have some checks and cleaning mechanism to prevent garbage values from entering into the system. This should be followed by having the entered data validated and vetted by at least one level above in hierarchy. Data with high impact should be having suitable validation and Vetting mechanism in place.

Maria Serena Chiucchi⁶reports organisations do not seem to address the issue of Intellectual Capital. It is possible in the EPC segment that there could be a failure to address this problem. One of the reason would be that in addition to simple problem solving skills which most of the other industries desire to have in their employees, the employees in an EPC company get exposed to diverse problems. Putting them all into one would be an impossible task. At this point, the principles outlined above can be extended.

Case Study of a Construction Company diversifying into new avenues

Take the case of a small construction company that has been constructing residential buildings. With the experience gained, it will be able to construct institutional buildings and recreational facilities. If this organisation bids for construction of a coal handling system for a power plant, it will very quickly realise that the nature of work is different from the ones it has undertaken. The steel structures have different tolerances and design requirements. The underground works for material handling equipment as a wagon tippler is far more massive than what the biggest industrial shed that the organization would have executed. In addition, there is also the fact that the tools and plant available will not be sufficient to.

However, when the organisation up scales and wishes to undertake industrial contracts, it will find that the knowledge pool contained will not match the requirement. When the knowledge is classified with weights, a decision on using the consultant route, Joint Venture route or recruitment of talent focused towards the direction the company wishes to make a foray into will be clear.

Data about employees that can be classified

The most valuable resource of the company will be the Human Resource. A lot of potential is present that could be used within the industry. When the organization has to take a decision on how to tackle a new EPC job, this data will be helpful.This means arriving suitability off a person’s capabilityfor constructing or handling the project assigned. This aspect is very crucial in today’s competition. A lot of damage and rework is taking place just because the contractor or construction manager doesn’t have sufficient information on suitability of a person for a particular task. Thus, there is aneed toidentifying skillset of a person and quantify and qualify the knowledge.

With the help of this scale a person can be classified learner, beginner, amateur, senior and advance. The basis of the scale could be the number of projects and type of projects an engineer has worked on. With this data we can plot a graph and then with that we can come up with the level of an engineer and then one can conclude if he is able to handle the project or not.

A sample of the same is illustrated below:

Thus, the areas where an individual can fit into an organizations key areas is immediately identified. The performance indicator can be a probabilistic function that is derived from the number of jobs done in a particular domain along with a performance rating against the peers and difficulty level when compared to previous executed projects or risk index.

When the above chart is compiled for all employees, and the same is put up, it will show the areas where there will be a gap. The above data is purely fictitious. Gap areas in employees will be immediately identified when a new type of project will be undertaken by the EPC company.

Challenges

Often, potentially embarrassing incidents to an individual are window dressed to prevent blame, criticism and potential hurdles to the growth. The cost involved in developing individual systems to handle knowledge will be costly. In addition, the training to be imparted will mean employees will take time to accept a new system. This learning curve is potentially reduced when the principles are established. Users of the system will know what, where, when and how to put information associated with the project.

Face to Face meetings are the best form for sharing knowledge⁷. When the inter personal touch is lost, the danger of reducing the vetting of learnings to clearing one more item from the work flow.

CONCLUSION:

Such a system of classifying data will leave the EPC community benefiting at large. The tags can be attached to every resource and bit of information available as drawings, designs, specifications, procurement documents, minutes of strategic decisions.

The biggest benefits will be integration of lessons learnt with planning tools. When the system knows the codes used to describe a bit of information, relevant codes can be shown to the users. Planning team can harmonize activities with target milestones, continuously learning from past experience because their tools digs into the company’s knowledge base. Key players will continue to enrich the company even when they are not working on the specified projects as some other individual is digging into this information store. Even after the employment tenure, the knowledge is safe for reuse. Instances of ‘reinventing the wheel’ will be reduced.

There is a marked acceptance of use of Information and Communication Technologies (ICT) when compared to the scenario in 2009 described by V Ahuja et al in their paper⁸ to what has been observed in 2014 observed by Anil Sawhney et al in their paper⁹. Wider acceptance is possible because of the drop in prices of hand held devices that can capture time spatial details as GPS Coordinates, photographs, barcodes and QR Codes. Updated drawings with unlimited version history can be made available on tablets to remote sites over GPRS networks. Real time updating of incidents and learnings can be updated and validated on a day to day basis. This is the best time for the construction industry to pool their resource to get a system of classifying data in place in India.

REFERENCES:

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2. Santana, R. (2010, August). A Continuous Improvement Approach: Closing The Loop In An Engineering, Procurement, And Construction Management Environment. Performance Improvement, 49(7).

3. Watermeyer, Ron. International Standards for Construction Procurement. Civil Engineering: Magazine of the South African Institution of Civil Engineering 17.1 (Jan/Feb 2009): 20-21.

4. Satchidanand Dehuri, S.-B. C. (2011). Theoretical Foundations of Knowledge Mining and Intelligence. In S.-B. C. Satchidanand Dehuri, Knowledge Mining Using Intelligent Agents. Advances in Computer Science and Engineering: Texts – Vol. 6 (pp. 1 - 26). London: Imperial College Press.

5. Love, P. H. (2000). Total quality managment and the learning organization: a dialogue for change in construction. Construction Management and Economics, 18(3), 321-31.

6. Maria Serena Chiucchi. Measuring and reporting intellectual capital Lessons learnt from some interventionist research projects. Journal of Intellectual Capital Vol. 14 No. 3, 395-413

7. Serkan Kivrak, Gokhan Arslan, Irem Dikmen and M. Talat Birgonu. (2008). Capturing Knowledge in Construction Projects: Knowledge Platform for Contractors. Journal of Management in Engineering, ASCE. 87 - 95.

8. Vanita Ahuja, Jay Yang, Ravi Shankar. (2009). Study of ICT adoption for building project management in the Indian construction industry. Automation in Construction 18 415 - 423

9. Anil Sawhneya, Kamal K. Mukherjeeb, Farzad Pour Rahimian. (2014). Scenario Thinking Approach for Leveraging ICT to Support SMEs in the Indian Construction Industry. Procedia Engineering 85, 446 – 453.

Received on 15.11.2015 Accepted on 16.12.2015

Int. J. Tech. 5(2): July-Dec., 2015; Page 100-104

DOI: 10.5958/2231-3915.2015.00004.8