WIPRO THOUGHT LEADERSHIP Intelligent Manufacturing

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1 Intelligent Manufacturing

2 TABLE OF CONTENTS Oil and Gas Industry Refinery Capacity Economics of Refinery Operations Trends in Oil and Gas Refining Industry Intelligent Manufacturing Scope of Intelligent Manufacturing6 Intelligent Manufacturing: Operational Level6 Intelligent Manufacturing: Strategic Level8 Industry Trends9 Value Proposition of Intelligent Manufacturing Why Wipro The right Oil and Gas (O&G) partner with rich IT expertise and key industry relationships21 A strong value proposition22 Other solution offerings References Intelligent Manufacturing Solution Intelligent Manufacturing Maturity Framework11 Challenges of Typical Refinery12 Overall Intelligent Manufacturing Vision12 System Architecture13 System Features16 Wipro s Role as System Integrator

3 OIL AND GAS INDUSTRY The increase in the demand for energy is closely correlated to the economic growth. The International Energy Agency (IEA) estimates that the total demand for oil and gas products could reach over 92 million barrels per day by Fig 1: Total Global Demand of Oil (Source: International Energy Agency (December 2008)) The oil and gas industry is segregated into various discrete activities. The focus area of this paper is the refining aspect of the supply chain and how technology can be leveraged to improve the value and margins of the refining business. Crude Acquisition Oil refining is a global business since crude oil acquisition can be done across the globe and it can be transported to various refineries. Refineries are rated on their ability to process feedstock (refinery complexity). The higher complexity refineries can process poorer quality feed stocks with higher sulfur content into value added products. Refineries with greater complexity can process a range of feedstock and hence can generally obtain higher margins by reacting faster to market opportunities. Refinery Capacity Total Demand (million barrels per day) Refining Fig 2: Value chain of Oil and Gas Industry Primary Distribution Product Storage Since the peak in 1978 and 1981, the world s total refining capacity saw a decline for most of the 80s and the 90s. There has been a shift in the geographic spread of installed refining capacity, and the number of refineries in developed regions like Europe and United States has declined. The Secondary Distribution creation of new refining capacity has been concentrated in Asia while the utilization rate of existing facilities in Asia Pacific, Europe and United States has increased significantly. There are two fundamental reasons for the shift from low complexity and low economic size to the more complex larger refineries. Firstly, as discussed earlier, the economic viability of older refineries is greatly reduced due to better margins that can be achieved in newer and more complex refineries. Secondly, the petroleum specifications have tightened considerably. These trends also push existing refineries towards leveraging technology to improve their Gross Refining Margins (GRM) to remain competitive with Greenfield refineries. Economics of Refinery Operations The refiner s ultimate goal is to optimize the refining process and hence maximize the yield of all the products with relation to the feedstock used. Gross Refining Margins (GRM) is the total value of the finished products less the cost of crude and other feedstock used. Consequently the GRM of higher complexity refineries are higher since the relative yield of light and middle distillates Commercial & Retail Consumers from low-cost, heavier and sourer crude is greater. The crude that is landed at refinery sites is often a mix of various crudes and the optimum crude blending option has to be evaluated before processing. The ultimate aim of any refinery is to process the crude such that the dollar value per barrel can be maximized. This is often a complex processing challenge and a combination of technologies is used to ensure end-product quality, increase fuel efficiency and minimize load on environment. Refineries use various disparate information system modules to manage and optimize various areas of their operations from crude mix selection to operations and maintenance.

4 Trends in Oil and Gas Refining Industry $ $ $ $ $80.00 $60.00 $40.00 $20.00 $0.00 Crude Oil Prices per Barrel 30-Dec Dec Dec Dec Dec-09 Fig 3: Crude Oil Prices at the New York Mercantile Exchange from 2006 to the Present The price of crude has been fluctuating greatly from a high of USD 145 to below USD 40 levels in the last 24 months. In such an unpredictable environment, making investments get difficult and there is a growing need to leverage better technology in order to meet the user demands. The industry has to find cost-effective solutions in order to cater to increasing demand. In an industry where the stakes are already high, volatile prices and low retail margins have made the risk of investments even bigger. It is obvious that the oil and gas industry must tighten its belt to manage costs and cash flow better something that helps add to the bottom line even in good times. The environmental pollution norms are getting tighter across the world and all companies are actively devising strategies to meet them. The existing refineries would face a lot of pressure due to factors ranging from economic downturn, changing energy policies and the expansion pattern of global refining capacity. The need for efficiency and optimization will continue since it would help refiners make it through tough economic conditions today. The adoption of correct processes and technology would help them meet the increased market demand and quality would be a competitive factor. The industry is confronted with certain critical challenges which it has to address in the current volatile environment: Aging Workforce: The industry has an aging workforce where the average age is 50 and most of the industry is ready to retire. Added to this is the fact that student uptake in energy-related fields like geology and petrochemical engineering is seeing a slowdown, drawing deep concern. According to a John S. Herold report, upstream oil and gas companies will see an erosion of 60 percent of their employees by Developing human resource is clearly a priority. While information technology (IT) has empowered the industry to address these challenges, the increasing IT dependence has also generated mountains of data at an increased rate, which if not managed properly can create bottlenecks in the decision making process. Technology Needs: Oil and gas companies need to focus on medium to long-term growth and continue to make investments in human capital and technology as well, calling for sound management decisions, cost control and risk management. This calls for the creation of industryspecific solutions in people and training as well as in technologies like digital oil fields, engineering portals and partnerships with technology majors. Data Management: The oil and gas industry throws up over 23 MB of data every second, making the task of storage, retrieval and analysis a challenge. In addition, with the complex regulatory and reporting requirements of the industry and the growth of investor and stakeholder requirements, data management itself has become a prime concern. The advent of International Financial Reporting Standards and the Sarbanes-Oxley Act for US registrants has added to the challenges. Data management and knowledge management have to become more intelligent and more efficient to meet industry demands. Geographical Spread: The Exploration & Production (E&P) sector is expanding to areas outside the mature base of the Middle East, Canada, US, Europe and the UK, competing for resources and end markets. Geographies such as Russia, Kazakhstan, Africa and Latin America are the new focus of the industry, leading to higher project complexity. Managing global operations, with local resources, across JVs, partnerships, and product lines calls for one management and one leadership. As geographical borders are merged in the business, larger corporations need nimble and flexible partners. The pressure on the industry is to address the need for hiring and training a workforce that is familiar and comfortable with new geographies, and to make sound technology investments which can be reused across geographies through tools and

5 solutions that meet the growing need for reliable and efficient data management. There is a growing appreciation, within the oil and gas ecosystem, for the need of improved integration and interoperability of the diverse information stores, which are critical for better collaboration, and information sharing leading to improved productivity and decision making. INTELLIGENT MANUFACTURING Oil majors have started looking at Intelligent Manufacturing (IM) as an investment into the future to meet the various challenges of the industry. Due to the fluctuating crude prices, the refining industry has been hit hard and the fundamentals have now been altered greatly. This has resulted in renewed focus of refineries on operational aspects and the need to improve the bottom line by improved operational efficiencies. Downstream refineries are under great pressure to achieve greater efficiencies over and above what has already been achieved. Intelligent Manufacturing aims at leveraging the existing infrastructure and improving the planning, operation and maintenance of refineries. Intelligent Manufacturing leverages technology to drive and support a more predictive, collaborative, and consistent way of working. It enables a predictive and responsive mode of operation across multiple manufacturing areas that, taken together, can drive Operational Excellence. Scope of Intelligent Manufacturing For the purpose of this paper Intelligent Manufacturing (IM) solution is segregated into two areas: Operational Level: There is a need for monitoring the process at the refinery plant and enterprise level. The maintenance systems should move from a planned, reactive maintenance system to a predictive or reliabilitybased system by leveraging on manufacturing and operational intelligence. This in turn reduces the refinery downtime and optimizes asset utilization (also reduces Health, Safety and Environmental (HSE) incidences). Strategic Level Enterprise View of Information: IM aims at replacing the data silos that exist within individual refineries with a networked data warehouse system at the enterprise level thus increasing the ability of the enterprise to react to unanticipated events by developing enterprise intelligence. Intelligent Manufacturing: Operational Level Improved Maintenance Oil and gas companies are asset intensive industries and in the current economic environment optimizing asset utilization is crucial. The companies look at investment in maintenance as an important area but not as a potential competitive advantage. Companies that understand that maintenance management can be a potential area of significant dollar savings and provide them with a competitive advantage in the industry have rationalized resources both labor and non-labor. This has enabled such technology leaders improve their maintenance management and schedule and thereby improve operations. The maintenance management activities of any company consist of a mix of break down maintenance, preventive maintenance, routine inspection and condition monitoring. Breakdown in any process industry is very expensive since it may result in plant-wide shut down and the downtime is not limited to the time required for maintenance activities. The time required to restart the plant could be significant and it can take time for the plant to reach fully operational status. The economic repercussions of such an event are significant. In addition, the negative fallout related to health and safety, and the environment issues associated to cases of breakdown can have far reaching consequences for the enterprise. Thus the role of the existing maintenance management programs should be to reduce or eliminate incidences of breakdown. The operational parameters of machinery and equipment in the refineries are being continuously monitored and a huge amount of data is available in the Distributed Control System (DCS) or other control systems. These data sources are typically utilized by individual refineries, in case of an eventuality or breakdown, to assess the cause of damage. This data can be utilized by organizations to achieve a predictive maintenance management system. Condition-based maintenance (CBM) should include continuous monitoring of parameters like vibration, temperature across process machinery and plant systems. An analytics system can be used on this data to raise exceptions well before individual machinery parameter or machinery system parameters reach critical levels. The analytics system can leverage on the plant historical data to create and trigger exceptions reducing false alarms and virtually eliminating breakdowns. Based on the criticality of exceptions, a planned maintenance schedule can be designed or operational

6 parameters can be tweaked. The challenge with condition monitoring is having the technical ability to decipher what the measured parameters are indicating about the health of the equipment. The true value of CBM can only be unleashed if data collected on a real time basis from machinery and equipment can be converted into actionable exceptions. For example, all equipments give some sort of warning signs before failure. An efficient CBM system would be able to flag such an exception and preventive action can be initiated to prevent possible failure. Process Unit Monitoring Monitoring of the process units is a critical area for the refineries and there are solutions specific to the industry that provide the process data view at the refinery and need system integration to make this visible at the enterprise level. The system should also have a knowledge repository which ensures that the responses to process and operational exceptions are documented. This enterprise intelligence ensures that the human action plans are optimal and the learning from the refinery operations are documented and codified into organizational learning. The continuous monitoring of plant and machinery allows operators to have a historical perspective and this enables a program of continuous improvement and optimization. Intelligent Manufacturing: Strategic Level The visibility of data at various levels within the organizations is also a key issue that organizations grapple with on a daily basis. On a macro level, the aging workforce results in operational issues including availability of top trouble shooting and operational talent at the field level. The solution to this problem, which is being increasingly adopted by forward looking organizations, is to replicate the machinery and equipment monitoring capabilities that exist at the plant level and make this data available at the enterprise level. Most refineries in their existing operations measure and store the data but the value of the Intelligent Manufacturing system is that it contextualizes the data generated. Existing refineries may have standalone visualization tools to monitor KPIs. However, the data view is limited to one site. A system which provides single window view of multiple sites would be of great value. In such a case, a centralized team in the organization can monitor various plants and refineries across the organization, providing improved detection of potential issues. Centralization of these activities results in improved planning and reduces misalignment with operations ultimately improving refinery uptime as well as the gross refining output. Coordination of operations across the organization can help develop a holistic picture and planning and scheduling of refinery downtime can be optimized taking into Case Study: World Class Refinery Maintenance Practices In a refinery, all equipments are monitored on a 24x7 basis. For example, the compressor OEM provides some monitoring systems in the initial configuration. The rationale for such systems is that the system is optimized and provides safety in operation. Compressor Control Corporation provides CPA system which minimizes compressor downtime and helps the plant operator to optimize maintenance intervals, consequently extending operational compressor life. Condition monitoring systems are used to diagnose and record the plant and equipment performance (including vibrations, axial displacement). The refinery has an event triggering mechanism both at the site as well as the central level. There are people dedicated for condition monitoring in the plant. However, the data is not integrated with the ERP system. There is a department of planning and maintenance in the central corporate office which coordinates all the technical issues related to planning of maintenance schedules. In case of trouble shooting requirements, the central technical team goes to the plant. For optimization, there are various tools including Aspen which run simulation of capacity, plant loading and optimization of feedstock. Levels of Integration in World Class Oil and Gas Organization The organization has an information system for reporting to different management layers. For example, the top management can monitor the various production patterns. However, the asset condition monitoring and problem tracking is inferential in nature. The top management of the firm utilizes Aspen Explorer and can monitor the trends in all

7 consideration the enterprise and market economic scenario. Thus the operational stability of the individual plants can be planned to ensure that the overall economic objective of the enterprise is served. The enterprise view of refinery level data increases the knowledge and learning of the organization. For example, the operational issue with a particular make of centrifugal compressor under certain running conditions that is faced in one refinery becomes organizational learning, and this knowledge can be utilized to prevent the issue in other refineries. This would result in a standard process of dealing with the same equipment across sites. There could be multiple business points of view deployed at multiple sites and the sites do not have to wait for real time experts to arrive for maintenance. This increases uptime by moving towards a predictive and reliability-based operation which also includes CO2 and energy savings. Role-based visibility across the board increases the availability and utilization of data. Industry Trends Various large oil and gas firms have invested in this concept of Intelligent Manufacturing to improve their performance and many of these initiatives are in various stages of adoption and implementation. Firms with brown field assets, have to compete with newer companies with green field assets which are state of the art. In order to keep up in such a competitive space, firms increasingly want to invest in any technology which can increase the margins. The potential role of Intelligent Manufacturing is to reduce operational cost in term of reduced consumables, input material consumption and/or reduce down time. Compliance requirements are also a driver for Intelligent Manufacturing initiatives. However, this is more from the point of industry specific norms which have a bearing on how the operational parameters are monitored and reported. These initiatives around IM are long-term strategies for various companies and are being carried out in multiple waves of adoption. Value Proposition of Intelligent Manufacturing Intelligent Manufacturing is an intelligent tool since it uses already existing technology to improve operational performance. Intelligent Manufacturing is a concept of adding capabilities using existing infrastructure. This involves using the existing operational landscape to the optimum and increasing monitoring and predictive analytical capabilities. parameters. This is configured to the Management Information System through a built-in tool. The managers can access this information from remote locations through a web-based interface. Thus tracking and monitoring at the corporate level is possible. Maintenance Planning The increase in the maintenance periods is governed by business and economic needs and they are balanced across the portfolio of refineries to serve the best interest of the larger enterprise. However, in case of a technical fault, this takes precedence over other considerations. Technical and troubleshooting teams are centralized and there are the condition monitoring teams who are able to monitor multiple refineries as a result of application of uniform systems. The IT strategic decisions are taken at the corporate level and all improvement initiatives are pushed down from the top. Such initiatives are typically done as a pilot in one location and then they are scaled up to other locations. Case for Intelligent Manufacturing Financial Benefits Increase in Gross Refinery Output (Revenue Increase) and improved Gross Refining Margins (profits) Decreased Maintenance expense Increased return on asset and capital deployed Operational Benefits Increased uptime of assets Decreased incidence of Health Safety and Environmental Issues Better Solomon Report results

8 The primary goals of Intelligent Manufacturing and their value proposition: The ultimate goal is to make equipments self-diagnostic and move from a planned maintenance system to a predictive or reliability-based system. Potential degradation or failure can be detected The useful life of a component can be maximized by leaving the equipment in service if it meets the desired performance standards Savings on the potential Health Safety and Environment (HSE) consequences Reduce the refinery downtime and optimize asset utilization Process unit monitoring and information visibility across the enterprise allows for optimization of unit operations Improve the information flow across the enterprise using a role-based view. Facilitate collaboration across the enterprise and leverage existing talent regardless of their physical location. For example, an expert in one part of the world can remotely have access to operational conditional data of machinery and equipment in a remote refinery and perform remote diagnostics. The increase in margin is the ultimate goal of IM and by increasing availability of plant one can see greater top-line benefits. By reducing intake of the plant, there is a growth in bottom line. Thus the business case for IM comes from the quantitative savings that can be achieved on a per barrel basis in the refineries. There are qualitative improvements in areas like health safety and environment. refineries to effectively predict and prevent equipment failure. Enterprise Key Performance Indicators (KPI) View: This refers to the systems, which provides a role based contextual view of the data generated by the operational instrumentation at an enterprise wide level. Intelligent Manufacturing Maturity Framework Fig 4: Maturity Framework for Refineries (Source: Zinnov Analysis) Across these three functional parameters, the refinery or enterprise maturity can be defined as follows: INTELLIGENT MANUFACTURING SOLUTION The enterprise efforts across Intelligent Manufacturing can be divided into three main functional areas: Process control and monitoring systems: The availability of monitoring systems and instrumentation in the refinery to provide the data required for operational process monitoring. Equipment Predictive Analytics Systems: The availability of systems which can interpret the operational process data of

9 Maturity Level Low Medium High Process control and monitoring systems Operations based on manually downloaded information, partial remote information availability, and no integration of data Medium maturity would include collection of the key operational data, availability of automated interfaces for the data and limited integration of the operational data. High maturity refineries would have a centralized operations database along with complete integration of the operational data available from the plant and machinery. Equipment Predictive Analytics Systems Low maturity refineries predictive systems would be limited to collection and viewing of historical data trends. Refineries with medium maturity would provide condition-based maintenance using standard performance calculation. There would be limited integration of operational data with the performance applications. A high maturity would include predictive and early failure warning measures and complete integration of real time performance information. Enterprise KPI View Low maturity organizations would not have defined KPI across the organizational structure and hence there is no means of using these for real time decision making. Organizations with medium maturity would have some well-defined KPIs and these would be communicated and available across the organization to users. A high maturity organization would have real time KPIs available across the enterprise including measures useful at the management levels. This data would be available through an interactive system like an MIS. All refineries and enterprises can be evaluated on the maturity framework defined. The refineries should aspire to move from low maturity to high maturity by adopting Intelligent Manufacturing systems. Challenges of Typical Refinery Most refineries today have medium level of maturity across the functional areas discussed. The challenges with the existing systems are the low levels of coordination across the various business value chain participants. The various stand alone applications do not communicate with each other and there is independent project development and hence under-utilization of available infrastructure and systems. Consequently, the value chain is not optimized since the evaluation of operational conditions is not happening on a real time basis. The support structure for contingencies is not available on a real time basis due to the limited visibility of the refining operational performance measures. The lack of business perspective at the operational level and vice versa results in slow response to market changes and operational incidents. Given the high volume of data, data management becomes a challenge. A holistic view of assets is not available and there is very limited collaboration across multiple assets of the same enterprise. This results in lack of knowledge capturing and sharing among various assets.

10 Overall Intelligent Manufacturing Vision Intelligent Manufacturing aims at migrating enterprises towards developing a consistent and real time refinery infrastructure view. This would enable holistic management of refining infrastructure and provide standardization of critical applications and processes across the organization. Wipro has identified the business priorities of oil and gas firms and has worked towards developing a solution enabling enterprises move towards greater maturity across the areas identified. Business Priorities Process Safety/EH&S Product Quality Meeting Customer Expectations Reliability Equipment Must Be Ready to Run Cost control Close the Gap to TQP Energy Optimization / CO2 Minimization Margin maximization Extract potential from assets Current Focus Monitoring Contextual Information Role-based visibility, dashboards and reports Collaboration via one version of the truth, everywhere Future Focus Refinery Process Optimization Local Unit Refinery-wide Supply Chain Optimization Local Refinery Regional Supply and Product Chain Enhanced Prediction Intelligent assets Equipment monitors equipment Early event warning systems Fig 5: Wipro Intelligent Manufacturing Focus (Source: Wipro Industry Research) Wipro's vision of Information on Demand System would help enterprises make the leap to a greater maturity. The benefits of such a system include improved refinery level operations including better HSE management, improved catalytic unit operations resulting in improved economic and operational performance. Blending and scheduling can be streamlined, optimizing chemical consumptions and increasing reliability of operations. Information on Demand System also allows optimization of multiple refinery operations including efficient energy and CO2 management, maintenance and equipment management. System Architecture Business Application Layer R e f i n e r i e s h a v e v a r i o u s instrumentation and stand alone systems which generates data at various levels. There is a need for integration and analysis of the data to showcase the results in particular industry specific formats. Wipro's solution offering build on the data present in the r e f i n e r y b l a c k b o x (Distributed Control System) and uses advanced analytics to provide a bespoke application which allows integration and application of this d a t a. Portal With with visual Controls Data Services Layer Enterprise Service Bus Messaging Transformation Data Sources OSI / PI Data Historians LIMS Work flow Components Routing Registry Data Adapters HSE Application Web Services Collaboration Components Metadata Repositories Configuration Information Refinery Scheduling Applications SAP/ ERP Reports Data Repositories ETL Data Adapters Material Balance Applications Fig 5: Solution Architecture for Intelligent Manufacturing Solution (Source: Wipro Industry Research)

11 Wipro, due to its business model and scale, offers clients reduced implementation cycle for this solution hence increasing the potential savings from the solution. The solution proposes to provide data visibility across levels in an enterprise. The idea is to automate and reduce manual intervention so that the limited qualified manpower within the industry can be utilized for exceptions management instead of daily operations. There are multiple sources of data in the system and there is a need for the data model to be user friendly. The solution is to provide a lot of integration through a partnered approach with the client. Currently, there is no single service offering which caters to all of these areas. The existing base systems would be integrated. Hence the Wipro installation would be an incremental investment over existing systems. Data Service Layer (DSL) The DSL will act as a single data source for all enterprise applications, pulling and orchestrating data from various sources. The DSL will have model-aware adapters to connect to diverse source systems for the data required by the enterprise applications. There would be a standards-based data reference model to abstract similar data from different sources in a consistent format. This includes data mapping services to convert the source data models to the standard specific data model. There is an event driven architecture for capturing and responding to events in real/near real time basis. The DSL provides a rule-based architecture for better management of dynamic changes in business / calculation rules. Information from different data sources for the enterprise applications can be retrieved and aggregated using calculation engines to arrive at the required KPIs. The DSL will act as a single data source for all enterprise applications, pulling and orchestrating data from various sources. The DSL will have the following capabilities: 'Model-aware' adapters to connect to diverse source systems for the data required by the enterprise applications A standards-based data reference model to abstract similar data from different sources in a consistent format Data mapping services to convert the source data models to the standard specific data model An event driven architecture for capturing/ responding to events in real/near real time A rules based architecture for better management of dynamic changes in business/ calculation rules. Orchestration capabilities to retrieve and aggregate information from different data sources for the enterprise applications Development of interfaces to retrieve the relevant data from the source systems Implementation of reference data model to standardize the data elements used across multiple applications Implementation of an event driven architecture to process the requests arising from Visualization layer Development of data transformation, enrichment and mapping services to arrive at the response for the requests arising from the Visualization layer Wipro s Capabilities

12 Data Access Services Data access service will provide the necessary connectivity to retrieve the relevant data from the data sources using modelaware OPC adapters and XML adapters. Wipro will select and implement the right set of adapters to connect to heterogeneous data sources. Business Request Services These services expose useful functionality to web users through a standard web protocol. These services provide a way to describe their interfaces in enough detail to allow a user to build a client application to utilize them. This description is usually provided in an XML document called a Web Services Description Language (WSDL) document. Enterprise Service Bus An Enterprise Service Bus provides the glue to connect the systems across heterogeneous operating systems, programming models, application types and locations. An Enterprise Service Bus is an implementation pattern which provides support for messaging, intelligent routing, mediation, web services and registries. Canonical Message Model CMM connects measurements, equipment, planning and scheduling, life cycle management, etc. throughout an enterprise and facilitates the exchange of information rather than replicating data. This model provides multiple enterprise navigation methods that allow the access of process equipment, measurements, and documents and provides a role based information capability. The CMM can be queried to find equipment and its related information and provides a base for Model Aware Adapters that can link multiple Industrial standards like ISA 95, ISA 88, OPC, and MIMOSA. Visualization Layer The visualization layer provides visual components like dash boards, KPI reports, collaboration mechanisms with respect to Intelligent Manufacturing specific business intelligence which use data service layer to access the required data. Wipro system integration services include development of portals which will help in enabling the Intelligent Manufacturing relevant features using existing visual components like PI RT WebParts, and PI process book. Wipro has also built collaborative tools like chat, audio, video etc. which enable people within enterprises leverage existing talent. The visualization layer provides Visual components like Dash boards, KPI reports, Collaboration mechanisms with respect to Smart Manufacturing specific business intelligence which use data service layer to access the required data Provide a common and consistent mechanism to access the information required Provide a consistent framework for the development fo user interfaces. Dashboards, Reporting, Collaboration Develop portals and necessary visual components which will help in enabling the Smart manufacturing relevant features Build collabrorative tools like Chat, Audio, Video etc Wipro s Capabilities

13 System Features The proposed Intelligent Manufacturing solution by Wipro would meet the functional requirements of the oil and gas industry leveraging various IT elements. Area Process control and monitoring systems Functionality Various role-based user interfaces including interactive process flow diagram screens IT elements to provide the functionality Web-based visualization; asset hierarchy data model for drill-down Remote access on demand to: Process information, across units and plants Economics and planning information ERP Operations screens Unstructured information such as drawings Data Management Services Enterprise Service Bus Reference Data Models / Data Historian Reference Meta Data Data access orchestration Equipment Predictive Analytics Systems Enterprise KPI View Analytics and calculation engines available to act on the information accessed Multiple on-screen reports for various roles and functions Role-based portals to organize and orchestrate a wide range of information and reports Off-the-shelf analytics Be-spoke analytics (e.g., regression analyses for data validation) Configurable Reporting application Web services / Portal Design Process Control and Monitoring Systems Wipro s Intelligent Manufacturing solution allows equipment performance improvement via increased visibility of asset information through remote monitoring of equipment performance, access to all information related to the asset and allows capturing of best practice knowledge. There is access to operations screens to facilitate discussions with operators on a real time basis. The solution provides access to all information related to the process units including drawings and collaboration for improved root cause analysis and event management to reduce downtime.

14 Fig 6: Energy Dashboards and Process Flow Diagram User Interfaces Equipment Predictive Analytics Systems The Intelligent Manufacturing solution would draw the real time operational data from the Distributed Control System (DCS). The analytics engine provided by Wipro consists of a combination of off-the-shelf analytics package as well as be-spoke models which would help refineries move towards condition-based maintenance by enabling statistical predictions of potential problems. The solution would allow collaboration for improved root cause analysis and event management, reducing downtime. Enterprise KPI View The visualization layer created by Wipro would include dashboards for monitoring KPI at various levels of the enterprise using standard interfaces. A web-based solution would include multiple dashboards for various stakeholders from the corporate levels (VPs) to the plant level (Plant Engineer). The plant level data can then be collated to create single window web-based portals which can be used by Intelligent Manufacturing clients. The offerings can be used for collaboration whereby people within the organization can find experts in various domains for troubleshooting. The system allows remote monitoring of process unit production and performance against various targets and provides various forms of analysis and economic logic to identify performance improvements on a continuous basis (changing production parameters).

15 Fig 7: Intelligent Manufacturing Solution: Enterprise KPI View Wipro s Role as System Integrator Support from a System Integrator / Implementer will be required across a range of activities from designing of the system, getting a pilot program in place, building to scale, testing and finally deployment. In addition to these activities, continuous post-implementation support would be provided by the system integrator. There are existing solutions in the market which are at the plant level. However, Wipro s value proposition is to aggregate the information from an individual plant level to encompass the portfolio of plants of an organization. Wipro s role in this area also includes business consulting which can determine the kind of information that is required at each level. This includes the requirement for visual representation, for example, a drop down tree structure or mapping against historical data for condition monitoring.

16 Fig 8: Intelligent Manufacturing Solution: Wipro s service offerings (Source: Wipro Industry Research) Wipro has strong domain knowledge and has worked in this area, building up expertise. The degree of customization required by most customers would be low and the offerings can be tweaked incrementally. Why Wipro Wipro helps refineries in process streamlining and performance improvement to first quartile. The following are the key areas where Wipro helps customers improve performance. Streamlining of refinery planning and scheduling and implementing tools like Aspen PIMS, Aspen Orion, Aspen MBO for improving GRM of the refinery. Faster product reconciliation and accurate movement of oil through implementation of best-in-class tools like Aspen Advisor and Aspen ATOMS. Real time refinery dash board, Intelligent Manufacturing initiative in OSI PI platform. It also provides solutions to integrate in real time ERP/SCM systems with plant floor data to enhance control and flexibility of refineries. Integrated approach to asset management to improve reliability, availability and maintenance efficiency index. Wipro, as part of global excellence in asset management, brings a unique model where maintenance execution, reliability-centered maintenance, corrosion and inspection, annual turn around, instrument protective function and ensuring safe production is integrated for maximum business benefit. Wipro s unique managed shared services in MES application support can reduce 50 percent of the support cost on a case-to-case basis. The right Oil and Gas (O&G) partner with rich IT expertise and key industry relationships To address the challenges of the O&G industry, there is need for a partner who has domain knowledge, is global and has proven expertise in upstream as well as downstream services is adept with new technologies, has partnerships within the domain as well in the technology space.

17 Wipro has been working with the O&G industry for the last decade and is well-positioned to leverage its capabilities across geographies. Helping Wipro address complexity of the industry is a team of domain experts that includes geophysicists, logging and production engineers, seismic modelers and petroleum economists in upstream, financial and energy traders in trading segment and finally experts with experience working in refineries, retail marketing and B2B marketing in downstream. This team of domain experts supports technologists in the areas of analytics, enterprise resource planning, product engineering services and portals and content management solutions to leverage technology for meeting business goals through consulting, Business Process Mapping, Application Development, Support, Testing, Migration and SOX Compliance. Wipro, with its global footprint across 25 countries, has capabilities in Europe, UK and the US and is not just hiring industry leaders and domain experts from these geographies adding capability that is relevant but is also focused on internal training. In the next 12 months, Wipro will have a team of 50 consultants to address the O&G industry needs and continue to deliver effective solutions in areas of system integration, system implementation, application development, data management, knowledge management, process integration and collaboration, leading to better decision making and improved productivity. Industry experience: 10 +: Years since the formation of a practice dedicated to the Energy and Utilities Industry 75+: Relationships with Energy & Utility companies in North America, Europe and Asia Pacific USD 400+: Million in revenues 3500+: Professionals dedicated to delivery of services to its Energy and Utilities clients Over the last decade, Wipro has been associated with key oil and gas majors such as Shell, BP, Cairn Energy and Origin Energy, Petronas and Exxon Mobil working through the lifecycle of the O&G business. The relationship has helped Wipro understand the industry, appreciate its nuances and above all, prepare itself to meet the needs of a quickly globalizing industry with in-depth domain knowledge and expertise. Wipro is the strategic partner for two of the world s five Oil Super Majors ensuring that Wipro has insight and appreciation for the future of the O&G industry. Partnerships with industry leaders such as Petris has helped Wipro understand and develop software-based solutions for the energy industry related to exploration, drilling and production, deploying its capabilities in system integration, implementation, support and helping the O&G industry unlock previously inaccessible processes and efficiencies. Wipro also leverages its technological partnerships with some of the largest solution providers to the industry which include SAP Oracle, Cisco, OSISoft, Microsoft, EMC, Informatica, etc. Wipro is clearly well-connected in the O&G ecosystem and is poised to make investments in the domain, building on its already considerable expertise. Wipro, Microsoft and Rice University have jointly conducted a research program to explore solutions to address the challenge of big crew change. When the retired employees leave the company, they will take with them a lifetime of institutional knowledge which is instrumental for the ongoing success of operations. This impacts organizations both financially and in terms of safety. Wipro has arrived at a new knowledge management strategy based on knowledge communities that consist of on-duty, off-duty, retired or alumni personnel and potential interns or partnership with university resources. The solution is based on newer collaboration based technologies such as Microsoft Sharepoint and Unified Communications that provide an enabling platform to bring this community together virtually. Wipro has also arrived at innovating incentive systems that would encourage existing employees to codify their skills and knowledge into electronic systems and to get the off-duty employees and retired personnel to invest in their personal time. A strong value proposition In an industry that is under tremendous cost pressure, Wipro has a strong value proposition for its O&G clients: it is able to bring in domain expertise from mature markets, deploy costeffective local resources that understand native market dynamics and business environments, and bring in highlyqualified and trained Indian offshore resources for development and support. The cost model is optimized to meet the complex needs of the O&G industry.

18 Other solution offerings Upstream Supply Distribution and Trading Refining & Manufacturing B2B marketing and Retail Digitization solutions Data management Document management Petro economic modeling Human Capital management High Performance Computing Demand Forecasting Supply Chain Visibility Planning workbench Transportation, Planning and Scheduling Terminal Automation Master Data Management Refinery yield/ oil movement Plant Historian HSSE Solution Planning, Scheduling and Optimization Asset Management Refinery MIS Order Management Used Oil Analysis Retail Asset Management Retail Site System Point Solution on Implementation, Integration and Maintenance of applications References Interviews with Wipro Industry Experts Interviews with Oil and Gas Professional Wipro Industry Research International Energy Agency New York Mercantile Exchange Centre for Intelligent Maintenance Systems Zinnov Knowledge Base and Analysis For more information on this paper, please contact Mr. Bhavesh Storewala at Visit Wipro at

19 About the Authors Wipro is the first PCMM Level 5 and SEI CMMi Level 5 certified IT Services Company globally. Wipro provides comprehensive IT solutions and services (including systems integration, IS outsourcing, package implementation, software application development and maintenance) and Research & Development services (hardware and software design, development and implementation) to corporations globally. Wipro's unique value proposition is further delivered through our pioneering Offshore Outsourcing Model and stringent Quality Processes of SEI and Six Sigma. About Wipro Council for Industry Research The Wipro Council for Industry Research comprising of domain and technology experts from the organization aims to address the needs of customers by specifically looking at innovative strategies that will help them gain competitive advantage in the market. The Council in collaboration with leading academic institutions and industry bodies studies market trends to equip organization with insights that facilitate their IT and business strategies. For more information please visit /industryresearch ALL RIGHTS RESERVED Copyright Wipro Technologies. All rights reserved. No part of this document may be reproduced, stored in a retrieval system, transmitted in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without express written permission from Wipro Technologies. Specifications subject to change without notice. All other trademarks mentioned herein are the property of their respective owners. Specifications subject to change without notice.