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|a يعرف التحول الرقمي Digital Transformation في الصناعة بأنه عملية استخدام التكنولوجيا الرقمية Digital technology بهدف تحقيق التميز في أداء الشركات، وتعزيز قدرتها التنافسية. يؤثر التحول الرقمي في استراتيجيات الشركات من خلال خمسة مجالات رئيسية هي: الزبائن، والمنافسة، والبيانات، والابتكار، والقيمة. وهي المجالات التي يمكن للتقنيات الرقمية تغيير القواعد التي يجب أن تعمل الشركات من خلالها لتحقيق النجاح المنشود. يتركز الهدف الرئيسي للتحول الرقمي في تعزيز القدرة التنافسية للشركات، من خلال تحسين كفاءة استخدام الموارد، وتعظيم الإنتاجية، وذلك باستخدام التكنولوجيات الرقمية مثل الذكاء الاصطناعي Artificial Intelligent (AI)، والفضاء السحابي Cloud system، والحوسبة السحابية Cloud Computing، وتحليلات البيانات الضخمة Big Data Analytics، والروبوتات التكيفية Adaptive Robotics، والواقع المعزز Augmented Reality، وإنترنت الأشياء الصناعي Industrial Internet of Things (IoT).
|b Refining and petrochemical industries are faced with various challenges, such as changing, market scenarios, global competition, increased regulatory pressure, decreased oil products demand, and increase in operating and maintenance cost. To cope with these challenges, refining and petrochemical industry is trying to improve its performance through looking for available methods to minimise costs and ensure high competitiveness. The purpose of this study is to shed light on the role of digital transformation in achieving the operational excellence in refining and petrochemical industry. The study includes three chapters. The first chapter reviews the most important digital technologies applied in the refining and petrochemical industry, such as the industrial Internet of Things, Digital Twin, Augmented Reality, Cloud Computing, Machine Learning, Artificial Intelligence and Robotics. The second chapter explains the role of applying the digital technologies in improving the performance business operations of refining and petrochemical industry. These include predictive analytics to forecast equipment and asset health and optimize maintenance of critical equipment and AI-based technology to increase the efficiency of operations and facilitate lower carbon footprint. The third chapter addresses the success factors behind developing a digital transformation strategy and build bridges in several areas, which are related with information, data, processes, technologies, human aspects and much more. The third chapter also reviews the states of applying digital transformation. The chapter also addresses there are several initiatives emerging in the refining and petrochemical industry related to digital transformation in the Arab countries, most of these initiatives are centered in OAPEC member countries which have export oriented refining and petrochemical complexes. The objectives of these initiatives are enhancing the operational excellence to continue their role as strategic suppliers to the international markets, through improving plant availability, and minimizing unscheduled shutdown of the units, optimizing maintenance of critical equipment, and reducing the carbon footprint. The study includes several case studies of applying digital technologies in refining and petrochemical industry in some world regions, and Arab countries. These case studies provide lessons learned from the experiences of others in applying digital transformation in its operational aspects. The study concluded that the digital transformation could bring a significant benefit to the refining and petrochemical companies. One of the most important factors that enable refining companies to improve its performance is embedding digital capabilities in all aspects of their operations. Furthermore, digital technologies could help refiners to reduce costs, improve revenues and margins and make their work environments more efficient, reliable, and safe. Also, the study recommends that the OAPEC’s member countries must issue the necessary regulations for sharing historical data between different refining and petrochemical companies to be used for predictive analysis which can forecast equipment and asset health and helps the operator to predict the failure of an equipment before it happens.
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