Profit Maximization Techniques for Operating Chemical Plants. Sandip K. Lahiri
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СКАЧАТЬ maximization, business objectives also venture out to the fields of sustainability, reliability, low environment impact, etc. With the advent of faster computers, online optimization, advance process control, real‐time plant monitoring, online equipment fault diagnosis, big data‐based process parameter data analytics, artificial intelligence (AI), and internet of things (IOT)‐based sensors and technology have found their way into process industries.

      During this turbulent time, people and industries that cannot change their way of doing business quickly gradually become obsolete. Many industries and technologies that were running 25 years ago no longer exist as they could not cope with the changing requirements of modern times. After globalization, chemical industries needed to purchase their raw material and sell their finished products to the international market at the international market price. They have to compete with cheap raw material prices of OPEC countries, cheap manpower costs of China, big capacity of the Middle East plants, etc. Most of the traditional industries could not cope with this uneven competition and gradually became obsolete. Hence, to survive in today's business environment, industry needs to find new ways of doing business. Therefore, a completely new way of thinking and optimization is required to maximize profit. A complete paradigm shift in mindset is the need of the hour.

      Profit maximization is one of the prime goals of every management team of process industries across the globe.

      Profit maximization in running chemical plants is itself a huge challenge that needs to be addressed by holistic vision and procedures. What is the objective of profit maximization in the process industries? It is not simply waste or loss minimization and it is not simply energy and raw material minimization. It is much bigger than that. The ultimate goal of profit maximization is to use every resource available to the process industry in the most efficient manner so that dollar per hour generation is maximized and sustained over years. To achieve this goal, energy, raw materials, equipment, manpower, processes, and environment as well as the mindset of the people must be aligned and be holistically optimized.

      Most of the time, engineers and managers working in process industries tackle this problem with a fragmented approach. Process engineers try to optimize process parameters, production engineers try to meet a production target rate, energy managers want to minimize energy consumption, maintenance engineers try to increase equipment uptime, reliability engineers try to increase equipment and process an on‐stream factor, safety engineers try to reduce accidents and incidents, etc. All of them try to increase profit in their own way without paying attention to what other people are doing. Sometimes, their objectives are contradictory. However, a profit maximization project needs to holistically combine all their effort in the most efficient way so that sustainability and profit maximization are achieved.

      Over the years, engineers working in process industries have believed that reducing loss and waste is the only way to achieve efficiency. Thus, to them, energy efficiency means to identify and rectify steam leaks, faulty steam traps, damage insulation in steam lines, less flaring, cleaning of fouled exchangers, etc. In the last decade they focused on these basic old housekeeping parts of energy efficiency. These are the techniques of past decades. With the advent of faster computers and data historians, every minute many process parameter data are stored, with the availability of offline process simulators (like Aspen, Pro II, etc.) and online advanced process control (APC) and real‐time optimization (RTO) applications. With the advance of artificial intelligence‐based data analytics a complete new generation of profit maximization tools and techniques are currently available. This book attempts to highlight some of these proven new generation tools, which slowly being introduced in progressive process industries. Adaptions of these new techniques in process industries need a mindset change of engineers and management. The real challenge becomes: how can a mindset change of management be made so that new generation techniques can be quickly applied to generate profit. How can these new generation tools and techniques be learnt and adapted quickly? The challenge boils down to: which methods should be selected, how can they be tailor‐made to fit them into specific applications, and how can they be implemented for specific circumstances?

      However, there are no dedicated effective books available to discuss a basic roadmap to utilize various intelligent tools and techniques, provide practical methods to implement them on the shop floor, and explain industrial application procedures.

      This book has been written to fill this gap with the following people in mind: practicing process or chemical engineers, production engineers, supervisors, and senior technicians working in chemical, petrochemical, pharmaceuticals, paper and pulp, oil and gas companies and petroleum refineries across the globe. This book will also become particularly useful for large numbers of managers, general managers, top level senior executives, and senior technical service consultants whose main jobs include strategic planning and implementation of various optimization projects to increase profit in chemical process industries. Undergraduate and postgraduate chemical engineering students and business students who want to pursue careers in the chemical field will also greatly benefit from this book. The book is aimed at providing various intelligent computational tools to engineers and managers working in CPI who face challenges and are looking for new ways to increase profit in running chemical plants. This book aims to convey concepts, theories, and methods in a straightforward and practical manner.

      The book will present various intelligent computation techniques covering profit optimization strategy, application methodology, supporting structures, and assessment methods. In short, it will describe completely new ways and techniques to maximize profit for process plants and how to sustain profit improvement benefits.

      Short on background theory and long on step‐by‐step application procedures, it covers everything plant process engineers and technical managers need to know about identifying, building, deploying, and managing profit improvement applications in their companies. Readers are able to take away new ways to increase profit in their current plant, background computational tools and techniques for identifying profit improvement opportunities, and analysis, optimization, and monitoring procedures that are required to identify, assess, implement, and sustain profit improvement opportunities.

      In chemical process industries (CPIs), profit maximization is attained in many fragmented ways. Energy managers in a plant try to increase profit by increasing energy efficiency, production engineers increase profit by pushing the plant to its highest possible capacity, control engineers try to optimize the plant in real time by advance process control, maintenance engineers try to maximize the critical single line equipment availability by doing proper preventive and predictive maintenance, reliability engineers try to reduce the failure rate by proper inspection, the human resource (HR) department tries to reduce manpower cost and increase employee's productivity, safety engineers try to minimize the incidence and accident rate, etc., and many people try to maximize profit in a multi‐dimensional fragmented way. However, all of the above approaches are not independent but are deeply interrelated and sometimes conflicting. СКАЧАТЬ