KPIs for Asset Management: A Pump Case Study

The integration of multiple data sources and the convergence of process control systems and business intelligence layer such as the enterprise resource planning (ERP) are paving the way for important progress in plant operation optimization. Numerous companies offer “Analytics Services” to leverage this newly available mine of data but applications still appear to be limited to certain specific types of large plants. Key Performance Indicators (KPIs) is arguably the most used approach to make sense of large and complex systems in a wide variety of fields and its applicability to industrial operations is more and more common, to the extent that standardization of KPIs has become a major topic for the International Organization for Standardization (ISO). While the KPI standard ISO 22400 focuses on KPIs for manufacturing operations management at the plant level, the scope of this thesis is to bring it to the first layer of the control system: the equipment. In addition to being part of the quest for operational excellence and energy efficiency, bringing KPIs to the asset level is an important step towards integration of the different layers of the automation pyramid, integrating in particular control and scheduling. Developed within the frame of the new generation of Operations Management Software for the process industries, this work presents a case study on the most widely used assets in the field – pumps, based on operational data of different plants in the Oil & Gas and Chemicals industries

Development of systematic technique for energy and property integration in batch processes

The increasing consumption of energy, generation of waste as well as higher cost of fresh resources and waste treatment systems are the important driving forces for developing efficient, environmentally friendly and economic resource conservation techniques in the process industries. Process integration is being recognized as an useful systematic strategy for resource conservation and waste minimization. Up to date, less research works have been investigated on heat and property integration and these works are only focused on continuous processes.Since the application of batch processes is increasingly popular due to the development of technology-intensive industries such as pharmacy, fine chemistry and foods, it is necessary to consider both heat and property integration in batch processes simultaneously. In this thesis, a new mixed integer nonlinear programming (MINLP) mathematical model is introduced to synthesize a property-based heat integrated resource conservation networks (HIRCNs) for batch processes. A source-HEN-sink superstructure is constructed to embed all possible network configurations. Then, an MINLP model that consists of propertybased resource conservation network (RCN) and heat exchanger network (HEN) models is developed.In the proposed model, the property-based RCN model is formulated based on supertargeting approach while HEN model is formulated via automated targeting method (ATM). The optimization objective is to minimize total annualized cost (TAC) for a batch process system. This includes the operating cost of fresh resources, hot and cold utilities as well as the capital cost of storage tanks. To demonstrate the proposed approach, three case studies were solved. Based on the optimized results, the proposed simultaneous targeting approach for property-based HIRCNs is more effective in term of TAC for HIRCNs than the presented sequential targeting approach

Integrated management of chemical processes in a competitive environment

El objetivo general de esta Tesis es mejorar el proceso de la toma de decisiones en la gestión de cadenas de suministro, tomando en cuenta principalmente dos diferencias: ser competitivo considerando las decisiones propias de la cadena de suministro, y ser competitivo dentro de un entorno global. La estructura de ésta tesis se divide en 4 partes principales: La Parte I consiste en una introducción general de los temas cubiertos en esta Tesis (Capítulo 1). Una revisión de la literatura, que nos permite identificar las problemáticas asociadas al proceso de toma de decisiones (Capítulo 2). El Capítulo 3 presenta una introducción de las técnicas y métodos de optimización utilizados para resolver los problemas propuestos en esta Tesis. La Parte II se enfoca en la integración de los niveles de decisión, buscando mejorar la toma de decisiones de la propia cadena de suministro. El Capítulo 4 presenta una formulación matemática que integra las decisiones de síntesis de procesos y las decisiones operacionales. Además, este capítulo presenta un modelo integrado para la toma de decisiones operacionales incluyendo las características del control de procesos. El Capítulo 5 muestra la integración de las decisiones del nivel táctico y el operacional, dicha propuesta está basada en el conocimiento adquirido capturando la información relacionada al nivel operacional. Una vez obtenida esta información se incluye en la toma de decisiones a nivel táctico. Finalmente en el capítulo 6 se desarrolla un modelo simplificado para integrar múltiples cadenas de suministro. El modelo propuesto incluye la información detallada de las entidades presentes en una cadena de suministro (suministradores, plantas de producción, distribuidores y mercados) introduciéndola en un modelo matemático para su coordinación. La Parte III propone la integración explicita de múltiples cadenas de suministro que tienen que enfrentar numerosas situaciones propias de un mercado global. Asimismo, esta parte presenta una nueva herramienta de optimización basada en el uso integrado de métodos de programación matemática y conceptos relacionados a la Teoría de Juegos. En el Capítulo 7 analiza múltiples cadenas de suministro que cooperan o compiten por la demanda global del mercado. El Capítulo 8 incluye una comparación entre el problema resuelto en el Capítulo anterior y un modelo estocástico, los resultados obtenidos nos permiten situar el comportamiento de los competidores como fuente exógena de la incertidumbre típicamente asociada la demanda del mercado. Además, los resultados de ambos Capítulos muestran una mejora sustancial en el coste total de las cadenas de suministro asociada al hecho de cooperar para atender de forma conjunta la demanda disponible. Es por esto, que el Capítulo 9 presenta una nueva herramienta de negociación, basada en la resolución del mismo problema (Capítulo 7) bajo un análisis multiobjetivo. Finalmente, la parte IV presenta las conclusiones finales y una descripción general del trabajo futuro.This Thesis aims to enhance the decision making process in the SCM, remarking the difference between optimizing the SC to be competitive by its own, and to be competitive in a global market in cooperative and competitive environments. The structure of this work has been divided in four main parts: Part I: consists in a general introduction of the main topics covered in this manuscript (Chapter I); a review of the State of the Art that allows us to identify new open issues in the PSE (Chapter 2). Finally, Chapter 3 introduces the main optimization techniques and methods used in this contribution. Part II focuses on the integration of decision making levels in order to improve the decision making of a single SC: Chapter 4 presents a novel formulation to integrate synthesis and scheduling decision making models, additionally, this chapter also shows an integrated operational and control decision making model for distributed generations systems (EGS). Chapter 5 shows the integration of tactical and operational decision making levels. In this chapter a knowledge based approach has been developed capturing the information related to the operational decision making level. Then, this information has been included in the tactical decision making model. In Chapter 6 a simplified approach for integrated SCs is developed, the detailed information of the typical production‐distribution SC echelons has been introduced in a coordinated SC model. Part III proposes the explicit integration of several SC’s decision making in order to face several real market situations. As well, a novel formulation is developed using an MILP model and Game Theory (GT) as a decision making tool. Chapter 7 includes the tactical and operational analysis of several SC’s cooperating or competing for the global market demand. Moreover, Chapter 8 includes a comparison, based on the previous results (MILP‐GT optimization tool) and a two stage stochastic optimization model. Results from both Chapters show how cooperating for the global demand represent an improvement of the overall total cost. Consequently, Chapter 9 presents a bargaining tool obtained by the Multiobjective (MO) resolution of the model presented in Chapter 7. Finally, final conclusions and further work have been provided in Part IV.Postprint (published version