Download or read book Data Analytics and Artificial Intelligence for Inventory and Supply Chain Management written by Dinesh K. Sharma and published by Springer Nature. This book was released on 2022-11-08 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book considers new analytics and AI approaches in the areas of inventory control, logistics, and supply chain management. It provides valuable insights for the retailers and managers to improve business operations and make more realistic and better decisions. It also offers a number of smartly designed strategies related to inventory control and supply chain management for the optimal ordering and delivery policies. The book further uses detailed models and AI computing approaches for demand forecasting to planning optimization and digital execution tracking. One of its key features is use of real-life examples, case studies, practical models to ensure adoption of new solutions, data analytics, and AI-lead automation methodologies are included.The book can be utilized by retailers and managers to improve business operations and make more accurate and realistic decisions. The AI-based solution, agnostic assessment, and strategy will support the companies for better alignment and inventory control and capabilities to create a strategic road map for supply chain and logistics. The book is also useful for postgraduate students, researchers, and corporate executives. It addresses novel solutions for inventory to real-world supply chain and logistics that retailers, practitioners, educators, and scholars will find useful. It provides the theoretical and applicable subject matters for the senior undergraduate and graduate students, researchers, practitioners, and professionals in the area of artificial intelligent computing and its applications in inventory and supply chain management, inventory control, and logistics.

Download or read book Artificial Intelligence in Supply Chain Management written by Calvin Klein and published by Cuvillier Verlag. This book was released on 2023-10-06 with total page 95 pages. Available in PDF, EPUB and Kindle. Book excerpt: As Artificial Intelligence (AI) continues to revolutionize industries worldwide, its omnipresence becomes increasingly evident in Supply Chain Management (SCM). This Consortium Study, conducted by the Institute of Supply Chain Management (ISCMHSG) at the University of St.Gallen and its promotional association, examines the integration of AI in SCM and aims to address the gap between expectations and reality. The study provides a knowledge foundation to assist supply chain managers in developingrealistic expectations of this technology. Considering the rapid advancement of AI technologies and their potential impact on SCM, this study explores the current state of AI in SCM and analyzes the disparity between expectations and reality. Through a comprehensive market analysis of AI solutions offered in SCM, opportunities for improvement are identified. The study focuses on aligning expectations and reality by fostering a better understanding of the capabilities of AI in SCM. Additionally, the study investigates obstacles to successful AI integration, including data quality, integration challenges, and unrealistic expectations of potential benefits. Through the collaborative efforts of the participating organizations, this Consortium Study offers a collective understanding of the current state of AI in SCM. It serves as a valuable resource for industry professionals, and academia facilitating the successful integration of AI and driving operational excellence in SCM.

Download or read book Data Driven Technologies and Artificial Intelligence in Supply Chain written by Mahesh Chand and published by CRC Press. This book was released on 2023-11-23 with total page 291 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights the importance of data-driven technologies and artificial intelligence in supply chain management. It covers important concepts such as enabling technologies in Industry 4.0, the impact of artificial intelligence, and data-driven technologies in lean manufacturing. "Provides solutions to solve complex supply chain management issues using artificial intelligence and data-driven technologies" Emphasizes the impact of a data-driven supply chain on quality management "Discusses applications of artificial intelligence, and data-driven technologies in the service industry, and lean manufacturing" Highlights the barriers to implementing artificial intelligence in small and medium enterprises Presents a better understanding of different risks such as procurement risks, process risks, demand risks, transportation risks, and operational risks The book comprehensively discusses the applications of artificial intelligence and data-driven technologies in supply chain management for diverse fields such as service industries, manufacturing industries, and healthcare. It further covers the impact of artificial intelligence and data-driven technologies in managing the FMGC supply chain. It will be a valuable resource for senior undergraduate, graduate students, and academic researchers in diverse fields including electrical engineering, electronics and communications engineering, industrial engineering, manufacturing engineering, production engineering, and computer engineering.

Download or read book Supply Chain Analytics written by Kurt Y. Liu and published by Springer Nature. This book was released on 2022-04-07 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: This innovative new core textbook, written by an experienced professor and practitioner in supply chain management, offers a business-focused overview of the applications of data analytics and machine learning to supply chain management. Accessible yet rigorous, this text introduces students to the relevant concepts and techniques needed for data analysis and decision making in modern supply chains and enables them to develop proficiency in a popular and powerful programming software. Suitable for use on upper-level undergraduate, postgraduate and MBA courses in supply chain management, it covers all of the major supply chain processes, including managing supply and demand, warehousing and inventory control, transportation and route optimization. Each chapter comes with practical real-world examples drawn from a range of business contexts, including Amazon and Starbucks, case study discussion questions, computer-assisted exercises and programming projects.

Download or read book Utilization of AI Technology in Supply Chain Management written by Pandey, Digvijay and published by IGI Global. This book was released on 2024-03-01 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: The surge in digital transformation and the integration of innovative technologies into manufacturing processes have given rise to a pressing issue in supply chain management. Businesses are in dire need of solutions to navigate this complexity and harness the true potential of intelligent supply chains. Utilization of AI Technology in Supply Chain Management is a comprehensive guide tailored for academic scholars seeking to unravel the mysteries of artificial intelligence (AI) and machine learning (ML) in the context of supply chain management. Amid the hype surrounding AI and ML, there exists a critical need to bridge the gap between human expertise and technological advancements. Utilization of AI Technology in Supply Chain Management addresses this necessity by delving into real-world instances where teams have successfully employed these innovative technologies to enhance supply chain performance, reduce inventory, and optimize routes. The adoption of AI and ML is not just a trend; it is the cornerstone of digital acceleration initiatives, making it imperative for scholars to understand and leverage these technologies effectively.

Download or read book AI and Machine Learning Impacts in Intelligent Supply Chain written by Pandey, Binay Kumar and published by IGI Global. This book was released on 2024-01-29 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: Businesses are facing an unprecedented challenge - the urgent need to adapt and thrive in a world where intelligent factories and supply chains are the new norm. The digital transformation of supply chains is essential for staying competitive, but it is a complex journey fraught with uncertainties. How can organizations harness the power of emerging technologies like Artificial Intelligence (AI) and Machine Learning (ML) to increase profitability, cut supply chain costs, elevate customer service, and optimize their networks? The answers to these questions are crucial for business survival and success. AI and Machine Learning Impacts in Intelligent Supply Chain is a groundbreaking book that offers a comprehensive solution to the challenges posed by the Industry 4.0 revolution. This book is your indispensable guide to navigating the intricate world of supply chain digital transformation using innovative technologies. It provides real-world examples and insights that illustrate how AI and ML are the keys to solving complex supply chain problems, from inventory management to route optimization and beyond. Whether you are an academic scholar seeking to delve into the impact of AI and ML on supply chain management or a business leader striving to gain a competitive edge, this book is tailored to meet your needs.

Download or read book The Oxford Handbook of Supply Chain Management written by Thomas Y. Choi and published by Oxford University Press. This book was released on 2021-08-30 with total page 815 pages. Available in PDF, EPUB and Kindle. Book excerpt: Supply chain management contends with structures and processes for delivering goods and services to customers. It addresses the core functions of connected businesses to meet downstream demand. This innovative volume provides an authoritative and timely guide to the overarching issues that are ubiquitous throughout the supply chain. In particular, it addresses emerging issues that are applicable across supply chains--such as data science, financial flows, human capital, internet technologies, risk management, cyber security, and supply networks. With chapters from an international roster of leading scholars in the field, the Oxford Handbook of Supply Chain Management is a necessary resource for all students and researchers of the field as well as for forward-thinking practitioners.

Download or read book Innovative Supply Chain Management via Digitalization and Artificial Intelligence written by Kumaresan Perumal and published by Springer Nature. This book was released on 2022-04-06 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the impact of artificial intelligence (AI) and machine learning (ML) models on supply chain operations in industry 4.0. The chapters illustrate the AI and ML models for all functional areas of operations in SCM. The book also includes examples using ML models like handling supply-to-demand imbalances, triggering automated responses, and reinforcing customer relationships. It describes the evolution of blockchain technology coupled with the ability to automate business logic for the transparency of goods, infrastructure, products, and licenses in software. The book also includes case studies that provide a problem statement and industry overcome by applying ML and AI technologies. This book is suitable for undergraduates, postgraduates, industrial professionals, business executives, entrepreneurs, and freelancers to encourage practical learning on AI and ML algorithms in SCM 4.0. Additionally, this book will provide computer science and information system professionals with the latest technologies embedded in the corporate world.

Download or read book Big Data Analytics in Supply Chain Management written by Iman Rahimi and published by CRC Press. This book was released on 2020-12-20 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: In a world of soaring digitization, social media, financial transactions, and production and logistics processes constantly produce massive data. Employing analytical tools to extract insights and foresights from data improves the quality, speed, and reliability of solutions to highly intertwined issues faced in supply chain operations. From procurement in Industry 4.0 to sustainable consumption behavior to curriculum development for data scientists, this book offers a wide array of techniques and theories of Big Data Analytics applied to Supply Chain Management. It offers a comprehensive overview and forms a new synthesis by bringing together seemingly divergent fields of research. Intended for Engineering and Business students, scholars, and professionals, this book is a collection of state-of-the-art research and best practices to spur discussion about and extend the cumulant knowledge of emerging supply chain problems.

Download or read book Big Data Driven Supply Chain Management written by Nada R. Sanders and published by Pearson Education. This book was released on 2014 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master a complete, five-step roadmap for leveraging Big Data and analytics to gain unprecedented competitive advantage from your supply chain. Using Big Data, pioneers such as Amazon, UPS, and Wal-Mart are gaining unprecedented mastery over their supply chains. They are achieving greater visibility into inventory levels, order fulfillment rates, material and product delivery... using predictive data analytics to match supply with demand; leveraging new planning strengths to optimize their sales channel strategies; optimizing supply chain strategy and competitive priorities; even launching powerful new ventures. Despite these opportunities, many supply chain operations are gaining limited or no value from Big Data. In Big Data Driven Supply Chain Management, Nada Sanders presents a systematic five-step framework for using Big Data in supply chains. You'll learn best practices for segmenting and analyzing customers, defining competitive priorities for each segment, aligning functions behind strategy, dissolving organizational boundaries to sense demand and make better decisions, and choose the right metrics to support all of this. Using these techniques, you can overcome the widespread obstacles to making the most of Big Data in your supply chain -- and earn big profits from the data you're already generating. For all executives, managers, and analysts interested in using Big Data technologies to improve supply chain performance.

Download or read book Data Science for Supply Chain Forecasting written by Nicolas Vandeput and published by Walter de Gruyter GmbH & Co KG. This book was released on 2021-03-22 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: Using data science in order to solve a problem requires a scientific mindset more than coding skills. Data Science for Supply Chain Forecasting, Second Edition contends that a true scientific method which includes experimentation, observation, and constant questioning must be applied to supply chains to achieve excellence in demand forecasting. This second edition adds more than 45 percent extra content with four new chapters including an introduction to neural networks and the forecast value added framework. Part I focuses on statistical "traditional" models, Part II, on machine learning, and the all-new Part III discusses demand forecasting process management. The various chapters focus on both forecast models and new concepts such as metrics, underfitting, overfitting, outliers, feature optimization, and external demand drivers. The book is replete with do-it-yourself sections with implementations provided in Python (and Excel for the statistical models) to show the readers how to apply these models themselves. This hands-on book, covering the entire range of forecasting—from the basics all the way to leading-edge models—will benefit supply chain practitioners, forecasters, and analysts looking to go the extra mile with demand forecasting. Events around the book Link to a De Gruyter Online Event in which the author Nicolas Vandeput together with Stefan de Kok, supply chain innovator and CEO of Wahupa; Spyros Makridakis, professor at the University of Nicosia and director of the Institute For the Future (IFF); and Edouard Thieuleux, founder of AbcSupplyChain, discuss the general issues and challenges of demand forecasting and provide insights into best practices (process, models) and discussing how data science and machine learning impact those forecasts. The event will be moderated by Michael Gilliland, marketing manager for SAS forecasting software: https://youtu.be/1rXjXcabW2s

Download or read book Supply Chain Management in the Big Data Era written by Chan, Hing Kai and published by IGI Global. This book was released on 2016-11-04 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: Technological advancements in recent years have led to significant developments within a variety of business applications. In particular, data-driven research provides ample opportunity for enterprise growth, if utilized efficiently. Supply Chain Management in the Big Data Era is an authoritative reference source for the latest scholarly material on the implementation of big data analytics for improved operations and supply chain processes. Highlighting emerging strategies from different industry perspectives, this book is ideally designed for managers, professionals, practitioners, and students interested in the most recent research on supply chain innovations.

Download or read book Applications of Emerging Technologies and AI ML Algorithms written by Manoj Kumar Tiwari and published by Springer Nature. This book was released on 2023-07-01 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides practical insights into applications of the state-of-the-art of Machine Learning and Artificial Intelligence (AI) for solving intriguing and complex problems in procurement and supply chain management. The application domain includes perishable food supply chain, steel price prediction, electric vehicle charging infrastructure design, contract price negotiation, reverse logistics network design, and demand forecasting. Further, the book highlights the advanced topics in the procurement field, like AI in green procurement and e-procurement in the pharma sector. Furthermore, the book covers applications of well-established methodologies such as heuristics, optimization, game theory, and MCDM based on the nature of the problem. The inclusion of the vaccine supply chain digital twin and blockchain-based procurement signals the significance of the book. This book is a comprehensive guide for industry professionals to understand the power of data analytics, enabling them to improve efficiency and effectiveness in the procurement and supply chain sectors.

Download or read book The Fourth Industrial Revolution Implementation of Artificial Intelligence for Growing Business Success written by Allam Hamdan and published by Springer Nature. This book was released on 2021-04-11 with total page 483 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the implementation of AI for growing business, and the book includes research articles and expository papers on the applications of AI on decision-making, health care, smart universities, public sector and digital government, FinTech, and RegTech. Artificial Intelligence (AI) is a vital and a fundamental driver for the Fourth Industrial Revolution (FIR). Its influence is observed at homes, in the businesses and in the public spaces. The embodied best of AI reflects robots which drive our cars, stock our warehouses, monitor our behaviors and warn us of our health, and care for our young children. Some researchers also discussed the role of AI in the current COVID-19 pandemic, whether in the health sector, education, and others. On all of these, the researchers discussed the impact of AI on decision-making in those vital sectors of the economy.

Download or read book Data Science for Supply Chain Forecast written by Nicolas Vandeput and published by Independently Published. This book was released on 2018-11-12 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Science for Supply Chain Forecast Data Science for Supply Chain Forecast is a book for practitioners focusing on data science and machine learning; it demonstrates how both are closely interlinked in order to create an advanced forecast for supply chain. As one will discover in this book, artificial intelligence (AI) & machine learning (ML) are not simply a question of coding skills. Using data science in order to solve a problem requires a scientific mindset more than coding skills. The story behind these models is one of experimentation, of observation and of constant questioning; a true scientific method must be applied to supply chain. In the data science field as well as that of the supply chain, simple questions do not come with simple answers. In order to resolve these questions, one needs to be both a scientist as well as to use the correct tools. In this book, we will discuss both. Is this Book for me? This book has been written for supply chain practitioners, forecasters and analysts who are looking to go the extra mile. You do not need technical IT skills to start using the models of this book. You do not need a dedicated server or expensive software licenses: you solely need your own computer. You do not need a PhD in mathematics: mathematics will only be utilized as a tool to tweak and understand the models. In the majority of the cases - especially when it comes to machine learning - a deep understanding of the mathematical inner workings of a model will not be necessary in order to optimize it and understand its limitations. Reviews "In an age where analytics and machine learning are taking on larger roles in the business forecasting, Nicolas' book is perfect solution for professionals who need to combine practical supply chain experience with the mathematical and technological tools that can help us predict the future more reliably." Daniel Stanton - Author, Supply Chain Management For Dummies "Open source statistical toolkits have progressed tremendously over the last decade. Nicolas demonstrates that these toolkits are more than enough to start addressing real-world forecasting challenges as found in supply chains. Moreover, through its hands-on approach, this book is accessible to a large audience of supply chain practitioners. The supply chain of the 21st century will be data-driven and Nicolas gets it perfectly." Joannes Vermorel - CEO Lokad "This book is unique in its kind. It explains the basics of Python using basic traditional forecasting techniques and shows how machine learning is revolutionizing the forecasting domain. Nicolas has done an outstanding job explaining a technical subject in an easily accessible way. A must-read for any supply chain professional." Professor Bram Desmet - CEO Solventure "This book is before anything a practical and business-oriented "DIY" user manual to help planners move into 21st-century demand planning. The breakthrough comes from several tools and techniques available to all, and which thanks to Nicolas' precise and concrete explanations can now be implemented in real business environments by any "normal" planner. I can confirm that Nicolas' learnings are based on real-life experience and can tremendously help on improving top and bottom lines." Henri-Xavier Benoist - VP Supply Chain Bridegstone EMEA

Download or read book Computational Intelligence Techniques for Sustainable Supply Chain Management written by Sanjoy Kumar Paul and published by Elsevier. This book was released on 2024-06-03 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sustainable supply chain management involves integrating environmentally and financially viable practices into the complete supply chain lifecycle, from product design and development to material selection and sourcing, manufacturing, packaging, transportation, and distribution. A sustainable supply chain ensures balance between economic, social, and environmental performances – such as better assurance of human rights, ethical work practices, carbon footprint reduction, waste management, and resource efficiency. Computational Intelligence Techniques for Sustainable Supply Chain Management presents state-of-the-art computational intelligence techniques and applications for supply chain sustainability issues and logistic problems, filling the gap between general textbooks on sustainable supply chain management and more specialized literature dealing with methods for computational intelligence. This book focuses on addressing problems in advanced topics in the sustainable supply chain, and will appeal to practitioners, managers, researchers, academicians, students, and professionals interested in sustainable logistics, sustainable procurement, sustainable manufacturing, sustainable inventory and production management, sustainable scheduling, sustainable transportation, and sustainable network design. Serves as a reference on computational intelligence–enabled sustainable supply chains for graduate students in computer/data science, industrial engineering, industrial ecology, and business Explores key topics in sustainable supply chain informatics, that is, heuristics, metaheuristics, robotics, simulation, machine learning, big data analytics and artificial intelligence Provides a foundation for industry leaders and professionals to understand recent and cutting-edge methodologies and technologies in the domain of sustainable supply chain powered by computational intelligence techniques

Download or read book Data Analytics and Business Intelligence written by Vincent Charles and published by CRC Press. This book was released on 2023-06-15 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: Business Analytics (BA) is an evolving phenomenon that showcases the increasing importance of using huge volumes of data to generate value for businesses. Advances in BA have offered great opportunities for organisations to improve, innovate, and develop existing or new processes, products, and services. BA is the process of transforming data into actionable insight by using statistical and mathematical analysis, descriptive, prescriptive, and predictive models, machine learning, information systems and network science methods, among others, along with a variety of data, expert knowledge, and fact-based management to support better and faster decision-making. BA and Business Intelligence (BI) generate capabilities for companies to compete in the market effectively and has become one of the main functional areas in most companies. BA tools are used in diverse ways, for example, to identify consumer behaviour patterns and market trends, to derive valuable insights on the performance of stocks, to find information on the attrition rate of employees, to analyse and solve healthcare problems, to offer insight into inventory management and supply chain management, to analyse data from social networks, and to infer traffic behaviour and develop traffic management policy, among others. BA and BI have become one of the most popular research areas in academic circles, as well as in the industry, driven by the increasing demand in the business world. This book aims to become a stimulus for innovative business solutions covering a wide range of aspects of business analytics, such as management science, information technology, descriptive, prescriptive, and predictive models, machine learning, network science, mathematical and statistical techniques. The book will encompass a valuable collection of chapters exploring and discussing computational frameworks, practices, and applications of BA that can assist industries and relevant stakeholders in decision-making and problem-solving exercises, with a view to driving competitive advantage.