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Everything you do is determined. So who is behind the wheel? You are.
Managers face an infinite range of situations and problems that involve bringing materials and information together to produce and deliver goods and services to customers. In Hopps solid, practical introduction to manufacturing and supply chain dynamics, managers learn how to use the scientific approachto understand why systems behave the way they doas an effective way to deal with almost any scenario they may face. Written in a reader-friendly style, the text includes useful examples from manufacturers as well as service providers, presents the key concepts that underlie the behavior of operations systems in a largely non-mathematical way, contains illustrations and analogies to everyday life, links theory to practice, and reinforces the learning process with end-of-chapter Questions for Thought.
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.
**This is the chapter slice "Food Chains Gr. 1-5" from the full lesson plan "Hands-On - Life Science"** Spark curiosity in this great big world of ours by discovering how everything works and lives together with our Hands-On Life Science resource for grades 1-5. Combining Science, Technology, Engineering, Art, and Math, this resource aligns to the STEAM initiatives and Next Generation Science Standards. Dive right in by getting a firsthand look at ecosystems and building your own terrarium. Make information sheets for plants and animals, complete with hand-made drawings. Design your own food chain while grasping the knowledge about producers, consumers and decomposers. See what traits you inherited from your parents while learning about different adaptations. Learn about life cycles by studying a caterpillar's marvelous transformation into a butterfly. Explore your own brain with memory games and tracking your heart rate and dreams while you sleep. Each concept is paired with hands-on experiments and comprehension activities to ensure your students are engaged and fully understand the concepts. Reading passages, graphic organizers, before you read and assessment activities are included.
Chain Mobility and Progress in Medicine, Pharmaceuticals, and Polymer Science and Technology covers the core fundamentals and applications of chain movement, chain mobility, segmental mobility, segmental dynamics, and chain orientation in polymer science, medicine, pharmaceuticals, and other disciplines. The book starts by defining principal terms, then looks at the work of Pierre-Gilles de Gennes and his 1991 Nobel Prize in Physics for his work on polymer-chain motion. From there the book discusses the different mechanisms of chain motion of macromolecular substances, the conditions under which chains move, and the effects of these movements on properties of materials, such as chain alignment, chain orientation, creation of free volume, dimensional stability, and more. The final chapters provide insight on analytical methods of chain movement, chain movement phenomena in different polymers, and various fields of application. All concepts, findings, and applications are discussed in easy-to-understand language stripped of disciplinary slang, making the book accessible to researchers and practitioners across a variety of scientific fields. Discusses various chain motion mechanisms such as bond fluctuation, Brill transition, chain diffusion, and more and how these can be applied in the development of cutting-edge products Looks at conditions under which chains move and the effects these movements have on the properties of materials Provides examples of research and technological aspects of chain movements as they relate to analytical methods used for studies, different polymers, and various fields of application
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
The demand and supply chain planning process for manufacturers, distributors, and retailers has evolved over the years. It has gone from a disjointed, unconnected, slow, inaccurate, fairly manual set of processes to an integrated, timely process enabled by the use and coordination of highly trained people, lean, agile processes, and cutting-edge technology. To make this set of processes work effectively, one has to fully understand and appreciate that there is an "art and science" aspect to the process which can take years of education and experience to fully understand. Essentially, this book will offer the reader a chance to fully understand the interconnected set of processes in a "best-practice" application. Furthermore, examples and cases will be used to illustrate its practical application in today’s complex global supply chain. In addition, readers will understand and be able to apply and articulate the concepts, tools, and techniques used in the efficient supply of goods and services in today’s changing global economy. It will help them to learn how businesses, through their supply chain, work both internally and with their trading partners – both upstream and downstream – to build strong relationships and integrate demand and supply planning activities across the supply chain to deliver customer value efficiently and effectively. They will learn about the tools and technologies enabling integration, and the critical drivers and key metrics of supply chain performance.