Predictive Safety Analytics : Reducing Risk through Modeling and Machine Learning

Robert Stevens

ISBN 10: 1032424389 / ISBN 13: 9781032424385

Published by CRC Press, 2023

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - Nearly all our safety data collection and reporting systems are backwardlooking: incident reports; dashboards; compliance monitoring systems; and so on. This book shows how we can use safety data in a forward-looking, predictive sense.Predictive Safety Analytics: Reducing Risk through Modeling and Machine Learning contains real use cases where organizations have reduced incidents by employing predictive analytics to foresee and mitigate future risks. It discusses how Predictive Safety Analytics is an opportunity to break through the plateau problem where safety rate improvements have stagnated in many organizations. The book presents how the use of data, coupled with advanced analytical techniques, including machine learning, has become a proven and successful innovation. Emphasis is placed on how the book can 'meet you where you are' by illuminating a path to get there, starting with simple data the organization likely already has. Highlights of the book are the real examples and case studies that will assist in generating thoughts and ideas for what might work for individual readers and how they can adapt the information to their particular situations.This book is written for professionals and researchers in system reliability, risk and safety assessment, quality control, operational managers in selected industries, data scientists, and ML engineers. Students taking courses in these areas will also find this book of interest to them.

Seller Inventory # 9781032424385

Bibliographic Details

• Title: Predictive Safety Analytics : Reducing Risk through Modeling and Machine Learning
• Publisher: CRC Press
• Publication Date: 2023
• Language: English
• ISBN 10: 1032424389
• ISBN 13: 9781032424385
• Binding: Buch
• Condition: Neu
• Dimensions: 222W x 145H x 9D millimeters 222 millimeters width by 145 millimeters height by 9 millimeters depth
• Weight: 268 grams

About this title

Synopsis

Nearly all our safety data collection and reporting systems are backwardlooking: incident reports; dashboards; compliance monitoring systems; and so on. This book shows how we can use safety data in a forward-looking, predictive sense.

Predictive Safety Analytics: Reducing Risk through Modeling and Machine Learning contains real use cases where organizations have reduced incidents by employing predictive analytics to foresee and mitigate future risks. It discusses how Predictive Safety Analytics is an opportunity to break through the plateau problem where safety rate improvements have stagnated in many organizations. The book presents how the use of data, coupled with advanced analytical techniques, including machine learning, has become a proven and successful innovation. Emphasis is placed on how the book can “meet you where you are” by illuminating a path to get there, starting with simple data the organization likely already has. Highlights of the book are the real examples and case studies that will assist in generating thoughts and ideas for what might work for individual readers and how they can adapt the information to their particular situations.

This book is written for professionals and researchers in system reliability, risk and safety assessment, quality control, operational managers in selected industries, data scientists, and ML engineers. Students taking courses in these areas will also find this book of interest to them.

About the Author

Rob is part of the leadership team at First Analytics, a boutique analytical consulting firm. First Analytics designs and implements predictive analytics and machine learning solutions. The firm services multiple industries with many applications. With an enabling engagement model, the firm teams up with its clients to build their in-house capabilities and systems. In his role as Vice President at First Analytics, Rob helps companies develop and execute programs to cultivate their analytics competency. He brings experience to bear stemming from more than thirty years as an analytics professional, starting as an econometrician. His career has consisted of consulting, product development, client service, technical, and sales roles within software, consulting, and market research firms. Rob has participated in or led safety analytics implementations in the railroad, utility, oil and gas, and manufacturing industries. He has spoken on predictive safety analytics in venues such as National Safety Council congresses, an OSHA safety conference, human and organizational learning conferences, manufacturing forums, private analytics consortiums, and conferences and webinars sponsored by software companies.