Sarah Sharples (97 results)

Hardcover. Condition: Very Good. No Jacket. First Edition. 8vo - over 7¾" - 9¾" tall. VG in cloth backed boards (rubbing to corners, some foxing) large 8vo 44pp Biography concerning the author's parents, Abbie Hall and Stephen Sharples. Stephen Sharples was a founding member of the American Chemical Society.Illustrated by With 4 photographs.…

Condition: As New. Unread book in perfect condition.

Condition: New.

Condition: New.

Paperback. Condition: New. With the development of sensor technology, wireless communications, big data, and machine learning, there is an increasing interest in technologies and solutions that assess and predict the state of equipment and assets within various industrial settings. These technologies aim to collect information from multiple sources about infrastructure asset status. Then, through current and historical data analysis, this configuration of technologies delivers intelligence on current and future asset status to a maintenance operator or manager to inform optimal maintenance decision-making. These technologies are known under different terms - remote condition monitoring, e-maintenance, prognostic systems, predictive maintenance, and smart or intelligent infrastructure. Despite the promise of remote condition monitoring and predictive technologies, there is a growing concern with such technologies because they can be difficult or impractical to use.Understanding and mitigating potential human factors issues could ensure that such vast investments are not wasted. This book considers, in depth, the challenges placed on users of current and future condition monitoring systems. Its primary focus is to understand the cognitive processes, including managing alarms, interpreting data, and collaborating with automation. The book describes a range of human factors methods that can be used to understand the current and future functioning of people and technology in an enhanced maintenance and asset monitoring context. The book also presents a framework for describing these issues systematically and presents the resulting design considerations to increase the effectiveness of individual operators and organisations as a whole.…

Condition: New.

Condition: As New. Unread book in perfect condition.

Paperback. Condition: Good. Good - . In good condition.

Condition: New. In English.

Condition: very_good. Supports Goodwill of Silicon Valley job training programs. The cover and pages are in very good condition! The cover and any other included accessories are also in very good condition showing some minor use. The spine is straight, there are no rips tears or creases on the cover or the pages.…

Paperback. Condition: Brand New. 154 pages. 9.18x6.12x9.21 inches. In Stock.

Hardcover. Condition: New. Brand new book, sourced directly from publisher. Dispatch time is 7-8 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Condition: New.

Condition: Good. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Condition: As New. Unread book in perfect condition.

Condition: New.

Condition: New. pp. 180.

Condition: As New. Unread book in perfect condition.

Condition: New. pp. 180.

Condition: New.

Condition: New.

Paperback. Condition: New. With the development of sensor technology, wireless communications, big data, and machine learning, there is an increasing interest in technologies and solutions that assess and predict the state of equipment and assets within various industrial settings. These technologies aim to collect information from multiple sources about infrastructure asset status. Then, through current and historical data analysis, this configuration of technologies delivers intelligence on current and future asset status to a maintenance operator or manager to inform optimal maintenance decision-making. These technologies are known under different terms - remote condition monitoring, e-maintenance, prognostic systems, predictive maintenance, and smart or intelligent infrastructure. Despite the promise of remote condition monitoring and predictive technologies, there is a growing concern with such technologies because they can be difficult or impractical to use.Understanding and mitigating potential human factors issues could ensure that such vast investments are not wasted. This book considers, in depth, the challenges placed on users of current and future condition monitoring systems. Its primary focus is to understand the cognitive processes, including managing alarms, interpreting data, and collaborating with automation. The book describes a range of human factors methods that can be used to understand the current and future functioning of people and technology in an enhanced maintenance and asset monitoring context. The book also presents a framework for describing these issues systematically and presents the resulting design considerations to increase the effectiveness of individual operators and organisations as a whole.…

Condition: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

Condition: New.

Paperback. Condition: New. Brand new book, sourced directly from publisher. Dispatch time is 7-8 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Hardcover. Condition: New. Brand new book, sourced directly from publisher. Dispatch time is 7-8 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Condition: New. In English.

Condition: New.

Condition: New.

Condition: New. In English.