Analytics-driven asset management

Asset-intensive businesses across industries rely on physical assets to deliver services to their customers, and effective asset management is critical to the businesses. Today, businesses may make use of enterprise asset-management (EAM) solutions for many asset-related processes, ranging from the core asset-management functions to maintenance, inventory, contracts, warranties, procurement, and customer-service management. While EAM solutions have transformed the operational aspects of asset management through data capture and process automation, the decision-making process with respect to assets still heavily relies on institutional knowledge and anecdotal insights. Analytics-driven asset management is an approach that makes use of advanced analytics and optimization technologies to transform the vast amounts of data from asset management, metering, and sensor systems into actionable insight, foresight, and prescriptions that can guide decisions involving strategic and tactical assets, as well as customer and business models.

[1]  Y. S. Sherif,et al.  Optimal maintenance models for systems subject to failure–A Review , 1981 .

[2]  Keith C. C. Chan,et al.  Discovering Association Patterns in Large Spatio-temporal Databases , 2006, Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06).

[3]  M. Kulldorff A spatial scan statistic , 1997 .

[4]  Ramakrishnan Srikant,et al.  Fast Algorithms for Mining Association Rules in Large Databases , 1994, VLDB.

[5]  R. A Fenner,et al.  Approaches to sewer maintenance: a review , 2000 .

[6]  Jean-Pierre Villeneuve,et al.  Modeling Water Pipe Breaks—Three Case Studies , 2003 .

[7]  Jiawei Han,et al.  Discovery of Spatial Association Rules in Geographic Information Databases , 1995, SSD.

[8]  Philip M. Long,et al.  Predicting Electricity Distribution Feeder Failures Using Machine Learning Susceptibility Analysis , 2006, AAAI.

[9]  Jun Wei Liu,et al.  Mining Association Rules in Spatio‐Temporal Data: An Analysis of Urban Socioeconomic and Land Cover Change , 2005, Trans. GIS.

[10]  John F. Roddick,et al.  Association mining , 2006, CSUR.

[11]  Jon Røstum,et al.  Statistical modelling of pipe failures in water networks , 2000 .

[12]  Tomasz Imielinski,et al.  Mining association rules between sets of items in large databases , 1993, SIGMOD Conference.

[13]  Mike Rees,et al.  5. Statistics for Spatial Data , 1993 .

[14]  Michael Masin,et al.  Diversity Maximization Approach for Multiobjective Optimization , 2008, Oper. Res..

[15]  Rehan Sadiq,et al.  Probabilistic risk analysis of corrosion associated failures in cast iron water mains , 2004, Reliab. Eng. Syst. Saf..

[16]  Haimonti Dutta,et al.  A process for predicting manhole events in Manhattan , 2009, Machine Learning.

[17]  Tim Strauss,et al.  A GIS-Integrated Intelligent System for Optimization of Asset Management for Maintenance of Roads and Bridges , 2002, IEA/AIE.

[18]  Rommert Dekker,et al.  Applications of maintenance optimization models : a review and analysis , 1996 .

[19]  Ramakrishnan Srikant,et al.  Fast algorithms for mining association rules , 1998, VLDB 1998.

[20]  Bert Huang,et al.  Maximum Entropy Density Estimation with Incomplete Presence-Only Data , 2009, AISTATS.

[21]  Noel A Cressie,et al.  Statistics for Spatial Data. , 1992 .

[22]  J. Pearl Causality: Models, Reasoning and Inference , 2000 .

[23]  Daniel Straub,et al.  A framework for the asset integrity management of large deteriorating concrete structures , 2009 .

[24]  Balvant Rajani,et al.  Comprehensive review of structural deterioration of water mains: statistical models , 2001 .

[25]  Richard A. Davis,et al.  Introduction to time series and forecasting , 1998 .

[26]  Edward P. K. Tsang,et al.  Fast local search and guided local search and their application to British Telecom's workforce scheduling problem , 1997, Oper. Res. Lett..

[27]  Hongzhou Wang,et al.  A survey of maintenance policies of deteriorating systems , 2002, Eur. J. Oper. Res..

[28]  David Lesaint,et al.  Dynamic workforce management , 1997 .

[29]  Balvant Rajani,et al.  Comprehensive review of structural deterioration of water mains: physically based models , 2001 .

[30]  Patrick Prosser,et al.  Solving Vehicle Routing Problems Using Constraint Programming and Metaheuristics , 2000, J. Heuristics.