Energy Savings Opportunities and Energy Efficiency Performance Indicators for a Serial Production Line. - Michael Brundage; Qing Chang 001; Shiyao Wang; Shaw C. Feng; Guoxian Xiao; Jorge Arinez 001 (APMS (1), 2013)

Utilizing energy opportunity windows and energy profit bottlenecks to reduce energy consumption per part for a serial production line. - Michael P. Brundage; Qing Chang 001; Yang Li 014; Jorge Arinez 001; Guoxian Xiao (CASE, 2014)

Energy Efficiency Management of an Integrated Serial Production Line and HVAC System. - Michael P. Brundage; Qing Chang 001; Yang Li 014; Guoxian Xiao; Jorge Arinez 001 (IEEE Trans Autom. Sci. Eng., 2014)

Evaluating and reducing production impact on HVAC cooling load. - Michael P. Brundage; Qing Chang 001; Jorge Arinez 001; Jon Longtin; Tao He (CASE, 2015)

Market Demand Oriented Data-Driven Modeling for Dynamic Manufacturing System Control. - Yang Li 014; Qing Chang 001; Michael P. Brundage; Stephan Biller; Jorge Arinez 001; Guoxian Xiao (IEEE Trans. Syst. Man Cybern. Syst., 2015)

An Overview of a Smart Manufacturing System Readiness Assessment. - Kiwook Jung; Boonserm Kulvatunyou; Sang Su Choi; Michael P. Brundage (APMS, 2016)

Sustainable Manufacturing Performance Indicators for a Serial Production Line. - Michael P. Brundage; Qing Chang 001; Yang Li 014; Jorge Arinez 001; Guoxian Xiao (IEEE Trans Autom. Sci. Eng., 2016)

Implementing a Real-Time, Energy-Efficient Control Methodology to Maximize Manufacturing Profits. - Michael P. Brundage; Qing Chang 001; Yang Li 014; Jorge Arinez 001; Guoxian Xiao (IEEE Trans. Syst. Man Cybern. Syst., 2016)

Hybrid datafication of maintenance logs from AI-assisted human tags. - Thurston Sexton; Michael P. Brundage; Michael Hoffman; K. C. Morris 001 (IEEE BigData, 2017)

Maturity Models and Tools for Enabling Smart Manufacturing Systems: Comparison and Reflections for Future Developments. - Anna De Carolis; Marco Macchi; Boonserm Kulvatunyou; Michael P. Brundage; Sergio Terzi (PLM, 2017)

A Review of Current Machine Learning Techniques Used in Manufacturing Diagnosis. - Toyosi Toriola Ademujimi; Michael P. Brundage; Vittaldas V. Prabhu (APMS (1), 2017)

Improvement Strategies for Manufacturers Using the MESA MOM Capability Maturity Model. - Quanri Li; Michael Brundage; Boonserm (Serm) Kulvatunyou; Dennis Brandl; Sang Do Noh (APMS (1), 2017)

Toward Semi-autonomous Information - Extraction for Unstructured Maintenance Data in Root Cause Analysis. - Michael Sharp; Thurston Sexton; Michael P. Brundage (APMS (1), 2017)

An event-based analysis of condition-based maintenance decision-making in multistage production systems. - Yang Li 014; Qirong Tang; Qing Chang 001; Michael P. Brundage (Int. J. Prod. Res., 2017)

Event-Based Supervisory Control for Energy Efficient Manufacturing Systems. - Yang Li 014; Qing Chang 001; Jun Ni 002; Michael P. Brundage (IEEE Trans Autom. Sci. Eng., 2018)

A Visual Analytics Approach for the Diagnosis of Heterogeneous and Multidimensional Machine Maintenance Data. - Xiaoyu Zhang 014; Takanori Fujiwara; Senthil K. Chandrasegaran; Michael P. Brundage; Thurston Sexton; Alden Dima; Kwan-Liu Ma (PacificVis, 2021)

Online Maintenance Prioritization Via Monte Carlo Tree Search and Case-Based Reasoning. - Michael Hoffman; Eunhye Song; Michael Brundage; Soundar Kumara (J. Comput. Inf. Sci. Eng., 2022)

Discovering critical KPI factors from natural language in maintenance work orders. - Madhusudanan Navinchandran; Michael Sharp; Michael P. Brundage; Thurston Sexton (J. Intell. Manuf., 2022)

Online Improvement of Condition-Based Maintenance Policy via Monte Carlo Tree Search. - Michael Hoffman; Eunhye Song; Michael P. Brundage; Soundar Kumara (IEEE Trans Autom. Sci. Eng., 2022)

Demystifying the Accuracy-Interpretability Trade-Off: A Case Study of Inferring Ratings from Reviews. - Pranjal Atrey; Michael P. Brundage; Min Wu; Sanghamitra Dutta (CoRR, 2025)