Massimo Pacella

1.5k total citations
57 papers, 1.1k citations indexed

About

Massimo Pacella is a scholar working on Industrial and Manufacturing Engineering, Control and Systems Engineering and Mechanical Engineering. According to data from OpenAlex, Massimo Pacella has authored 57 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Industrial and Manufacturing Engineering, 15 papers in Control and Systems Engineering and 13 papers in Mechanical Engineering. Recurrent topics in Massimo Pacella's work include Fault Detection and Control Systems (12 papers), Manufacturing Process and Optimization (12 papers) and Advanced Statistical Process Monitoring (11 papers). Massimo Pacella is often cited by papers focused on Fault Detection and Control Systems (12 papers), Manufacturing Process and Optimization (12 papers) and Advanced Statistical Process Monitoring (11 papers). Massimo Pacella collaborates with scholars based in Italy, United States and Denmark. Massimo Pacella's co-authors include Bianca Maria Colosimo, Quirico Semeraro, A. Anglani, Kamran Paynabar, Antonio Grieco, Nicola Senin, Marco Grasso, Jionghua Jin, Tullio Tolio and Hao Yan and has published in prestigious journals such as Technometrics, Sensors and Sustainability.

In The Last Decade

Massimo Pacella

54 papers receiving 1.1k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Massimo Pacella Italy 19 378 367 296 261 170 57 1.1k
Shing I. Chang United States 23 351 0.9× 356 1.0× 286 1.0× 349 1.3× 148 0.9× 60 1.6k
Chaoqun Duan China 18 141 0.4× 200 0.5× 322 1.1× 333 1.3× 139 0.8× 60 1.4k
Lee J. Wells United States 16 183 0.5× 370 1.0× 157 0.5× 139 0.5× 70 0.4× 43 833
Jun‐Geol Baek South Korea 16 127 0.3× 290 0.8× 287 1.0× 144 0.6× 244 1.4× 94 910
Yifan Zhou China 21 194 0.5× 82 0.2× 311 1.1× 181 0.7× 77 0.5× 79 1.1k
Jinhua Mi China 22 915 2.4× 65 0.2× 337 1.1× 250 1.0× 240 1.4× 60 2.0k
Haiping Zhu China 22 140 0.4× 350 1.0× 1.3k 4.3× 730 2.8× 241 1.4× 80 2.2k
Haobo Qiu China 31 1.5k 3.9× 151 0.4× 229 0.8× 246 0.9× 491 2.9× 90 2.6k
Michele Compare Italy 21 338 0.9× 138 0.4× 387 1.3× 115 0.4× 84 0.5× 58 1.2k
Kim Phuc Tran France 27 873 2.3× 199 0.5× 532 1.8× 71 0.3× 567 3.3× 85 1.9k

Countries citing papers authored by Massimo Pacella

Since Specialization
Citations

This map shows the geographic impact of Massimo Pacella's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Massimo Pacella with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Massimo Pacella more than expected).

Fields of papers citing papers by Massimo Pacella

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Massimo Pacella. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Massimo Pacella. The network helps show where Massimo Pacella may publish in the future.

Co-authorship network of co-authors of Massimo Pacella

This figure shows the co-authorship network connecting the top 25 collaborators of Massimo Pacella. A scholar is included among the top collaborators of Massimo Pacella based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Massimo Pacella. Massimo Pacella is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Pacella, Massimo, et al.. (2025). A Scalable Framework for Sensor Data Ingestion and Real-Time Processing in Cloud Manufacturing. Algorithms. 18(1). 22–22. 4 indexed citations
2.
3.
Gupta, Swati, et al.. (2024). Sequential sampling for functional estimation via Sieve. Quality and Reliability Engineering International. 40(6). 3253–3279.
4.
Zhang, Zihan, et al.. (2024). Federated Multiple Tensor-on-Tensor Regression (FedMTOT) for Multimodal Data Under Data-Sharing Constraints. Technometrics. 66(4). 548–560. 1 indexed citations
5.
6.
Pacella, Massimo, et al.. (2023). Utilizing Mixture Regression Models for Clustering Time-Series Energy Consumption of a Plastic Injection Molding Process. Algorithms. 16(11). 524–524. 3 indexed citations
7.
Gahrooei, Mostafa Reisi, et al.. (2023). Robust tensor-on-tensor regression for multidimensional data modeling. IISE Transactions. 56(1). 43–53. 2 indexed citations
8.
Demartini, Melissa, et al.. (2022). An Agent-Based Approach for Make-To-Order Master Production Scheduling. Processes. 10(5). 921–921. 2 indexed citations
9.
Pacella, Massimo, et al.. (2022). Topic Modeling for Automatic Analysis of Natural Language: A Case Study in an Italian Customer Support Center. Algorithms. 15(6). 204–204. 7 indexed citations
10.
Tonelli, Flavio, et al.. (2021). Cyber-physical systems (CPS) in supply chain management: from foundations to practical implementation. Procedia CIRP. 99. 598–603. 16 indexed citations
11.
Demartini, Melissa, et al.. (2021). A Review of Production Planning Models: emerging features and limitations compared to practical implementation. Procedia CIRP. 104. 588–593. 5 indexed citations
12.
Pacella, Massimo, et al.. (2020). Fault Diagnosis by Multisensor Data: A Data-Driven Approach Based on Spectral Clustering and Pairwise Constraints. Sensors. 20(24). 7065–7065. 7 indexed citations
13.
Grasso, Marco, Bianca Maria Colosimo, & Massimo Pacella. (2014). Profile monitoring via sensor fusion: the use of PCA methods for multi-channel data. International Journal of Production Research. 52(20). 6110–6135. 56 indexed citations
14.
Colosimo, Bianca Maria, Massimo Pacella, & Nicola Senin. (2014). Multisensor data fusion via Gaussian process models for dimensional and geometric verification. Precision Engineering. 40. 199–213. 61 indexed citations
15.
Paynabar, Kamran, Jionghua Jin, & Massimo Pacella. (2013). Monitoring and diagnosis of multichannel nonlinear profile variations using uncorrelated multilinear principal component analysis. IIE Transactions. 45(11). 1235–1247. 72 indexed citations
16.
Pacella, Massimo & Quirico Semeraro. (2011). Monitoring roundness profiles based on an unsupervised neural network algorithm. Computers & Industrial Engineering. 60(4). 677–689. 27 indexed citations
17.
Colosimo, Bianca Maria & Massimo Pacella. (2009). A comparison study of control charts for statistical monitoring of functional data. International Journal of Production Research. 48(6). 1575–1601. 55 indexed citations
18.
Colosimo, Bianca Maria, et al.. (2006). Identification of Manufacturing Processes Signature by a Principal Component based Approach. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 1–6. 1 indexed citations
19.
Colosimo, Bianca Maria & Massimo Pacella. (2005). On the identification of manufacturing processes' signature. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 1–6. 4 indexed citations
20.
Anglani, A., et al.. (2003). A CAD environment for the numerical simulation of servo pneumatic actuator systems. 17. 593–598. 2 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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