M. A. Rahim

58 papers receiving 1.2k citations

Peers

M. A. Rahim
Comparison fields: 5 of 71
  • Statistics, Probability and Uncertainty 1.1k
  • Medical Laboratory Technology 92
  • Statistics and Probability 377
  • Industrial and Manufacturing Engineering 327
  • Management Information Systems 280
Replace Erwin M. Saniga with:
Erwin M. Saniga United States
Chao‐Yu Chou Taiwan
Lonnie C. Vance United States
Smiley W. Cheng Canada
W. K. Chiu Hong Kong
K. Govindaraju New Zealand
Cai Wen Zhang China
Muhammad Azam Pakistan
Bahram Sadeghpour Gildeh Iran
Alireza Faraz Belgium
M. A. Rahim relative to Erwin M. Saniga United States Erwin M. Saniga's profile →
Citations per field
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Erwin M. Saniga · 1×
Citations per year

Countries citing papers authored by M. A. Rahim

Since Specialization
Citations

This map shows the geographic impact of M. A. Rahim'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 M. A. Rahim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. A. Rahim more than expected).

Fields of papers citing papers by M. A. Rahim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M. A. Rahim. 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 M. A. Rahim. The network helps show where M. A. Rahim may publish in the future.

Co-authors

The 25 scholars most cited alongside M. A. Rahim, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with M. A. Rahim Line = papers co-authored together M. A. Rahim links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 59 papers — load more, or switch the sort, to bring in the rest.

#Work
1 199396
2 200180
3 200463
4 200458
5 201754
6 200651
7 198950
8 200647
9 200146
10 201346
11 200840
12 200539
13 198738
14 201835
15 200435
16 198834
17 200433
18 199729
19 201428
20 198826

About M. A. Rahim

M. A. Rahim is a scholar working on Statistics, Probability and Uncertainty, Industrial and Manufacturing Engineering, Management Science and Operations Research, Management Information Systems and Statistics and Probability, having authored 59 papers that have together received 1.3k indexed citations. Recurring topics across this work include Advanced Statistical Process Monitoring (40 papers), Scientific Measurement and Uncertainty Evaluation (16 papers), Manufacturing Process and Optimization (13 papers), Optimal Experimental Design Methods (13 papers), Advanced Statistical Methods and Models (9 papers), Supply Chain and Inventory Management (9 papers), Fault Detection and Control Systems (6 papers) and Bird parasitology and diseases (4 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (1.1k citations), Medical Laboratory Technology (92 citations), Statistics and Probability (377 citations), Industrial and Manufacturing Engineering (327 citations) and Management Information Systems (280 citations). M. A. Rahim has collaborated with scholars based in Canada, Saudi Arabia and Brazil. Frequent co-authors include Antônio Fernando Branco Costa, Pradeep Banerjee, Michael B. C. Khoo, Wai Chung Yeong, Mohamed Ben‐Daya, R.S. Lashkari, Khaled S. Al‐Sultan, Hiroshi Ohta, Ming Ha Lee and Marcela Aparecida Guerreiro Machado. Their work appears in journals such as Quality and Reliability Engineering International, The International Journal of Advanced Manufacturing Technology, Computers & Industrial Engineering, Journal of Quality Technology and Engineering Optimization.

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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