臺灣博碩士論文加值系統

可程式邏輯控制器在現今工業及未來發展都是不可或缺的一環，尤其在智慧工廠、智慧居家科技或自動化生產線，甚至機械製造機台等。本研究以透過與專家學者訪談可程式邏輯控制器對於未來開發趨勢得出對編輯介面、語法、中央處理器、記憶體單元及通訊模組等較為需要探討，透過模糊德懷術分析得到區域/全域標籤設定及連接設定改成視覺化呈現會更容易操作，可考慮增加Python、JAVA、LabVIEW及Scratch等語法讓更多人學習利用，指令處理速度的提升，程式容量及擴充容量在原本基礎上增加一倍或改由使用者自行安裝決定，通訊模組改成乙太網路雙通道、與外網及無線網路連結等，皆可使整體運用更佳，另透過模糊層次分析進行重要性分析得知通訊模組最為重要，其次是中央處理及增加Python與介面視覺化，再來則是程式容量增加、最後LabVIEW及擴充容量提升和JAVA及Scratch等語法，最後以技術地圖呈現可程式邏輯控制器軟硬體發展之趨勢圖及提出可程式邏輯控制器整體發展趨勢建議，提供業者開發、研究之參考，以符合工業發展所需。

Programmable Logic Controllers (PLCs) are an indispensable component in current industrial applications and future developments, especially in smart factories, smart home technologies, automated production lines, and even mechanical manufacturing equipment. This research, through interviews with experts and scholars, identified that the future development trends of PLCs need to focus on aspects such as editing interfaces, syntax, central processing units, memory units, and communication modules.
Through fuzzy Delphi method analysis, this study found that changing the regional/global tag settings and connection settings to visual representations would make operations easier. Consideration should be given to adding syntaxes like Python, JAVA, LabVIEW, and Scratch to allow more people to learn and utilize PLCs. Other improvements include enhancing instruction processing speed, doubling the program capacity and expansion capacity from the original basis or allowing users to decide on installation, and upgrading communication modules to dual-channel Ethernet with external network and wireless network connections. These changes can improve overall utilization.
Furthermore, through fuzzy analytic hierarchy process (FAHP) for importance analysis, it was determined that communication modules are the most important, followed by central processing and the addition of Python along with interface visualization. Next in importance are increased program capacity, then LabVIEW, enhanced expansion capacity, and finally JAVA and Scratch syntaxes.
Lastly, a technology roadmap is presented to illustrate the trends in PLC hardware and software development, and recommendations for overall PLC development trends are proposed. These insights are provided as a reference for industry developers and researchers to meet the needs of industrial development.

目次
摘要 I
Abstract II
謝誌 IV
目次 V
表目錄 VII
圖目錄 IX
第一章 緒論 1
1-1研究背景與動機 1
1-2研究目的 4
1-3名詞釋義 4
第二章 文獻與理論探討 6
2-1可程式邏輯控制器 6
2-2物聯網 14
2-3技術地圖 16
2-4專家訪談法 19
2-5模糊德懷術 23
2-6模糊層次分析 25
第三章 研究架構與方法 27
3-1研究流程架構 27
3-2研究範圍與限制 28
3-3研究方法與設計 29
3-4研究構面 38
第四章 研究結果與分析 39
4-1建置問卷與評估項目 39
4-2模糊德懷術問卷統計與分析 47
4-3模糊層次分析統計與分析 56
4-4技術地圖 60
第五章 結論 64
參考文獻 67
附錄 81
附錄一 模糊德懷術問卷 81
附錄二 模糊層次分析問卷 86

 
表目錄
表 1 FX系列沿革 10
表 2 訪談結構類型 21
表3 9分制量表 35
表4 語意三角模糊量表 37
表 5 模糊德懷術受測專家學者基本資料 39
表 6 模糊德懷術受測專家學者基本資料 續 40
表 7 模糊德懷術 43
表 8 修正後模糊德懷術問卷 44
表 9 修正後模糊德懷術問卷 續1 45
表 10 修正後模糊德懷術問卷 續2 46
表 11 模糊德懷術統計表-編輯介面 47
表 12 模糊德懷術統計表-編輯介面 續 48
表 13 模糊德懷術統計表-語法 49
表 14 模糊德懷術統計表-語法 續 50
表 15 模糊德懷術統計表-中央處理器 51
表 16 模糊德懷術統計表-記憶體單元 52
表 17 模糊德懷術統計表-通訊模組 54
表 18 模糊層次分析統計表-構面 56
表 19 模糊層次分析統計表-軟體 57
表 20 模糊層次分析統計表-硬體 58
表 21 模糊層次分析全域統計表 59
 
圖目錄
圖1 工業發展演變 3
圖2 可程式邏輯控制器構造示意圖 6
圖3 系統層次圖 8
圖4 可程式邏輯控制器外觀圖 11
圖5 可程式邏輯控制器配置說明 11
圖6 編輯軟體對應機種 12
圖7 編輯軟體語法 12
圖8 模組配置圖 13
圖 9 物聯網應用層面 16
圖 10 Motorola 汽車用電晶體收音機產品開發規劃 17
圖 11 技術地圖與主體、對象與環境關係示意圖 18
圖 12 研究流程架構圖 27
圖 13 專家訪談流程圖 29
圖 14 模糊德懷術流程圖 30
圖 15 樂觀與保守三角模糊化模型 32
圖 16 模糊層次分析流程圖 34
圖 17 研究構面圖 38
圖 18 修正後研究構面圖 42
圖 19 可程式邏輯控制器技術地圖 60
圖 20 可程式邏輯控制器發展順序圖 62

[1]戚玉樑, ‘語意網技術在工業4.0的角色與應用’, 機械工業雜誌, no. 437, pp. 75–84, 2019.
[2]黃以宜, 胡曉, 蔡承佐,和范盛維, ‘工業4.0通訊技術與應用’, 機械工業雜誌, no. 413, pp. 17–29, 2017.
[3]A. Derakhti, E. D. R. Santibanez Gonzalez, and A. Mardani, ‘Industry 4.0 and Beyond: A Review of the Literature on the Challenges and Barriers Facing the Agri-Food Supply Chain’, Sustainability, vol. 15, no. 6, p. 5078, Mar. 2023, doi: 10.3390/su15065078.
[4]H. J. Geldenhuys, A. C. Brent, and I. H. De Kock, ‘SSUIT Smart Sustainable Urban Infrastructure Transitioning’, Sustainability, vol. 15, no. 18, p. 13729, Sep. 2023, doi: 10.3390/su151813729.
[5]S. Hasan, Z. Işık, and G. Demirdöğen, ‘Evaluating the Contribution of Lean Construction to Achieving Sustainable Development Goals’, Sustainability, vol. 16, no. 8, p. 3502, Apr. 2024, doi: 10.3390/su16083502.
[6]S. O. Ametepey, C. Aigbavboa, W. D. Thwala, and H. Addy, ‘The Impact of AI in Sustainable Development Goal Implementation: A Delphi Study’, Sustainability, vol. 16, no. 9, p. 3858, May 2024, doi: 10.3390/su16093858.
[7]Rockwell Automation, [Online]. Available: https://www.rockwellautomation.com/
[8]張鴻, ‘「工業5.0」與亞太區域產業及社會永續發展的契機’, 臺灣經濟研究月刊, vol. 46, no. 2, pp. 21–28, Feb. 2023, doi: 10.29656/TERM.202302_46(2).0004.
[9]陳昌憲, 莊柏逸, 和鍾逸呈, ‘AI智慧擷取－PLC自動轉譯技術’, 電腦與通訊, no. 183, pp. 47–50, Jun. 2020.
[10]B. S. Alsaeed, D. V. L. Hunt, and S. Sharifi, ‘A Sustainable Water Resources Management Assessment Framework (SWRM-AF) for Arid and Semi-Arid Regions—Part 2: Refining the Conceptual Framework Using the Delphi Technique’, Sustainability, vol. 16, no. 11, p. 4463, May 2024, doi: 10.3390/su16114463.
[11]K. Kwon, M. Kang, D. Kim, and H. Choi, ‘Prioritization of Hazardous Zones Using an Advanced Risk Management Model Combining the Analytic Hierarchy Process and Fuzzy Set Theory’, Sustainability, vol. 15, no. 15, p. 12018, Aug. 2023, doi: 10.3390/su151512018.
[12]I. Tronnebati, F. Jawab, Y. Frichi, and J. Arif, ‘Green Supplier Selection Using Fuzzy AHP, Fuzzy TOSIS, and Fuzzy WASPAS: A Case Study of the Moroccan Automotive Industry’, Sustainability, vol. 16, no. 11, p. 4580, May 2024, doi: 10.3390/su16114580.
[13]S.-N. Li, Y. Li, and W. Yu, ‘Assessing the Content Quality of Industry Technology Roadmaps’, Sustainability, vol. 15, no. 11, p. 9058, Jun. 2023, doi: 10.3390/su15119058.
[14]O. Ogut, J. N. Tzortzi, and C. Bertolin, ‘Creating a Roadmap to Forecast Future Directions in Vertical Green Structures as a Climate Change Mitigation Strategy: A Critical Review of Technology-Driven Applications’, Sustainability, vol. 16, no. 11, p. 4543, May 2024, doi: 10.3390/su16114543.
[15]X. Mao, X. Li, Y. Huang, J. Shi, and Y. Zhang, ‘Programmable Logic Controllers Past Linear Temporal Logic for Monitoring Applications in Industrial Control Systems’, IEEE Trans. Ind. Inf., vol. 18, no. 7, pp. 4393–4405, Jul. 2022, doi: 10.1109/TII.2021.3123194.
[16]L. C. Tasca, E. Pignaton De Freitas, and F. R. Wagner, ‘A study on the performance impact of programmable logic controllers based on enhanced architecture and organization’, Microprocessors and Microsystems, vol. 76, p. 103082, Jul. 2020, doi: 10.1016/j.micpro.2020.103082.
[17]L. C. Tasca, E. P. D. Freitas, and F. R. Wagner, ‘Enhanced architecture for programmable logic controllers targeting performance improvements’, Microprocessors and Microsystems, vol. 61, pp. 306–315, Sep. 2018, doi: 10.1016/j.micpro.2018.06.007.
[18]M. A. Sehr et al., ‘Programmable Logic Controllers in the Context of Industry 4.0’, IEEE Trans. Ind. Inf., vol. 17, no. 5, pp. 3523–3533, May 2021, doi: 10.1109/TII.2020.3007764.
[19]S. C. Rowe, C. I. Samson, and D. E. Clough, ‘A Framework to Guide the Instruction of Industrial Programmable Logic Controllers in Undergraduate Engineering Education’, Education for Chemical Engineers, vol. 31, pp. 76–84, Apr. 2020, doi: 10.1016/j.ece.2020.03.001.
[20]U. Pora, N. Gerdsri, N. Thawesaengskulthai, and S. Triukose, ‘Data-Driven Roadmapping (DDRM): Approach and Case Demonstration’, IEEE Trans. Eng. Manage., vol. 69, no. 1, pp. 209–227, Feb. 2022, doi: 10.1109/TEM.2020.3005341.
[21]M. G. De Oliveira, J. S. Freitas, B. S. Pereira, and P. V. Guerra, ‘Exploring the Involvement of Experts in Strategic Roadmapping With Large Groups’, IEEE Trans. Eng. Manage., vol. 69, no. 1, pp. 56–66, Feb. 2022, doi: 10.1109/TEM.2020.3026936.
[22]H. Miao, Y. Wang, X. Li, and F. Wu, ‘Integrating Technology-Relationship-Technology Semantic Analysis and Technology Roadmapping Method: A Case of Elderly Smart Wear Technology’, IEEE Trans. Eng. Manage., vol. 69, no. 1, pp. 262–278, Feb. 2022, doi: 10.1109/TEM.2020.2970972.
[23]B. Mazon-Olivo and A. Pan, ‘Internet of Things: State-of-the-art, Computing Paradigms and Reference Architectures’, IEEE Latin Am. Trans., vol. 20, no. 1, pp. 49–63, Jan. 2022, doi: 10.1109/TLA.2022.9662173.
[24]C. W. Chen, ‘Internet of Video Things: Next-Generation IoT With Visual Sensors’, IEEE Internet Things J., vol. 7, no. 8, pp. 6676–6685, Aug. 2020, doi: 10.1109/JIOT.2020.3005727.
[25]J. A. Ansere, G. Han, L. Liu, Y. Peng, and M. Kamal, ‘Optimal Resource Allocation in Energy-Efficient Internet-of-Things Networks With Imperfect CSI’, IEEE Internet Things J., vol. 7, no. 6, pp. 5401–5411, Jun. 2020, doi: 10.1109/JIOT.2020.2979169.
[26]Y. Zhang et al., ‘Robust Resource Allocation for Lightweight Secure Transmission in Multicarrier NOMA-Assisted Full Duplex IoT Networks’, IEEE Internet Things J., vol. 9, no. 9, pp. 6443–6457, May 2022, doi: 10.1109/JIOT.2021.3110974.
[27]T. B. Da Silva, R. P. Dos Santos Chaib, C. S. Arismar, R. Da Rosa Righi, and A. M. Alberti, ‘Toward Future Internet of Things Experimentation and Evaluation’, IEEE Internet Things J., vol. 9, no. 11, pp. 8469–8484, Jun. 2022, doi: 10.1109/JIOT.2021.3114540.
[28]A. Canedo, H. Ludwig, and M. A. Al Faruque, ‘High Communication Throughput and Low Scan Cycle Time with Multi/Many-Core Programmable Logic Controllers’, IEEE Embedded Syst. Lett., vol. 6, no. 2, pp. 21–24, Jun. 2014, doi: 10.1109/LES.2014.2299731.
[29]M. Watanabe, Y. Nakagami, T. Isshiki, M. Kunugi, and Y. Yasunaga, ‘Research on the TRM Kaizen Method for Governmental Organizations to Apply Technology Roadmapping as a Methodology to Achieve the Goals of Industrial Technology Policy’, IEEE Trans. Eng. Manage., vol. 69, no. 1, pp. 17–33, Feb. 2022, doi: 10.1109/TEM.2020.3032603.
[30]T. Alves, R. Das, and T. Morris, ‘Embedding Encryption and Machine Learning Intrusion Prevention Systems on Programmable Logic Controllers’, IEEE Embedded Syst. Lett., vol. 10, no. 3, pp. 99–102, Sep. 2018, doi: 10.1109/LES.2018.2823906.
[31]D. Formby and R. Beyah, ‘Temporal Execution Behavior for Host Anomaly Detection in Programmable Logic Controllers’, IEEE Trans.Inform.Forensic Secur., vol. 15, pp. 1455–1469, 2020, doi: 10.1109/TIFS.2019.2940890.
[32]W. Alsabbagh and P. Langendoerfer, ‘A New Injection Threat on S7-1500 PLCs - Disrupting the Physical Process Offline’, IEEE Open J. Ind. Electron. Soc., vol. 3, pp. 146–162, 2022, doi: 10.1109/OJIES.2022.3151528.
[33]P. Krupa, D. Limon, and T. Alamo, ‘Implementation of Model Predictive Control in Programmable Logic Controllers’, IEEE Trans. Contr. Syst. Technol., vol. 29, no. 3, pp. 1117–1130, May 2021, doi: 10.1109/TCST.2020.2992959.
[34]H. Su, Z. Luo, Y. Feng, and Z. Liu, ‘Application of Siemens PLC in Thermal Simulator Control System’, Procedia Manufacturing, vol. 37, pp. 38–45, 2019, doi: 10.1016/j.promfg.2019.12.009.
[35]N. Mohammed and A. M. Saif, ‘Programmable logic controller based lithium-ion battery management system for accurate state of charge estimation’, Computers & Electrical Engineering, vol. 93, p. 107306, Jul. 2021, doi: 10.1016/j.compeleceng.2021.107306.
[36]M. S. El-Genk, R. Altamimi, and T. M. Schriener, ‘Pressurizer dynamic model and emulated programmable logic controllers for nuclear power plants cybersecurity investigations’, Annals of Nuclear Energy, vol. 154, p. 108121, May 2021, doi: 10.1016/j.anucene.2020.108121.
[37]S. Vadi, R. Bayindir, Y. Toplar, and I. Colak, ‘Induction motor control system with a Programmable Logic Controller (PLC) and Profibus communication for industrial plants — An experimental setup’, ISA Transactions, vol. 122, pp. 459–471, Mar. 2022, doi: 10.1016/j.isatra.2021.04.019.
[38]N. Aziz, S. A. K. Tanoli, and F. Nawaz, ‘A programmable logic controller based remote pipeline monitoring system’, Process Safety and Environmental Protection, vol. 149, pp. 894–904, May 2021, doi: 10.1016/j.psep.2021.03.045.
[39]D. Chivilikhin, S. Patil, K. Chukharev, A. Cordonnier, and V. Vyatkin, ‘Automatic State Machine Reconstruction From Legacy Programmable Logic Controller Using Data Collection and SAT Solver’, IEEE Trans. Ind. Inf., vol. 16, no. 12, pp. 7821–7831, Dec. 2020, doi: 10.1109/TII.2020.2992235.
[40]J. Zhao and Z. Tao, ‘Toward Reliable Programmable Logic Controller Function Block Diagrams’, IEEE Access, vol. 9, pp. 166137–166146, 2021, doi: 10.1109/ACCESS.2021.3133630.
[41]MITSUBISHI ELECTRIC AUTOMATION (TAIWAN) CO., LTD., [Online]. Available: https://www.setsuyo.com.tw/news_detail223.htm
[42]X. Jia et al., ‘A Novel Program Scheme to Optimize Program Disturbance in Dual-Deck 3D NAND Flash Memory’, IEEE Electron Device Lett., vol. 43, no. 7, pp. 1033–1036, Jul. 2022, doi: 10.1109/LED.2022.3178155.
[43]S. Xia et al., ‘Analysis and Optimization of Temporary Read Errors in 3D NAND Flash Memories’, IEEE Electron Device Lett., vol. 42, no. 6, pp. 820–823, Jun. 2021, doi: 10.1109/LED.2021.3073604.
[44]S. Demirhan and A. Bozbey, ‘Design and Implementation of a Single Flux Quantum Logic-Based Memory Controller for Josephson-CMOS Hybrid Memory Systems’, IEEE Trans. Appl. Supercond., vol. 30, no. 7, pp. 1–6, Oct. 2020, doi: 10.1109/TASC.2020.3012382.
[45]L. Yang, R. Zhao, Y. Li, H. Tong, Y. Yu, and X. Miao, ‘In-Memory Search With Phase Change Device-Based Ternary Content Addressable Memory’, IEEE Electron Device Lett., vol. 43, no. 7, pp. 1053–1056, Jul. 2022, doi: 10.1109/LED.2022.3179736.
[46]M. Poremba, T. Zhang, and Y. Xie, ‘NVMain 2.0: A User-Friendly Memory Simulator to Model (Non-)Volatile Memory Systems’, IEEE Comput. Arch. Lett., vol. 14, no. 2, pp. 140–143, Jul. 2015, doi: 10.1109/LCA.2015.2402435.
[47]Two-Way, [Online]. Available: http://www.two-way.com.tw/
[48]FAPRO ENTERPRISE CO.,LTD, [Online]. Available: https://www.fapro.com.tw/
[49]G. Albuquerque, S. Hernandez, M. T. Kief, D. Mauri, and L. Wang, ‘HDD Reader Technology Roadmap to an Areal Density of 4 Tbpsi and Beyond’, IEEE Trans. Magn., vol. 58, no. 2, pp. 1–10, Feb. 2022, doi: 10.1109/TMAG.2021.3081042.
[50]M. V. Pereia Pessoa and A. Gowda, ‘Integrated PSS Roadmapping Using Customer Needs and Technology Change Likelihood’, IEEE Trans. Eng. Manage., vol. 69, no. 1, pp. 127–141, Feb. 2022, doi: 10.1109/TEM.2020.3024581.
[51]M. Han and Y. Geum, ‘Roadmapping for Data: Concept and Typology of Data-Integrated Smart-Service Roadmaps’, IEEE Trans. Eng. Manage., vol. 69, no. 1, pp. 142–154, Feb. 2022, doi: 10.1109/TEM.2020.3013295.
[52]J. Nazarko et al., ‘Roadmapping in Regional Technology Foresight: A Contribution to Nanotechnology Development Strategy’, IEEE Trans. Eng. Manage., vol. 69, no. 1, pp. 179–194, Feb. 2022, doi: 10.1109/TEM.2020.3004549.
[53]S. Ozcan, A. Homayounfard, C. Simms, and J. Wasim, ‘Technology Roadmapping Using Text Mining: A Foresight Study for the Retail Industry’, IEEE Trans. Eng. Manage., vol. 69, no. 1, pp. 228–244, Feb. 2022, doi: 10.1109/TEM.2021.3068310.
[54]J.-Y. Ho and E. O’Sullivan, ‘Toward Integrated Innovation Roadmapping: Lessons From Multiple Functional Roadmaps Beyond Technology R&D’, IEEE Trans. Eng. Manage., vol. 69, no. 1, pp. 155–167, Feb. 2022, doi: 10.1109/TEM.2020.3029783.
[55]P. T. Letaba and M. W. Pretorius, ‘Toward Sociotechnical Transition Technology Roadmaps: A Proposed Framework for Large-Scale Projects in Developing Countries’, IEEE Trans. Eng. Manage., vol. 69, no. 1, pp. 195–208, Feb. 2022, doi: 10.1109/TEM.2021.3050812.
[56]E. Kim et al., ‘User-Centered Design Roadmapping: Anchoring Roadmapping in Customer Value Before Technology Selection’, IEEE Trans. Eng. Manage., vol. 69, no. 1, pp. 109–126, Feb. 2022, doi: 10.1109/TEM.2020.3030172.
[57]Y. He, G. Han, M. Xu, and M. Martinez-Garcia, ‘A Pseudopacket Scheduling Algorithm for Protecting Source Location Privacy in the Internet of Things’, IEEE Internet Things J., vol. 9, no. 12, pp. 9999–10009, Jun. 2022, doi: 10.1109/JIOT.2021.3117957.
[58]Y. Liu, K. Wang, K. Qian, M. Du, and S. Guo, ‘Tornado: Enabling Blockchain in Heterogeneous Internet of Things Through a Space-Structured Approach’, IEEE Internet Things J., vol. 7, no. 2, pp. 1273–1286, Feb. 2020, doi: 10.1109/JIOT.2019.2954128.
[59]H. Tran-Dang, N. Krommenacker, P. Charpentier, and D.-S. Kim, ‘Toward the Internet of Things for Physical Internet: Perspectives and Challenges’, IEEE Internet Things J., vol. 7, no. 6, pp. 4711–4736, Jun. 2020, doi: 10.1109/JIOT.2020.2971736.
[60]L. Yuan, H. Zhang, M. Xu, F. Zhou, and Q. Wu, ‘A Multiscale CNN Framework for Wireless Technique Classification in Internet of Things’, IEEE Internet Things J., vol. 9, no. 12, pp. 10366–10367, Jun. 2022, doi: 10.1109/JIOT.2021.3132652.
[61]K. Yang, Y. Zhang, X. Lin, Z. Li, and L. Sun, ‘Characterizing Heterogeneous Internet of Things Devices at Internet Scale Using Semantic Extraction’, IEEE Internet Things J., vol. 9, no. 7, pp. 5434–5446, Apr. 2022, doi: 10.1109/JIOT.2021.3110757.
[62]R. Gomes Alves, R. Filev Maia, and F. Lima, ‘Discrete-event simulation of an irrigation system using Internet of Things’, IEEE Latin Am. Trans., vol. 20, no. 6, pp. 941–947, Jun. 2022, doi: 10.1109/TLA.2022.9757736.
[63]H. Lu, X. He, M. Du, X. Ruan, Y. Sun, and K. Wang, ‘Edge QoE: Computation Offloading With Deep Reinforcement Learning for Internet of Things’, IEEE Internet Things J., vol. 7, no. 10, pp. 9255–9265, Oct. 2020, doi: 10.1109/JIOT.2020.2981557.
[64]Y. Liu, C. Chi, Y. Zhang, and T. Tang, ‘Identification and Resolution for Industrial Internet: Architecture and Key Technology’, IEEE Internet Things J., vol. 9, no. 18, pp. 16780–16794, Sep. 2022, doi: 10.1109/JIOT.2022.3160737.
[65]J. Liu, X. Zhao, P. Qin, S. Geng, and S. Meng, ‘Joint Dynamic Task Offloading and Resource Scheduling for WPT Enabled Space-Air-Ground Power Internet of Things’, IEEE Trans. Netw. Sci. Eng., vol. 9, no. 2, pp. 660–677, Mar. 2022, doi: 10.1109/TNSE.2021.3130251.
[66]F. Zhang, G. Han, L. Liu, M. Martinez-Garcia, and Y. Peng, ‘Joint Optimization of Cooperative Edge Caching and Radio Resource Allocation in 5G-Enabled Massive IoT Networks’, IEEE Internet Things J., vol. 8, no. 18, pp. 14156–14170, Sep. 2021, doi: 10.1109/JIOT.2021.3068427.
[67]S. Xu, X. Wang, G. Yang, J. Ren, and S. Wang, ‘Routing optimization for cloud services in SDN-based Internet of Things with TCAM capacity constraint’, J. Commun. Netw., vol. 22, no. 2, pp. 145–158, Apr. 2020, doi: 10.1109/JCN.2020.000006.
[68]M. Sayagh, N. Kerzazi, B. Adams, and F. Petrillo, ‘Software Configuration Engineering in Practice Interviews, Survey, and Systematic Literature Review’, IIEEE Trans. Software Eng., vol. 46, no. 6, pp. 646–673, Jun. 2020, doi: 10.1109/TSE.2018.2867847.
[69]T. Hogan, U. Hinrichs, and E. Hornecker, ‘The Elicitation Interview Technique: Capturing People’s Experiences of Data Representations’, IEEE Trans. Visual. Comput. Graphics, vol. 22, no. 12, pp. 2579–2593, Dec. 2016, doi: 10.1109/TVCG.2015.2511718.
[70]P. Chundury, B. Patnaik, Y. Reyazuddin, C. Tang, J. Lazar, and N. Elmqvist, ‘Towards Understanding Sensory Substitution for Accessible Visualization: An Interview Study’, IEEE Trans. Visual. Comput. Graphics, vol. 28, no. 1, pp. 1084–1094, Jan. 2022, doi: 10.1109/TVCG.2021.3114829.
[71]Whisper Maisiri; Liezl van Dyk; Rojanette Coetzee, ‘Development of an industry 4.0 competency maturity model’, SAIEE Africa Research Journal, vol. 112, no. 4, pp. 189–197, 2021.
[72]P. Gray and J. M. Nilles, ‘Evaluating a Delphi forecast on personal computers’, IEEE Trans. Syst., Man, Cybern., vol. SMC-13, no. 2, pp. 222–224, Mar. 1983, doi: 10.1109/TSMC.1983.6313116.
[73]G. Parekh et al., ‘Identifying Core Concepts of Cybersecurity: Results of Two Delphi Processes’, IEEE Trans. Educ., vol. 61, no. 1, pp. 11–20, Feb. 2018, doi: 10.1109/TE.2017.2715174.
[74]A. J. Maddox, R. D. Downs, J. F. Lindsay, and M. T. Quesada, ‘The Delphi outer detector decision module: Lucifer’, IEEE Trans. Nucl. Sci., vol. 37, no. 5, pp. 1589–1593, Oct. 1990, doi: 10.1109/23.58709.
[75]A. Ishikawa, M. Amagasa, T. Shiga, G. Tomizawa, R. Tatsuta, and H. Mieno, ‘The max-min Delphi method and fuzzy Delphi method via fuzzy integration’, Fuzzy Sets and Systems, vol. 55, no. 3, pp. 241–253, May 1993, doi: 10.1016/0165-0114(93)90251-C.
[76]Jao-Hong Cheng, ‘Indexes of Competitive Power and Core Competence in Selecting Asia-Pacific Ports’, Journal of the Chinese Institute of Transportation, vol. 13, no. 1, pp. 1–25.
[77]Jeng Tsang-Bin, ‘Fuzzy assessment model for maturity of software organization in improving its staff’s capability’, National Taiwan University of Science and Technology, 2001.
[78]T. L. Saaty and L. G. Vargas, ‘Estimating technological coefficients by the analytic hierarchy process’, Socio-Economic Planning Sciences, vol. 13, no. 6, pp. 333–336, Jan. 1979, doi: 10.1016/0038-0121(79)90015-6.
[79]J. J. Buckley, ‘Fuzzy hierarchical analysis’, Fuzzy Sets and Systems, vol. 17, no. 3, pp. 233–247, Dec. 1985, doi: 10.1016/0165-0114(85)90090-9.
[80]R. W. Saaty, ‘The analytic hierarchy process—what it is and how it is used’, Mathematical Modelling, vol. 9, no. 3–5, pp. 161–176, 1987, doi: 10.1016/0270-0255(87)90473-8.
[81]R.L.N. Murty, Sivaji Ganesh Kondamudi, M.V. Suryanarayana and P. Giribabu, ‘Application Of Buckley’S Fuzzy Ahp To Identify The Most Important Factor Affecting The Unorganized Microentrepreneurs’ Borrowing Decision’, vol. 11, no. 6, pp. 665–674, 2020.
[82]Z. Geng, Z. Wang, C. Peng, and Y. Han, ‘A New Fuzzy Process Capability Estimation Method Based on Kernel Function and FAHP’, IEEE Trans. Eng. Manage., vol. 63, no. 2, pp. 177–188, May 2016, doi: 10.1109/TEM.2016.2517337.
[83]H. Zhang, X. Feng, Y. Wei, and Z. Li, ‘A Vagueness Adaptive Efficiency Evaluation Method of Science and Technology Resources Opening and Sharing Platforms Based on FAHP and BP Neural Network’, IEEE Trans. Eng. Manage., vol. 71, pp. 2049–2062, 2024, doi: 10.1109/TEM.2022.3173370.
[84]M. Ri, J. Ko, S. Pak, Y. Song, and C. Kim, ‘Notice of Removal: Exploiting an Integrated FAHP-VWA-TOPSIS in Whole-Process of On-Demand Charging Scheduling for WRSNs’, IEEE Systems Journal, vol. 17, no. 4, pp. 6634–6644, Dec. 2023, doi: 10.1109/JSYST.2023.3302870.
[85]L. Li, M. Liu, W. Shen, and G. Cheng, ‘Recommending Mobile Services with Trustworthy QoS and Dynamic User Preferences via FAHP and Ordinal Utility Function’, IEEE Trans. on Mobile Comput., vol. 19, no. 2, pp. 419–431, Feb. 2020, doi: 10.1109/TMC.2019.2896239.
[86]C. Valmohammadi, F. Faezy Razi, and F. Einy, ‘Six Sigma Project Selection Using the Hybrid Approach FAHP-FTOPSIS and Grey Relational Analysis Model’, IEEE Eng. Manag. Rev., vol. 49, no. 2, pp. 134–146, Jun. 2021, doi: 10.1109/EMR.2021.3071368.
[87]P. J. M. Van Laarhoven and W. Pedrycz, ‘A fuzzy extension of Saaty’s priority theory’, Fuzzy Sets and Systems, vol. 11, no. 1–3, pp. 229–241, 1983, doi: 10.1016/S0165-0114(83)80082-7.
[88]Shiang-Lin Lin and Chen-Shu Wang, ‘Integration of FAHP and Association Rule to Establish the Evaluation Mechanism for e-Learning Platform, Journal of Management & Systems’, Journal of Management & Systems, vol. 22, no. 1, pp. 124–147, Jan. 2015.