## 4 Future Work  
The integration of on-stream inspections and PACM into regular plant operations has been suggested as a potential solution to minimize TAM duration and extend TAM  
Figure 4: Research objective/aim summaries.  
intervals. To better understand the potential benefits and limitations of this approach, future research should focus on several key areas.  
First, the accuracy and reliability of PACM for on-stream inspections in high-temperature environments must be investigated. This can be done by conducting experiments on test samples up to 500 \({}^{\circ}\)C, primarily focusing on assessing the accuracy of the corrosion detection technique.  
Second, it is essential to explore the feasibility and potential impact of integrating on-stream inspections and PACM into existing maintenance strategies. This includes developing a framework for incorporating these techniques and conducting case studies to evaluate their effects on TAM duration, maintenance expenses, and plant reliability and availability. An important aspect of this research is the incorporation of Life Cycle Cost (LCC) analysis, which depends on various factors such as plant size, region, and on-stream inspection coverage. To conduct a comprehensive LCC analysis, future research should collect data on cost components, including initial investment in PACM equipment and software, operational costs (labor, consumables, energy consumption), maintenance costs, and training costs for personnel. These cost components should be compared with the savings from reduced plant downtime and improved plant reliability. It is crucial to note that the LCC analysis requires extensive data collection and may vary depending on the specific plant and context. The variation in plant sizes, regions, and on-stream inspection coverage necessitates a case-by-case approach to LCC analysis. Therefore, future research should aim to develop a methodology for conducting LCC analyses that can be adapted to different plants and contexts, enabling a more accurate assessment of the cost-effectiveness of integrating on-stream inspections and PACM into regular plant operations.  
Lastly, future research should investigate the potential of automating on-stream inspections and PACM to enhance efficiency and reduce maintenance costs. This can be achieved by developing autonomous inspection systems capable of navigating piping systems and equipment and integrating machine learning algorithms to analyze inspection data and provide maintenance recommendations. By focusing on these key areas, future research can contribute to the advancement and optimization of integrating on-stream inspections and PACM into regular plant operations.  
Conceptualization, data curation, formal analysis, investigation, methodology, visualization, and writing of the first draft were performed by J.L.T. Supervision and funding acquisition were performed by M.T.H.S., A.L. and Z.O. Project administration was performed by F.S.S., M.T.H.S., Z.O., A.L. and R.R.K. Reviewed and edited the previous versions of the manuscript M.T.H.S., A.L., Z.O. and R.R.K. All authors have read and agreed to the published version of the manuscript.  
The authors would like to thank Universiti Putra Malaysia for the financial support through Geran Inisiatif Putra Siswazah (GP-IPS) with grant number 9739200. This research was partially financed by the Ministry of Science and Higher Education of Poland with allocation to the Faculty of Mechanical Engineering, Bialystok University of Technology, for the WZ/WM-IIM/5/2023 and WZ/WM-IIB/4/2023 academic projects in the mechanical and biomedical engineering discipline.  
No new data were created in this study.  
The authors would also like to express their gratitude to the Department of Aerospace Engineering, Faculty of Engineering, Universiti Putra Malaysia, and the Laboratory of Biocomposite Technology, Institute of Tropical Forestry and Forest Product (INTROP), Universiti Putra Malaysia (HICOE) for their close collaboration in this study.  
The authors declare no conflict of interest.