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The integration of Big Data, Artificial Intelligence (AI), Machine Learning, the Internet of Things, Cloud Computing and Cybersecurity into aviation – is reshaping how airlines and Maintenance, Repair and Overhaul (MRO) organisations create value, yet evidence on the gap between digital potential and at-scale implementation remains fragmented. This study examines how Aviation 4.0 technologies affect aviation operations, with a particular focus on MRO. A qualitative, mixed-methods design combines a systematic literature review, secondary evidence from an industry MRO digital survey, five semi-structured expert interviews (sales, data science, MRO operations, R&D innovation, and technology-provider management), and two technical case studies (neural networks for aircraft retirement and an AI-based digital twin for a Power Electronics Cooling System). Findings reveal that predictive maintenance is the dominant digital priority (prioritised by 56% of respondents), yet only 6% of MROs have scaled digital and analytics across the enterprise; over 80% cite data limitations and more than 70% cite organisational resistance as barriers. Field implementations in a focal MRO produced substantial measurable value, including $4.2M annual savings from an in-house planning platform and $6M additional revenue from an integrated quote-to-contract system. The study triangulates concept, practice and market evidence in a single crosswalk, clarifying where the Aviation 4.0 promise has materialised and where the principal barriers persist. Practically, this study provides MRO executives and policymakers with an evidence-based roadmap mapping conceptual potentials to realised implementations.

Automated flow line manufacturing systems are becoming more relevant in the automotive sector.  Improving productivity in the manufacturing system is the core objective of all companies, measured by overall equipment effectiveness (OEE).  OEE is a measure of how well a manufacturing operation is utilised compared to its full potential during the periods when it is scheduled to run. Organisations have thus made technological changes in their processes that have led to opportunities for greater flexibilities.  This sentiment underpins the concept of automation.  Hence, this study examines the impact of automation for productivity improvement in the selected automotive assembly organisation in South Africa.  Automation is the creation and application of technology to monitor and control the production and delivery of products and services.  The study was quantitative in design and examined production and the related experiences of the automotive assembly organisation that has adopted automation system in its automobile roof process in weld plant for productivity improvement.  The Ordinary Least Squares (OLS) model, using the Statistical Package for Social Sciences (SPSS) was used to analyse data.  The company operates in the eThekwini Municipality in KwaZulu-Natal province of South Africa.  The study was achieved by collecting pre- and post-quarterly data for labour productivity, process efficiency and downtime.  The results establish that labour productivity, process efficiency and downtime have a relationship and are statistically significant to company productivity after automation was implemented.  It has the potential to reduce errors, increase productivity and augment human capacity.  Hence, the original value of this study is its approach in uncovering strengths and weaknesses of automation for productivity improvement in South Africa. 

Technological advancements are becoming increasingly significant due to the poor production levels of enterprises in South Africa.  Consequently, businesses use technology modifications in their operations that create chances for enhanced flexibility and productivity enhancement.  This emotion supports a transformative concept of digitisation.  Digitalisation involves the separation of information and technologies designed to transform operational dynamics for enhanced corporate performance.  It serves as both an enabler and a catalyst for enhancing productivity.  This study investigates the impact of digitisation on productivity enhancement within a specific distribution sector of a food manufacturing company in South Africa. The study employed a quantitative approach to investigate production and the associated experiences inside the distribution division of a food manufacturing enterprise that implemented digitalisation to enhance productivity.  The Ordinary Least Squares (OLS) model was employed to analyse data using the Statistical Package for Social Sciences (SPSS).  The corporation functions within the eThekwini Municipality in KwaZulu-Natal, South Africa.  The study was conducted by gathering pre- and post-quarterly data on product picking accuracy, hourly product loading, product replenishment rate, and product release rate.  The results demonstrate a statistically significant association between the product release pace and the company’s production in the post-digitalization period.  Nonetheless, it fails to demonstrate the correlation between product picking accuracy, product loading per hour, or product replenishment rate and productivity.  A targeted organisational strategy on digitisation is expected to enhance the organization's performance. Digitising records enables the tracking of each phase of the production process, so maintaining transparency and instilling confidence in consumers.  Therefore, the primary significance of this study lies in its examination of the strengths and shortcomings of digitalisation for enhancing productivity in South Africa. 

The global business environment is undergoing significant changes due to the impact of COVID-19 and shifts in workforce demographics, making organizational change an inevitable trend. In this context, the smooth adoption of smart manufacturing in the manufacturing industry is crucial for enhancing organizational value. Through a literature review, this study consolidated key factors related to organizational innovation and the implementation of smart manufacturing. The analytic hierarchy process (AHP) was employed to identify the prioritized sequence of key strategic actions for innovative operations. The results indicated that among 27 assessment indicators, motivation is the most crucial factor for organizational innovation/change. Subsequently, organizations must also prioritize strategic human resource deployment to accelerate the development of long-term organizational goals. This study further examined solutions to ensure both talent and organizational growth during the transformation of innovation strategies.  

Expressing the digitalization of industry in today's world which is rapidly developing day by day, Industry 4.0 is accepted as the most important technology revolution of our time. This shows that a new era in production has started and the industry has been digitized. In order to adapt to this change, companies should actively follow the innovations and shape the organizational structure accordingly. However, if this is the case, we can respond to the expectations of the current period. That is why it is necessary to activate Industry 4.0 after learning all aspects of it and to develop marketing strategies that can adapt to this digital age. In today's competitive environment, it is inevitable to act integrated into this new situation. This study is designed to emphasize how important it is to identify Industry 4.0 and the most heavily affected marketing strategies from it. It is also a review of the conceptual explanation of Industry 4.0 and the importance of advances in new technologies.