In recent years, cutting-edge technologies such as artificial intelligence (AI) have streamlined operations and fostered continuous innovation across various manufacturing systems. Generative AI (Gen-AI), a subset of AI, helps generate new ideas and perspectives using large language or diffusion models. Gen-AI is transforming the ways of designing, developing, and operating industrial systems. While Gen-AI is widely used to create text, images and video content, its applications in intelligent and adaptive manufacturing remain limited and require precision, reliability, seamless integration, and security. Since the adoption of Gen-AI is still in its infancy, stakeholders need to understand the various factors influencing its implementation. In the present study, the SAP-LAP framework is used to analyze the situation-actors-process (SAP) and learning-actions-performance (LAP) dimensions for the effective implementation of Gen AI to empower flexible manufacturing systems (FMS). In conjunction with the efficient interpretive ranking process (e-IRP), the actors and actions were further ranked. The research findings identify AI technology providers and start-ups, OEMs, and system integrators as the most prominent actors in the implementation of Gen-AI in flexible manufacturing systems, with government and regulatory bodies as key enablers through policy support and governance frameworks. Further results show that ‘Develop modular Gen-AI toolkits tailored to different FMS architectures’ ‘Promote standards and protocols for secure and ethical use of Gen-AI’ are the topmost actions. Insights from this study will be helpful to practitioners and researchers interested in adopting Gen-AI applications to enhance agility and flexibility in production systems.
The fifth industrial revolution (I5.0), which is based on the utilization of interconnected data for efficient resource usage in meeting human requirements, proposes efficient solutions to resource constraint situations. However, the transition to I5.0 in the health sector is not easy and has to face several obstacles. This study dives deep into exploring and handling the obstacles in the integration of I5.0 practices into the existing Indian health system and suggests measures for overcoming them. Twenty-three obstacles were identified from literature analysis and experts' suggestions. The identified obstacles were further clubbed under organizational, technological, behavioral, financial, and regulatory and legal categories. Further, the obstacles were put to the fuzzy DEMATEL approach, which prioritized them based on their interaction/influence with each other. Triangular Fuzzy Number (TFN) approach was used to accommodate any uncertainty in responses from the experts. The findings from the study highlight the lack of integration of pertinent "I5.0" technologies in medical work, the lack of patient security law and general data protection regulation for healthcare services, and the lack of support from top management for "I5.0" adaptation as the top three ranked obstacles requiring immediate attention. The cause-effect classification in the study paved the direction to address first the causal obstacles, utilizing their interrelationship with other obstacles to achieve integration of I5.0 in the health sector. This study can be an important guiding document to the policymakers and various healthcare stakeholders to integrate the I5.0 concept in addressing the needs of the vast Indian population.
PurposeThis study aims to measure medication errors rates in a tertiary care hospital and recommends Quality Function Deployment (QFD) framework on the lines of socio-technological systems theory as an intervention in converting voice of customers (VoC), i.e. healthcare workers into technological improvements in the existing hospital's electronic medical record (EMR) system using them to reduce medication errors.Design/methodology/approachUsing observational data and error reporting documents this cross-sectional study was carried out in Punjab state of India for a period of three months. Medication errors were categorized into prescription, documentation, administration, monitoring, indenting, dispensing and transcription errors. The QFD framework divided in four steps was applied to convert VoC into with technical Features in the EMR system.FindingsPrescription errors were the most common (61%), followed by documentation (17%), administration (9%) and monitoring errors (7%). Less frequent but significant errors included indenting, dispensing and transcription. The study identified automated error alerts, standardized ordering processes and dropdown medication lists as high-priority EMR features capable of reducing medication errors. Training modules for nurses were also deemed essential.Practical implicationsEMR-based interventions, supported by user-centered training, can meaningfully reduce medication errors and strengthen clinician trust in digital systems. Ensuring regular updates and managing false alerts remain critical for sustained EMR adoption. The study highlights QFD as a strategic link between patient-safety science and health-IT implementation, with the potential to enhance patient trust, reinforce safety as a competitive differentiator and contribute to a stronger hospital brand reputation.Originality/valueThis study uniquely applies the QFD framework to link healthcare provider needs with EMR design features, emphasizing technical and human-centered strategies for reducing medication error in an Indian hospital context.
PID controllers remain one of the widely used control strategies in the industrial systems because of their simple structure, ease of implementation and reliable performance. However, their effectiveness remains limited in non-linear, uncertain and time varying environments. To address these limitations, this study explored the literature on PID and Fuzzy PID controllers from Scopus and Web of Science database. The study reviews the architectures, tuning methods, intelligent integrations, industrial applications and future research directions. The selected studies were examined across multiple dimensions including controller design, rule-base deployment, optimization methods, adaptative and neuro-fuzzy tuning, IoT enabled control, digital twin integration and smart manufacturing applications. The findings of the study show that PID based control has moved beyond conventional tuning methods. Recent studies shows the integration of fuzzy logic, metaheuristic optimization, machine learning, reinforcement learning and digital twins to improve robustness, tracking accuracy and real time monitoring. Fuzzy PID controllers are useful in nonlinear and uncertain operating conditions, while hybrid and AI supported variants offers improved tuning and fault handling capabilities. The review also reveals the application areas of PID in robotics, process industries, additive manufacturing and sustainable industrial operations. Despite of these advances, the literature remains fragmented across domains and lacks in standardized benchmarking and cross sector validation. Based on these research gaps, the study proposes a future research agenda based on self-tuning frameworks, explainable fuzzy rule generation, digital twin supported adaptive control and sustainability oriented multi objective tuning. The present study contributes a comprehensive synthesis of Fuzzy PID research and shows how these controllers are contributing for Industry 4.0.
Pricing is a powerful communicative signal in tourism markets, yet its interpretation varies substantially across cultural contexts. This study examines how pricing strategies shape price perception and tourist retention, with perceived value as a mediating construct, through the theoretical lens of Attribution Theory. A cross-national survey of 557 tourists was analyzed using structural equation modeling (SEM) to test a culture-sensitive conceptual model. The findings reveal that psychological and premium pricing most strongly enhance price perception, while penetration pricing exerts a comparatively greater effect among international tourists. Perceived value emerged as a significant mediator in the pricing-retention relationship, with its relative weight varying across domestic and international tourist segments. The findings support Attribution Theory, indicating that consumers evaluate prices based on perceived fairness, quality signals, and affordability. The study contributes to cross-cultural tourism pricing literature and offers actionable guidance for destination managers seeking to design culturally responsive pricing strategies.
