Digitalizing service-product delivery
Almasi, Faezeh (2024)
Diplomityö
2024
School of Engineering Science, Tuotantotalous
Kaikki oikeudet pidätetään.
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe2024061753403
https://urn.fi/URN:NBN:fi-fe2024061753403
Tiivistelmä
In today's industrial landscape, digitalization is revolutionizing operations by leveraging data analytics, cloud computing, Artificial Intelligence (AI), and the Internet of Things (IoT) to enhance operational efficiency and service delivery. As part of this digital revolution, field services as a critical domain are undergoing significant evolution through the infusion of digital capabilities resulting in maintenance enhancements and more accurate demand forecasting.
This thesis with a focus on a case company, explores the integration of digitalization in company's field services, focusing on analyzer equipment. The aim is to improve the field service capabilities by reserving the current values. Through a qualitative research method, semi-structured interviews with stakeholders are conducted to get a comprehensive assessment of current field service practices. Findings reveal significant potential for enhancing field services through digitalization, with a particular emphasis on predictive maintenance strategies. es. The current levels of maintenance are reactive (corrective) and preventive approaches resulting in challenges such as unpredicted service requests, slightly inaccurate demand forecasting, and manual work.
By identifying key challenges through the current service flow, this thesis proposes solutions to move beyond reactive maintenance and achieve predictive maintenance capabilities. By leveraging data analytics and real-time monitoring, these predictive solutions aim to improve field service by identifying and fixing equipment issues before they become major problems. Additionally, implementing these digital capabilities allows service providers to streamline service scheduling, enhance demand forecasting, and ultimately elevate customer satisfaction levels through optimized field services.
This thesis with a focus on a case company, explores the integration of digitalization in company's field services, focusing on analyzer equipment. The aim is to improve the field service capabilities by reserving the current values. Through a qualitative research method, semi-structured interviews with stakeholders are conducted to get a comprehensive assessment of current field service practices. Findings reveal significant potential for enhancing field services through digitalization, with a particular emphasis on predictive maintenance strategies. es. The current levels of maintenance are reactive (corrective) and preventive approaches resulting in challenges such as unpredicted service requests, slightly inaccurate demand forecasting, and manual work.
By identifying key challenges through the current service flow, this thesis proposes solutions to move beyond reactive maintenance and achieve predictive maintenance capabilities. By leveraging data analytics and real-time monitoring, these predictive solutions aim to improve field service by identifying and fixing equipment issues before they become major problems. Additionally, implementing these digital capabilities allows service providers to streamline service scheduling, enhance demand forecasting, and ultimately elevate customer satisfaction levels through optimized field services.