Essays about: "Service Time"

Showing result 21 - 25 of 1929 essays containing the words Service Time.

1. 21. SDL, qualitative research on service chatbots’ co-destruction impact on consumer ecosystem.

   University essay from Jönköping University/IHH, Företagsekonomi

   Author : Daniele Galizzi; Dilyan Valentinov Peshev; [2023]
   Keywords : Chatbots; AI; Value Co-Creation; Value Co-Destruction; Service Ecosystem; Customer Service;

   Abstract : This study is rooted in the Service Dominant Logic (SDL) theory and explores the phenomenon of value co-destruction, the context being chatbot-mediated customer service, with a focusing on chatbots affiliation with value-co-destruction and on the impacts outsideof the dyadic relationship between the service provider and receiver, described as the broader consumer ecosystem. It is evident that the relationship between businesses and consumers is being revolutionized through the implementation of chatbots, claiming benefits such as improved operational efficiency, and non-time specific service. READ MORE

3. 22. Maximizing the Value of Large-Scale Solar PV Parks through Battery Storage and Ancillary Services : An analysis using multiple-integer linear programming optimization

   University essay from Uppsala universitet/Byggteknik och byggd miljö

   Author : Nora Ekström; [2023]
   Keywords : Solar PV park; BESS; ancillary service; linear programming optimization;

   Abstract : Renewable power production is becoming a necessity to improve society and overcome the challenges of climate change. In Sweden, large-scale solar PV power is growing year-on-year and today comprises 1 percent of electricity production. READ MORE

4. 23. Optimizing within the Supply Chain: A Mathematical Model for Inventory Optimization with respect to Demand Planning

   University essay from KTH/Matematisk statistik

   Author : William Bork; Martynas Giedraitis; [2023]
   Keywords : Inventory model; ”Fast Moving Consumer Goods-company” FMCG-company ; Reorder point; Order quantity; ”Software as a Service-Company”; EOQ-model; R; Q -model; Forecast; Holt-Winters model; Inventory model; ”Fast Moving Consumer Goods-company” FMCG-company ; Reorder point; Order quantity; ”Software as a Service-Company”; EOQ-model; R; Q -model; Forecast; Holt-Winters model;

   Abstract : This thesis examines how to design a mathematical inventory model for a ”Fast Moving Consumer Goods”-company (FMCG-company), which determines the optimal reorder point and order quantity such that the average inventory cost is minimized. The thesis was made in collaboration with a ”Software as a Service”- company which provided the data containing information about the products and inventory management of one of their customers, a FMCG-company. READ MORE

5. 24. Status Mapping of tank to grave management of Low-GWP refrigerants.

   University essay from KTH/Skolan för industriell teknik och management (ITM)

   Author : Sandra Parra Gimeno; [2023]
   Keywords : Refrigerant; Blends; Synthetic low-GWP refrigerant; Natural refrigerant; Global Warming Potential GWP ; Tank-to-grave; Interviews.; Köldmedier; Blandning; Globalt uppvärmningspotential GWP ; Låg-GWP köldmedier; Naturligt köldmedier; installation till destruktion; Intervjuer.;

   Abstract : Refrigeration plays a vital role today in various residential, commercial, and industrial processes, requiring refrigerants to facilitate the cooling or heating processes. Over time, refrigerants have undergone significant changes to meet technological, social, environmental, and economic needs. READ MORE

6. 25. AI/ML Development for RAN Applications : Deep Learning in Log Event Prediction

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Yuxin Sun; [2023]
   Keywords : LSTM; Anomaly Detection; Failure Prediction; Log Mining; Deep Learning; LSTM; Anomali Detection; Failure Prediction; Log Mining; Deep Learning;

   Abstract : Since many log tracing application and diagnostic commands are now available on nodes at base station, event log can easily be collected, parsed and structured for network performance analysis. In order to improve In Service Performance of customer network, a sequential machine learning model can be trained, test, and deployed on each node to learn from the past events to predict future crashes or a failure. READ MORE