Browsing by Author "Sharma, Shubham"

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    Identification of factors affecting noise levels by using data mining and design of experiments analysis techniques: A novel experimental approach
    (Sage Publications, 2022-04-29) Orbak, Ali Yurdun; Aydın, Fikret Umut; Sharma, Shubham; Chohan, Jasgurpreet S.; Rajkumar, S.; ORBAK, ALİ YURDUN; Aydın, Fikret Umut; Bursa Uludağ Üniversitesi/Endüstri Mühendisliği Bölümü; Bursa Uludağ Üniversitesi/Fen Bilimleri Enstitüsü; M-9216-2014; ITL-4245-2023
    The sounds that are high enough, which negatively affect our understanding, are called noise. Although students are one of the main sources of noise at schools, noise adversely affects students' success. Schools' acoustics and the time when the noise measurement is made are usually considered to be other reasons for noise. In this study, noise measurements are collected in several of a metropolitan city's primary and secondary schools, and factors that affect noise significantly are investigated using 2(3) full factorial experimental designs. In addition, school teachers' perception of noise is analyzed by the Apriori algorithm. Results indicate that noise values exceed the limit values set by the WHO and noise regulations currently in effect in Turkey. Also, the schools with no acoustic insulation were noisier than those with minimum insulation. From the Apriori analysis, it is concluded that female teachers are more sensitive than male teachers about noise annoyance.
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    Mathematical model assisted six-sigma approach for reducing the logistics costs of a pipe manufacturing company: A novel experimental approach
    (Mdpi, 2023-02-01) Sharma, Shubham; Li, Changhe; Kumar, Raman; Singh, Sunpreet; Di Bona, Gianpaolo; ORBAK, ALİ YURDUN; Küçük, Metin; Akansel, Mehmet; AKANSEL, MEHMET; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi.; 0000-0002-4924-7587; M-9216-2014; ABE-6702-2020
    This research addresses and analyzes the results of a six-sigma approach used to optimize the logistics costs of a pipe manufacturing company. Two mathematical models are developed for containers to control the company's logistics. The Mathematical Programming Language (MPL) software is used to generate and solve these models. The results verify that the proposed mathematical models result in the company's logistics improvement, especially in the DMAIC (define, measure, analyze, improve, and control) cycle by providing flexibility in choosing the most appropriate containers for logistics.