期刊


ISSN0954-4054
刊名Proceedings of the Institution of Mechanical Engineers
参考译名机械工程师学会会报B辑:工程制造杂志
收藏年代1995~2024



全部

1995 1996 1997 1998 1999 2000
2001 2002 2003 2004 2005 2006
2007 2008 2009 2010 2011 2012
2013 2014 2015 2016 2017 2018
2019 2020 2021 2022 2023 2024

2018, vol.232, no.1 2018, vol.232, no.10 2018, vol.232, no.11 2018, vol.232, no.12 2018, vol.232, no.13 2018, vol.232, no.14
2018, vol.232, no.2 2018, vol.232, no.3 2018, vol.232, no.4 2018, vol.232, no.5 2018, vol.232, no.6 2018, vol.232, no.7
2018, vol.232, no.8 2018, vol.232, no.9

题名作者出版年年卷期
Influence of nanofluid application on wheel wear, coefficient of friction and redeposition phenomenon in surface grinding of Ti-6Al-4VDinesh Setti20182018, vol.232, no.1
Multi response optimization of cutting parameters in drilling of AISI 304 stainless steels using response surface methodologyM Balaji; BSN Murthy; N Mohan Rao20182018, vol.232, no.1
An adaptability index system for product developmentOswaldo Luiz Agostinho; Iris Bento da Silva20182018, vol.232, no.1
A dual scheduling model for optimizing robustness and energy consumption in manufacturing systemsJoan Escamilla20182018, vol.232, no.1
Decision support system enabled by depth imaging sensor data for intelligent automation of moving assembliesVinayak Ashok Prabhu; Narendi Muhandri; Boyang Song; Ashutosh Tiwari20182018, vol.232, no.1
Adaptive robust control of machining force and contour error with tool deflection using global task coordinate frameTyler A Davis20182018, vol.232, no.1
Modelling, monitoring and evaluation to support automatic engineering process managementLei Shi; Linda Newnes; Steve Culley; Bruce Allen20182018, vol.232, no.1
Production control strategy inspired by neuroendocrine regulationHaitao Zhang; Dunbing Tang; Kun Zheng; Adriana Giret20182018, vol.232, no.1
A hormone regulation–based approach for distributed and on-line scheduling of machines and automated guided vehiclesKun Zheng; Dunbing Tang; Adriana Giret; Miguel A Salido; Zelei Sang20182018, vol.232, no.1
Evaluation and selection of lean resourced employee in the manufacturing industries using the TOPSIS-Simos methodK Balaji20182018, vol.232, no.1
12