Search | Engineering

Subscribe Submit

Home Journals Focus Achievement Fronts About Us 中文版

Resource Type

Journal Article 2

Year

2017 2

Keywords

Optimality assessment 2

Green manufacturing 1

High-end manufacturing 1

Multi-mode 1

Probabilistic principal component regression 1

Process industry 1

Smart and optimal manufacturing 1

open ︾

Search scope:

排序： Display mode:

Real-Time Assessment and Diagnosis of Process Operating Performance

Shabnam Sedghi,Biao Huang

Engineering 2017, Volume 3, Issue 2, Pages 214-219 doi: 10.1016/J.ENG.2017.02.004

Abstract: process variations and uncertainties, making it necessary to develop systematic methods for online optimalityIn this paper, we will establish an optimality assessment framework for processes that typically have

Keywords： Optimality assessment Probabilistic principal component regression Multi-mode

HTML PDF Collect

Fundamental Theories and Key Technologies for Smart and Optimal Manufacturing in the Process Industry

Feng Qian,Weimin Zhong,Wenli Du

Engineering 2017, Volume 3, Issue 2, Pages 154-160 doi: 10.1016/J.ENG.2017.02.011

Abstract:

Given the significant requirements for transforming and promoting the process industry, we present the major limitations of current petrochemical enterprises, including limitations in decision-making, production operation, efficiency and security, information integration, and so forth. To promote a vision of the process industry with efficient, green, and smart production, modern information technology should be utilized throughout the entire optimization process for production, management, and marketing. To focus on smart equipment in manufacturing processes, as well as on the adaptive intelligent optimization of the manufacturing process, operating mode, and supply chain management, we put forward several key scientific problems in engineering in a demand-driven and application-oriented manner, namely: ① intelligent sensing and integration of all process information, including production and management information; ② collaborative decision-making in the supply chain, industry chain, and value chain, driven by knowledge; ③ cooperative control and optimization of plant-wide production processes via human-cyber-physical interaction; and ④ life-cycle assessments for safety and environmental footprint monitoring, in addition to tracing analysis and risk control. In order to solve these limitations and core scientific problems, we further present fundamental theories and key technologies for smart and optimal manufacturing in the process industry. Although this paper discusses the process industry in China, the conclusions in this paper can be extended to the process industry around the world.

Keywords： Process industry Smart and optimal manufacturing Green manufacturing High-end manufacturing Optimality