Advances in Manufacturing II

Volume 2 - Production Engineering and Management
1. Auflage 2019
ISBN: 978-3-030-18788-0
Verlag: Springer International Publishing

Buch, Englisch, 400 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 628 g

Reihe: Lecture Notes in Mechanical Engineering

This book covers a variety of topics in manufacturing, with a special emphasis on product design, production planning, and implementation of both resources and production processes. The content is based on papers presented at the 6th International Scientific Technical Conference MANUFACTURING 2019, held in Poznan, Poland on May 19-22, 2019. The main focus is on showing best practices to use tools currently available in the enterprises to effectively improving industrial processes. Knowledge and production flow management, decision-making systems, production leveling, enterprise efficiency, as well as maintenance, modeling and simulation of production processes are just some of the topics discussed in this book, which offers a timely and practice-oriented reference guide for applied researchers, product engineers and product managers.

Zielgruppe

Research

Autoren/Hrsg.

Hamrol, Adam

Barraza, Manuel Francisco Suarez

Kujawinska, Agnieszka

Fachgebiete

• Technische Wissenschaften Maschinenbau | Werkstoffkunde Produktionstechnik
• Wirtschaftswissenschaften Betriebswirtschaft Management Projektmanagement

Inhaltsverzeichnis

A Framework for SME Performance Evaluation.- Environmental Management and Green Attitudes of the European SME Sector.- A Comparative Analysis of Various Production Organisation Forms on the Basis of Customised Manufacturing.- Tooling CAD Models Preparation Process for Automated Technology Design System.- Selection of Assembly Sequence for Manual Assembly Based on DFA Rating Factors.- Technology Management as a Process – a View from In-Depth Studies in Metal Processing Companies.- Formal Recording of Product Manufacturing Structure Oriented on Customer Based Production.- Multi-Objective Aggregate Production Planning Model Considering Overtime and Outsourcing Options under Fuzzy Seasonal Demand.