In-process pokayoke development in multiple automatic manufacturing processes

In this dissertation, three in-process pokayoke systems were developed to prevent defects from occurring, so as to ensure product quality for three automated manufacturing processes.;The first pokayoke development resulted in an in-process, gap-caused flash monitoring (IGFM) system for injection-molding machines. An accelerometer sensor was integrated in the proposed system to detect the difference of the vibration signals between flash and non-flash products. By sub-grouping every two consecutive molded parts with the vibration signal, the online statistical process control (OLSPC) was able to monitor 100% of the molded products. The threshold of this system established by the SPC approach can determine if flash occurred when the machine was in process. The testing results indicated that the accuracy of this IGFM system was 94.7% when flash is caused by a mold-closing gap.;The second pokayoke development led to an in-process surface roughness adaptive control (ISRAC) system for CNC end milling operations. A multiple linear regression algorithm was successfully employed to generate the models for predicting surface roughness and adaptive feed rate change in real time. Not only were the machining parameters included in the ISRAC pokayoke system, but also the cutting force signals collected by a dynamometer sensor. The testing results showed this proposed ISRAC system was able to predict surface roughness in real time with an accuracy of 91.5%, and could successfully implement adaptive control 100% of the time during milling operations.;The third pokayoke development brought an in-process surface roughness adaptive control (ISRAC) system in CNC turning operations. This system employed a back-propagation (BP) neural network algorithm to train the models for in-process surface roughness prediction and adaptive parameter control. In addition to the machining parameters, vibration signals in the Z direction used as an input variable to the neural network system were included for training. The test runs showed this pokayoke system was able to predict surface roughness in real time with an accuracy of 92.5%. The 100% success rate for adaptive control proved that this proposed system could be implemented to adaptively control surface roughness during turning operations

Mass Production Processes

It is always hard to set manufacturing systems to produce large quantities of standardized parts. Controlling these mass production lines needs deep knowledge, hard experience, and the required related tools as well. The use of modern methods and techniques to produce a large quantity of products within productive manufacturing processes provides improvements in manufacturing costs and product quality. In order to serve these purposes, this book aims to reflect on the advanced manufacturing systems of different alloys in production with related components and automation technologies. Additionally, it focuses on mass production processes designed according to Industry 4.0 considering different kinds of quality and improvement works in mass production systems for high productive and sustainable manufacturing. This book may be interesting to researchers, industrial employees, or any other partners who work for better quality manufacturing at any stage of the mass production processes

Industry 4.0 technologies for manufacturing sustainability: A systematic review and future research directions

Recent developments in manufacturing processes and automation have led to the new industrial revolution termed “Industry 4.0”. Industry 4.0 can be considered as a broad domain which includes: data management, manufacturing competitiveness, production processes and efficiency. The term Industry 4.0 includes a variety of key enabling technologies i.e., cyber physical systems, Internet of Things, artificial intelligence, big data analytics and digital twins which can be considered as the major contributors to automated and digital manufacturing environments. Sustainability can be considered as the core of business strategy which is highlighted in the United Nations (UN) Sustainability 2030 agenda and includes smart manufacturing, energy efficient buildings and low-impact industrialization. Industry 4.0 technologies help to achieve sustainability in business practices. However, very limited studies reported about the extensive reviews on these two research areas. This study uses a systematic literature review approach to find out the current research progress and future research potential of Industry 4.0 technologies to achieve manufacturing sustainability. The role and impact of different Industry 4.0 technologies for manufacturing sustainability is discussed in detail. The findings of this study provide new research scopes and future research directions in different research areas of Industry 4.0 which will be valuable for industry and academia in order to achieve manufacturing sustainability with Industry 4.0 technologies

Origin of Maternal Age Effect in Congenital Heart Disease Risk for Offspring

Increasing maternal age is widely acknowledged to lead to greater likelihood of pregnancy complications and congenital abnormalities, but the basis of this effect has not been well studied. Often dismissed as the product of oocyte ageing, the mechanistic basis of this maternal age effect is likely more complex. Congenital heart disease is a classic complex disease with multiple genetic and environmental modifiers, including maternal age. Maternal ageing is a known risk-factor in humans, and has been shown to exist in an Nkx2-5 haploinsufficient mouse model for the disease. This mouse model\u27s maternal age risk is dependent upon strain background, with C57BL/6N pure line and FVB/N x C57BL/6N F2 intercross pups being at risk due to maternal ageing, and A/J x C57BL/6N F2 intercrosses showing no maternal age risk. This indicates a maternal genetic component to maternal age risk, and implies that though ageing is inevitable, the negative effects on offspring are not. Using this model, this study examines whether the maternal age effect is due to oocyte ageing or a maternally intrinsic factor, shows a remediating treatment for maternal age risk, and defines epigenetic changes in offspring resulting from maternal ageing. Reciprocal ovarian transplants between old and young FVB/N x C57BL/6N F1 mothers were used to localize the basis of the maternal age effect to the mother. In spite of ovulating from ovaries aged well beyond the mouse\u27s normal reproductive life span, young mothers were at no higher risk for ventricular septal defects (VSD), while old mothers showed a persistent high risk for VSD in spite of ovulating young oocytes. Voluntary exercise experiments where FVB/N x C57BL/6N F1 mothers were given access to running wheels over the course of their lifetime showed that exercise decreased maternal age risk to levels indistinguishable from that of young mothers. Additionally, late-onset exercise was shown to be effective at reducing maternal age risk after just three months\u27 exposure, even with no overt changes in body mass, composition, or glucose tolerance. To study the impact of maternal ageing on epigenetic profiles, reduced representation bisulfite sequencing was used to compare aged and young sedentary fetal hearts and aged exercise fetal heart tissue. These comparisons showed eight differentially methylated regions, altered by maternal ageing but recovered by exercise treatment. These studies are conclusive proof that nonsyndromic maternal age risk is not due to oocyte ageing, but instead to a modifiable, maternally intrinsic risk factor. These studies also suggest the possibility of exercise as a prescription to prevent or turn back maternal age\u27s negative impacts. Exercise as an intervention poses tempting possibilities as a safe intervention for at-risk populations. Further investigation into the mechanistic influence of epigenetics in this effect may identify risk biomarkers for testing in maternal populations, and may provide keys to the underlying genetic architecture for congenital malformations such as congenital heart disease

Reducing the Scrap Rate in Manufacturing SMEs Through Lean Six Sigma Methodology: An Action Research

The aim of this project was to investigate operational benefits of the Lean Six Sigma (LSS) methodology to reduce the scrap rate in an automated production line of a first tier supplier of automotive sector. This is an action research case study using LSS methodology in fully automated sub-process of the manufacturers. The implementation of LSS methodology had an effective and significant impact on the scrap rate reduction with increased First Run Yield (FRY) and waste reduction leading to significant financial impact at this scale. The research investigation needs to be fully controlled by the team in order to correctly gauge the effect of any changes made to the process. This action research can be replicated in other sub- processes of the production line and other processes of the company. This project addresses novelty about effectiveness of LSS methodology to reduce scrap rate and add value to automated processes in first-tier manufacturing SMEs supplying automotive sector. The project had greater saving than expected by the managers at £98k per annum. The approach of this research project combines proven statistical tools with some basic but effective lean tools to be applied in an original sequence in order to design robust product and match manufacturing capabilities

Production Engineering and Management

It is our pleasure to introduce the seventh edition of the International Conference on Production Engineering and Management (PEM), an event that is the result of the joint effort of the University of Trieste and the Ostwestfalen- Lippe University of Applied Sciences. The conference has been established as an annual meeting under the Double Degree Master Program “Production Engineering and Management” by the two partner universities. This year the conference is hosted at the university campus in Pordenone. The main goal of the conference is to offer students, researchers and professionals in Germany, Italy and abroad, an opportunity to meet and exchange information, discuss experience, specific practices and technical solutions for planning, design and management of manufacturing and service systems and processes. As always, the conference is a platform aimed at presenting research projects, introducing young academics to the tradition of symposiums and promoting the exchange of ideas between the industry and the academy. This year’s special focus is on industry sustainability, which is currently a major topic of discussion among experts and professionals. Sustainability can be considered as a requirement for any modern production processes and systems, and also has to be embedded in the context of Industry 4.0. In fact, the features and problems of industry 4.0 have been widely discussed in the last editions of the PEM conference, in which efficiency and waste reduction emerged as key factors. The study and development of the connections between future industry and sustainability is therefore critical, as highlighted in the recent “German Sustainable Development Strategy and the 2030 Agenda”. Accordingly, the seventh edition of the PEM conference aims to offer a contribution to the debate. The conference program includes 25 speeches organized in six sessions. Three are specifically dedicated to “Direct Digital Manufacturing in the context of Industry 4.0” and “Technology and Business for Circular Economy and Sustainable Production”. The other sessions are covering areas of great interest and importance to the participants of the conference, which are related to the main focus: “Innovative Management Techniques and Methodologies”, “Industrial Engineering and Lean Management” and “Wood Processing Technologies and Furniture Production”. The proceedings of the conference include the articles submitted and accepted after a careful double-blind refereeing process

Six Sigma

In the new millennium the increasing expectation of customers and products complexity has forced companies to find new solutions and better alternatives to improve the quality of their products. Lean and Six Sigma methodology provides the best solutions to many problems and can be used as an accelerator in industry, business and even health care sectors. Due to its flexible nature, the Lean and Six Sigma methodology was rapidly adopted by many top and even small companies. This book provides the necessary guidance for selecting, performing and evaluating various procedures of Lean and Six Sigma. In the book you will find personal experiences in the field of Lean and Six Sigma projects in business, industry and health sectors