Investigation into inspection system utilisation for advanced manufacturing systems.

Masters Degree. University of KwaZulu-Natal, Durban.Varied inspection is an aperiodic inspection utilisation methodology that was developed for advanced manufacturing systems. The inspection scheme was created as a solution to improve manufacturing performance where inspection hinders production, such as cases where inspection time is significantly larger than machining time. Frequent inspection impedes production cycles which result in undesirable blocking, starving, low machine utilisation, increased lead time and work-in-process. The aim of the inspection strategy was to aid manufacturing metrics by adjusting inspection utilisation through multiple control methods. The novelty of the research lies in using an inspection strategy for improved manufacturing performance. Quality control was traditionally viewed as an unintegrated aspect of production. As such, quality control was only used as a tool for ensuring certain standards of products, rather than being used as a tool to aid production. The problem was solved by using the amount of inspection performed as a variable, and changing that variable based on the needs of the manufacturing process. “Inspection intensity” was defined as the amount of inspection performed on a part stream and was based on inputs such as part quality, required production rates, work-in-process requirements among other factors. Varied inspection was executed using a two-level control architecture of fuzzy controllers. Lower level controllers performed varied inspection while an upper level supervisory controller measured overall system performance and made adjustments to lower level controllers to meet system requirements. The research was constrained to simulation results to test the effects of varied inspection on different manufacturing models. Simulation software was used to model advanced manufacturing systems to test the effects of varied inspection against traditional quality control schemes. Matlab’s SimEvents® was used for discrete-event simulation and Fuzzy Logic Toolbox® was used for the controller design. Through simulation, varied inspection was used to meet production needs such as reduced manufacturing lead time, reduced work-in-process, reduced starvation and blockage, and reduced appraisal costs. Machine utilisation was increased. The contribution of the research was that quality control could be used to aid manufacturing systems instead of slowing it down. Varied inspection can be used as a flexible form of inspection. The research can be used as a control methodology to improve the usage of inspection systems to enhance manufacturing performance

UD Receives $50,000 Grant from GE Foundation for Advanced Manufacturing

News release announces that the University of Dayton has received a $50,000 grant from the General Electric Foundation to help set up an Advanced Manufacturing Systems Center in the School of Engineering

AI-enabled modeling and monitoring of data-rich advanced manufacturing systems

The infrastructure of cyber-physical systems (CPS) is based on a meta-concept of cybermanufacturing systems (CMS) that synchronizes the Industrial Internet of Things (IIoTs), Cloud Computing, Industrial Control Systems (ICSs), and Big Data analytics in manufacturing operations. Artificial Intelligence (AI) can be incorporated to make intelligent decisions in the day-to-day operations of CMS. Cyberattack spaces in AI-based cybermanufacturing operations pose significant challenges, including unauthorized modification of systems, loss of historical data, destructive malware, software malfunctioning, etc. However, a cybersecurity framework can be implemented to prevent unauthorized access, theft, damage, or other harmful attacks on electronic equipment, networks, and sensitive data. The five main cybersecurity framework steps are divided into procedures and countermeasure efforts, including identifying, protecting, detecting, responding, and recovering. Given the major challenges in AI-enabled cybermanufacturing systems, three research objectives are proposed in this dissertation by incorporating cybersecurity frameworks. The first research aims to detect the in-situ additive manufacturing (AM) process authentication problem using high-volume video streaming data. A side-channel monitoring approach based on an in-situ optical imaging system is established, and a tensor-based layer-wise texture descriptor is constructed to describe the observed printing path. Subsequently, multilinear principal component analysis (MPCA) is leveraged to reduce the dimension of the tensor-based texture descriptor, and low-dimensional features can be extracted for detecting attack-induced alterations. The second research work seeks to address the high-volume data stream problems in multi-channel sensor fusion for diverse bearing fault diagnosis. This second approach proposes a new multi-channel sensor fusion method by integrating acoustics and vibration signals with different sampling rates and limited training data. The frequency-domain tensor is decomposed by MPCA, resulting in low-dimensional process features for diverse bearing fault diagnosis by incorporating a Neural Network classifier. By linking the second proposed method, the third research endeavor is aligned to recovery systems of multi-channel sensing signals when a substantial amount of missing data exists due to sensor malfunction or transmission issues. This study has leveraged a fully Bayesian CANDECOMP/PARAFAC (FBCP) factorization method that enables to capture of multi-linear interaction (channels × signals) among latent factors of sensor signals and imputes missing entries based on observed signals

Strategic and tactical management of advanced manufacturing systems : a survey of British industry

British manufacturing Abstraot Companies have been slower to automate their facilities, and computerise their information systems, than many of their overseas competitors in Europe, North America and Japan. Initially, this research studied advanced manufacturing technology, (AMT), systems theory, the UK economy and investigated the underlying reasons for and against company' s decisions to automate. Automating procedures were studied for a sample of 20 Engineering companies with particular attention paid to their; systemic approach to implementing AMT, inter-business activity communications, individual company strategies, operational tactics, and implications from previous installations. This information was supported by questionnaires targeted at UK design engineers' and equipment suppliers. Interviews with Trade Unions, financial institutions, professional institutions and Government, were also arranged. The research found that correctly implemented AMT, with the optimum balance of flexibility and complexity, improved businesses' competitiveness, although many operational efficiencies could be attained merely by rationalising existing systems. When a company implements AMT it is critical that they synchronise the equipment with additional complementary systems and manufacturing resources. However, every company has their own unique solutions due to the historical evolution of factory facilities, product ranges and employee skills. The restrictive practices adopted the financial accountants and many of the Trade Union were found to restrain the rate of implementation for AMT and the move towards total integrated businesses. The research analysis yielded a ten point model for the strategic and tactical management of advanced manufacturing systems. Finally, the work concludes by identifying "accounting systems", and procedures for "designing for manufacture", as areas which deserve further investigation