Robotics in space-age manufacturing

Robotics technologies are developed to improve manufacturing of space hardware. The following applications of robotics are covered: (1) welding for the space shuttle and space station Freedom programs; (2) manipulation of high-pressure water for shuttle solid rocket booster refurbishment; (3) automating the application of insulation materials; (4) precision application of sealants; and (5) automation of inspection procedures. Commercial robots are used for these development programs, but they are teamed with advanced sensors, process controls, and computer simulation to form highly productive manufacturing systems. Many of the technologies are also being actively pursued in private sector manufacturing operations

A petri-net based methodology for modeling, simulation, and control of flexible manufacturing systems

Global competition has made it necessary for manufacturers to introduce such advanced technologies as flexible and agile manufacturing, intelligent automation, and computer-integrated manufacturing. However, the application extent of these technologies varies from industry to industry and has met various degrees of success. One critical barrier leading to successful implementation of advanced manufacturing systems is the ever-increasing complexity in their modeling, analysis, simulation, and control. The purpose of this work is to introduce a set of Petri net-based tools and methods to address a variety of problems associated with the design and implementation of flexible manufacturing systems (FMSs). More specifically, this work proposes Petri nets as an integrated tool for modeling, simulation, and control of flexible manufacturing systems (FMSs). The contributions of this work are multifold. First, it demonstrates a new application of PNs for simulation by evaluating the performance of pull and push diagrams in manufacturing systems. Second, it introduces a class of PNs, Augmented-timed Petri nets (ATPNs) in order to increase the power of PNs to simulate and control flexible systems with breakdowns. Third, it proposes a new class of PNs called Realtime Petri nets (RTPNs) for discrete event control of FMS s. The detailed comparison between RTPNs and traditional discrete event methods such as ladder logic diagrams is presented to answer the basic question \u27Why is a PN better tool than ladder logic diagram?\u27 and to justify the PN method. Also, a conversion procedure that automatically generates PN models from a given class of logic control specifications is presented. Finally, a methodology that uses PNs for the development of object-oriented control software is proposed. The present work extends the PN state-of-the-art in two ways. First, it offers a wide scope for engineers and managers who are responsible for the design and the implementation of modem manufacturing systems to evaluate Petri nets for applications in their work. Second, it further develops Petri net-based methods for discrete event control of manufacturing systems

The XDEM Multi-physics and Multi-scale Simulation Technology: Review on DEM-CFD Coupling, Methodology and Engineering Applications

The XDEM multi-physics and multi-scale simulation platform roots in the Ex- tended Discrete Element Method (XDEM) and is being developed at the In- stitute of Computational Engineering at the University of Luxembourg. The platform is an advanced multi- physics simulation technology that combines flexibility and versatility to establish the next generation of multi-physics and multi-scale simulation tools. For this purpose the simulation framework relies on coupling various predictive tools based on both an Eulerian and Lagrangian approach. Eulerian approaches represent the wide field of continuum models while the Lagrange approach is perfectly suited to characterise discrete phases. Thus, continuum models include classical simulation tools such as Computa- tional Fluid Dynamics (CFD) or Finite Element Analysis (FEA) while an ex- tended configuration of the classical Discrete Element Method (DEM) addresses the discrete e.g. particulate phase. Apart from predicting the trajectories of individual particles, XDEM extends the application to estimating the thermo- dynamic state of each particle by advanced and optimised algorithms. The thermodynamic state may include temperature and species distributions due to chemical reaction and external heat sources. Hence, coupling these extended features with either CFD or FEA opens up a wide range of applications as diverse as pharmaceutical industry e.g. drug production, agriculture food and processing industry, mining, construction and agricultural machinery, metals manufacturing, energy production and systems biology

Simulation modelling software approaches to manufacturing problems

Increased competition in many industries has resulted in a greater emphasis on developing and using advanced manufacturing systems to improve productivity and reduce costs. The complexity and dynamic behaviour of such systems, make simulation modelling one of the most popular methods to facilitate the design and assess operating strategies of these systems. The growing need for the use of simulation is reflected by a growth in the number of simulation languages and data-driven simulators in the software market. This thesis investigates which characteristics typical manufacturing simulators possess, and how the user requirements can be better fulfilled. For the purpose of software evaluation, a case study has been carried out on a real manufacturing system. Several simulation models of an automated system for electrostatic powder coating have been developed using different simulators. In addition to the evaluation of these simulators, a comprehensive evaluation framework has been developed to facilitate selection of simulation software for modelling manufacturing systems. Different hierarchies of evaluation criteria have been established for different software purposes. In particular, the criteria that have to be satisfied for users in education differ from those for users in industry. A survey has also been conducted involving a number of users of software for manufacturing simulation. The purpose of the survey was to investigate users' opinions about simulation software, and the features that they desire to be incorporated in simulation software. A methodology for simulation software selection is also derived. It consists of guidelines related to the actions to be taken and factors to be considered during the evaluation and selection of simulation software. On the basis of all the findings, proposals on how manufacturing simulators can be improved are made, both for use in education and in industry. These software improvements should result in a reduction in the amount of time and effort needed for simulation model development, and therefore make simulation more beneficial

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

An Ontology for Defect Detection in Metal Additive Manufacturing

A key challenge for Industry 4.0 applications is to develop control systems for automated manufacturing services that are capable of addressing both data integration and semantic interoperability issues, as well as monitoring and decision making tasks. To address such an issue in advanced manufacturing systems, principled knowledge representation approaches based on formal ontologies have been proposed as a foundation to information management and maintenance in presence of heterogeneous data sources. In addition, ontologies provide reasoning and querying capabilities to aid domain experts and end users in the context of constraint validation and decision making. Finally, ontology-based approaches to advanced manufacturing services can support the explainability and interpretability of the behaviour of monitoring, control, and simulation systems that are based on black-box machine learning algorithms. In this work, we provide a novel ontology for the classification of process-induced defects known from the metal additive manufacturing literature. Together with a formal representation of the characterising features and sources of defects, we integrate our knowledge base with state-of-the-art ontologies in the field. Our knowledge base aims at enhancing the modelling capabilities of additive manufacturing ontologies by adding further defect analysis terminology and diagnostic inference features

National Launch System: Structures and materials

The National Launch System provides an opportunity to realize the potential of Al-Li. Advanced structures can reduce weights by 5-40 percent as well as relax propulsion system performance specifications and reduce requirements for labor and materials. The effect on costs will be substantial. Advanced assembly and process control technologies also offer the potential for greatly reduced labor during the manufacturing and inspection processes. Current practices are very labor-intensive and, as a result, labor costs far outweigh material costs for operational space transportation systems. The technological readiness of new structural materials depends on their commercial availability, producibility and materials properties. Martin Marietta is vigorously pursuing the development of its Weldalite 049 Al-Li alloys in each of these areas. Martin Marietta is also preparing to test an automated work cell concept that it has developed using discrete event simulation

Design, Simulation, Manufacturing: The Innovation Exchange

The content of this book is based on the 3rd International Conference on Design, Simulation, Manufacturing: The Innovation Exchange (DSMIE-2020), held on June 9-12, 2020, in Kharkiv, Ukraine. This book reports on topics at the interface between manufacturing, materials, mechanical, and chemical engineering, with a special emphasis on design, simulation, and manufacturing issues. Specifically, it covers the development of computer-aided technologies for product design, the implementation of smart manufacturing systems and Industry 4.0 strategies, topics in technological assurance, numerical simulation, and experimental studies of cutting, milling, grinding, pressing, and profiling processes, as well as the development and implementation of advanced materials. It covers recent developments in the mechanics of solids and structures, numerical simulation of coupled problems, including wearing, compression, detonation, and collision, chemical process technology, including ultrasonic technology, capillary rising process, pneumatic classification, membrane electrolysis, and absorption process. Further, it reports on developments in the field of heat and mass transfer, energyefficient technologies, and industrial ecology. The book provides academics and professionals with extensive information on trends, technologies, challenges, and practice-oriented experience in the areas mentioned above

Coupling of interactive manufacturing operations simulation and immersive virtual reality

This paper presents a novel general-purpose simulation analysis application that combines concurrent operations simulation with the advanced data interrogation and user interaction capabilities of immersive virtual reality systems. The application allows for interactive modification of the simulation parameters, while providing the users with the available simulation information by effectively placing the operator in the midst of the environment being simulated. The major contribution of this research is the total integration of the immersive virtual reality environment with the simulation, allowing users in the environment to interactively change the inputs to the simulation as it is running. Implementation and functionality details of the developed application are presented. The experience of using the application to analyze a manufacturing operation in a collaborative scenario is also discussed

Intelligent Machining Systems

Machining is one of the most widespread manufacturing processes and plays a critical role in industries. As a matter of fact, machine tools are often called mother machines as they are used to produce other machines and production plants. The continuous development of innovative materials and the increasing competitiveness are two of the challenges that nowadays manufacturing industries have to cope with. The increasing attention to environmental issues and the rising costs of raw materials drive the development of machining systems able to continuously monitor the ongoing process, identify eventual arising problems and adopt appropriate countermeasures to resolve or prevent these issues, leading to an overall optimization of the process. This work presents the development of intelligent machining systems based on in-process monitoring which can be implemented on production machines in order to enhance their performances. Therefore, some cases of monitoring systems developed in different fields, and for different applications, are presented in order to demonstrate the functions which can be enabled by the adoption of these systems. Design and realization of an advanced experimental machining testbed is presented in order to give an example of a machine tool retrofit aimed to enable advanced monitoring and control solutions. Finally, the implementation of a data-driven simulation of the machining process is presented. The modelling and simulation phases are presented and discussed. So, the model is applied to data collected during an experimental campaign in order to tune it. The opportunities enabled by integrating monitoring systems with simulation are presented with preliminary studies on the development of two virtual sensors for the material conformance and cutting parameter estimation during machining processes