3,044 research outputs found
Enhanced cell controller for aerospace manufacturing
Aerospace manufacturing industry is unique in that production typically focuses on high variety and quality but extremely low volume. Manufacturing processes are also sometimes unique and not repeatable and, hence, costly. Production is getting more expensive with the introduction of industrial robots and their cells. This paper describes the development of the Flexa Cell Coordinator (FCC), a system that is providing a solution to manage resources at assembly cell level. It can control, organise and coordinate between the resources and is capable of controlling remote cells and resources because of its distributed nature. It also gives insight of a system to the higher management via its rich reporting facility and connectivity with company systems e.g., Enterprise Resource Planner (ERP). It is able to control various kinds of cells and resources (network based) which are not limited to robots and machines. It is extendable and capable of adding multiple numbers of cells inside the system. It also provides the facility of scheduling the task to avoid the deadlocking in the process. In FCC resources (e.g., tracker) can also be shared between cells
Data Analysis in Automotive Industrial Cells
The manufacturing industry always has been one of the leading energy consumers, so
companies in this area are always trying to use the best tools provided by the evolution
of the technology, to analyse and lower the production costs. Many known studies don’t
mind inconveniences such as stopping the production of the factory to perform studies
or deep architecture improvements in the transport system.
The proposed solution offers two different sets of tools. A device adapter, that targets
the gather and storage of data, from industrial robotic cells devices, being the main requirement
for a data analysis application, and a data analysis system, that analyses the
stored data, without changing the existing production model. The analysis procedure
aims the energy usage of a cell and its robot, and the duration of the executed processes.
This solution was tested in two different robotic cells, that execute the same process.
Multiple executions with different robot velocities were performed in order to gather
the required data to provide an analysis and the conclusion was that, for both cells, the
energy usage for each executed product was lower when the robot speed was higher, and
that one of the cells is more efficient that other cell when executing at high speed but less
efficient on lower velocities
Defining flexibility of assembly workstations through the underlying dimensions and impacting drivers
The concept of mass customization is becoming increasingly important for manufacturers of assembled products. As a result, manufacturers face a high variety of products, small batch sizes and frequent changeovers. To cope with these challenges, an appropriate level of flexibility of the assembly system is required. A methodology for quantifying the flexibility level of assembly workstations could help to evaluate (and improve) this flexibility level at all times. That flexibility model could even be integrated into the standard workstation design process. Despite the general consensus among researchers that manufacturing flexibility is a multi-dimensional concept, there is still no consensus on its different dimensions. A Systematic Literature Review (SLR) shows that many similarities can be found in the multitude of flexibility dimensions. Through a series of interactive company workshops, we achieved to reduce them to a shortlist of 9 flexibility dimensions applicable to an assembly workstation. In addition, a first step was taken to construct a causal model of these flexibility dimensions and their determining factors, the so called drivers, through the Interpretive Structural Modelling (ISM) approach. In the next phase, a driver scoring mechanism will be initiated to achieve an overall assembly workstation flexibility assessment based on the scoring of drivers depending on the workstation design
Development of a reconfigurable assembly system with enhanced control capabilities and virtual commissioning
Thesis (M. Tech. (Engineering: Electrical)) -- Central University of technology, Free State, 2013The South African (SA) manufacturing industry requires developing similar levels of sophistication and expertise in automation as its international rivals to compete for global markets. To achieve this, manufacturing plants need to be managed extremely efficiently to ensure the quality of manufactured products and these plants must also have the relevant infrastructure. Furthermore, this industry must also compensate for rapid product introduction, product changes and short product lifespan. To support this need, this industry must engage in the current trend in automation known as reconfigurable manufacturing.
The aim of the study is to develop a reconfigurable assembly system with enhanced control capabilities by utilizing virtual commissioning. In addition, this system must be capable of assembling multiple different products of a product range; reconfigure to accommodate the requirements of these products; autonomously reroute the product flow and distribute workload among assembly cells; handle erroneous products; and implement enhanced control methods. To achieve this, a literature study was done to confirm the type of components to be used, reveal design issues and what characteristics such a system must adhere to. Software named DELMIA was used to create a virtual simulation environment to verify the system and simultaneously scrutinize the methods of verification. On completion, simulations were conducted to verify software functions, device movements and operations, and the control software of the system. Based on simulation results, the physical system was built, and then verified with a multi agent system as overhead control to validate the entire system. The final results showed that the project objectives are achievable and it was also found that DELMIA is an excellent tool for system verification and will expedite the design of a system. By obtaining these results it is indicated that companies can design and verify their systems earlier through virtual commissioning. In addition, their systems will be more flexible, new products or product changes can be introduced more frequently, with minimum cost and downtime. This will enable SA manufacturing companies to be more competitive, ensure increased productivity, save time and so ensure them an advantage over their international competition
Enhancing Future Assembly Information Systems – Putting Theory into Practice
The manufacturing industry is in a changing state where technology advancements change the mindset of how manufacturing systems will function in the future. Industry 4.0 provides manufacturing companies with new methods for improved decision-making processes and dynamic process control. Despite this ambition, the manufacturing industry is far away from implementing this approach in practice. Assembly information systems will play an even more vital role enabling information transfer from product design to shop floor assembly in the future. To prepare the industry for these changes that are foreseen and for those that are yet to be discovered, a learning factory environment is vital. Such an environment is intended to support the industry during the development of assembly information systems. This paper presents an industrial demonstrator which incorporates well-known methods for improving assembly work stations with the perspective on assembly information systems. These methods are still not widely used in manual assembly intense manufacturing companies. This demonstrator illustrates how established theories can be practically used when designing future assembly information systems. The demonstrator will be used to validate functionalities and requirements for future assembly information systems
Production control
This thesis analyzes important concepts in production control from the perspective of a typical manufacturing plant. The scope is further limited to include theory that is especially relevant for the case company. The case company is an electric motor manufacturer ABB Oy, Motors and Generators Vaasa. The purpose of the research is first to develop understanding of theoretical concepts regarding production control. Secondly the case company will be used as an example to show some applications of the concepts discussed. The goal is to find the most effective tools for the development of the case company’s production control.
The research is divided into three parts: a theoretical part based on literature on production control, to the analysis of the case company’s production control and to a simulation study. The main focus will be given to principles that are directly applicable by the management of a manufacturing plant. The purpose of simulation will be to further increase the understanding of the theory discussed and to show the contrast of some varying production control configurations.
The research problem is: How can theoretical frameworks regarding production control be used for significant improvement in a typical manufacturing plant such as the case company? By discussing and clarifying many of the practical activities and processes in production control with a theoretical framework, the research shows that understanding such a framework can give managers valuable insights and perspectives for the development of processes.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format
Learning and reuse of engineering ramp-up strategies for modular assembly systems
YesWe present a decision-support framework for speeding up the ramp-up of modular assembly systems by learning from past experience. Bringing an assembly system to the expected level of productivity requires engineers performing mechanical adjustments and changes to the assembly process to improve the performance. This activity is time-consuming, knowledge-intensive and highly dependent on the skills of the engineers. Learning the ramp-up process has shown to be effective for making progress faster. Our approach consists of automatically capturing information about the changes made by an operator dealing with disturbances, relating them to the modular structure of the machine and evaluating the resulting system state by analysing sensor data. The feedback thus obtained on applied adaptations is used to derive recommendations in similar contexts. Recommendations are generated with a variant of the k-nearest neighbour algorithm through searching in a multidimensional space containing previous system states. Applications of the framework include knowledge transfer among operators and machines with overlapping structure and functionality. The application of our method in a case study is discussed.Funded by the European Commission as part of the 7th Framework Program under the Grant agreement CP-FP 229208-2, FRAME project
Entwicklung und EinfĂĽhrung von Produktionssteuerungsverbesserungen fĂĽr die kundenorientierte Halbleiterfertigung
Production control in a semiconductor production facility is a very complex and timeconsuming task. Different demands regarding facility performance parameters are defined by customer and facility management. These requirements are usually opponents, and an efficient strategy is not simple to define. In semiconductor manufacturing, the available production control systems often use priorities to define the importance of each production lot. The production lots are ranked according to the defined priorities. This process is called dispatching. The priority allocation is carried out by special algorithms. In literature, a huge variety of different strategies and rules is available. For the semiconductor foundry business, there is a need for a very flexible and adaptable policy taking the facility state and the defined requirements into account. At our case the production processes are characterized by a low-volume high-mix product portfolio. This portfolio causes additional stability problems and performance lags. The unstable characteristic increases the influence of reasonable production control logic. This thesis offers a very flexible and adaptable production control policy. This policy is based on a detailed facility model with real-life production data. The data is extracted from a real high-mix low-volume semiconductor facility. The dispatching strategy combines several dispatching rules. Different requirements like line balance, throughput optimization and on-time delivery targets can be taken into account. An automated detailed facility model calculates a semi-optimal combination of the different dispatching rules under a defined objective function. The objective function includes different demands from the management and the customer. The optimization is realized by a genetic heuristic for a fast and efficient finding of a close-to-optimal solution. The strategy is evaluated with real-life production data. The analysis with the detailed facility model of this fab shows an average improvement of 5% to 8% for several facility performance parameters like cycle time per mask layer. Finally the approach is realized and applied at a typical high-mix low-volume semiconductor facility. The system realization bases on a JAVA implementation. This implementation includes common state-of-the-art technologies such as web services. The system replaces the older production control solution. Besides the dispatching algorithm, the production policy includes the possibility to skip several metrology operations under defined boundary conditions. In a real-life production process, not all metrology operations are necessary for each lot. The thesis evaluates the influence of the sampling mechanism to the production process. The solution is included into the system implementation as a framework to assign different sampling rules to different metrology operations. Evaluations show greater improvements at bottleneck situations. After the productive introduction and usage of both systems, the practical results are evaluated. The staff survey offers good acceptance and response to the system. Furthermore positive effects on the performance measures are visible. The implemented system became part of the daily tools of a real semiconductor facility.Produktionssteuerung im Bereich der kundenorientierten Halbleiterfertigung ist heutzutage eine sehr komplexe und zeitintensive Aufgabe. Verschiedene Anforderungen bezüglich der Fabrikperformance werden seitens der Kunden als auch des Fabrikmanagements definiert. Diese Anforderungen stehen oftmals in Konkurrenz. Dadurch ist eine effiziente Strategie zur Kompromissfindung nicht einfach zu definieren. Heutige Halbleiterfabriken mit ihren verfügbaren Produktionssteuerungssystemen nutzen oft prioritätsbasierte Lösungen zur Definition der Wichtigkeit eines jeden Produktionsloses. Anhand dieser Prioritäten werden die Produktionslose sortiert und bearbeitet. In der Literatur existiert eine große Bandbreite verschiedener Algorithmen. Im Bereich der kundenorientierten Halbleiterfertigung wird eine sehr flexible und anpassbare Strategie benötigt, die auch den aktuellen Fabrikzustand als auch die wechselnden Kundenanforderungen berücksichtigt. Dies gilt insbesondere für den hochvariablen geringvolumigen Produktionsfall. Diese Arbeit behandelt eine flexible Strategie für den hochvariablen Produktionsfall einer solchen Produktionsstätte. Der Algorithmus basiert auf einem detaillierten Fabriksimulationsmodell mit Rückgriff auf Realdaten. Neben synthetischen Testdaten wurde der Algorithmus auch anhand einer realen Fertigungsumgebung geprüft. Verschiedene Steuerungsregeln werden hierbei sinnvoll kombiniert und gewichtet. Wechselnde Anforderungen wie Linienbalance, Durchsatz oder Liefertermintreue können adressiert und optimiert werden. Mittels einer definierten Zielfunktion erlaubt die automatische Modellgenerierung eine Optimierung anhand des aktuellen Fabrikzustandes. Die Optimierung basiert auf einen genetischen Algorithmus für eine flexible und effiziente Lösungssuche. Die Strategie wurde mit Realdaten aus der Fertigung einer typischen hochvariablen geringvolumigen Halbleiterfertigung geprüft und analysiert. Die Analyse zeigt ein Verbesserungspotential von 5% bis 8% für die bekannten Performancekriterien wie Cycletime im Vergleich zu gewöhnlichen statischen Steuerungspolitiken. Eine prototypische Implementierung realisiert diesen Ansatz zur Nutzung in der realen Fabrikumgebung. Die Implementierung basiert auf der JAVA-Programmiersprache. Aktuelle Implementierungsmethoden erlauben den flexiblen Einsatz in der Produktionsumgebung. Neben der Fabriksteuerung wurde die Möglichkeit der Reduktion von Messoperationszeit (auch bekannt unter Sampling) unter gegebenen Randbedingungen einer hochvariablen geringvolumigen Fertigung untersucht und geprüft. Oftmals ist aufgrund stabiler Prozesse in der Fertigung die Messung aller Lose an einem bestimmten Produktionsschritt nicht notwendig. Diese Arbeit untersucht den Einfluss dieses gängigen Verfahrens aus der Massenfertigung für die spezielle geringvolumige Produktionsumgebung. Die Analysen zeigen insbesondere in Ausnahmesituationen wie Anlagenausfällen und Kapazitätsengpässe einen positiven Effekt, während der Einfluss unter normalen Produktionsbedingungen aufgrund der hohen Produktvariabilität als gering angesehen werden kann. Nach produktiver Einführung in einem typischen Vertreter dieser Halbleiterfabriken zeigten sich schnell positive Effekte auf die Fabrikperformance als auch eine breite Nutzerakzeptanz. Das implementierte System wurde Bestandteil der täglichen genutzten Werkzeuglandschaft an diesem Standort
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