Generic Modeling Technique for Flexible and Highly Available Assembly Systems

Today's metadata models and metadata standards often focus on a specific media type only, lack combinability with other metadata models, or are limited with respect to the features they support. Thus they are not sufficient to describe the semantics of rich, structured multimedia documents. To overcome these limitations, we have developed a comprehensive model for representing multimedia metadata, the Multimedia Metadata Ontology (M3O). The M3O has been developed by an extensive analysis of related work and abstracts from the features of existing metadata models and metadata standards. It is based on the foundational ontology DOLCE+DnS Ultralight and makes use of ontology design patterns. The M3O serves as generic modeling framework for integrating the existing metadata models and metadata standards rather than replacing them. As such, the M3O can be used internally as semantic data model within complex multimedia applications such as authoring tools or multimedia management systems. To make use of the M3O in concrete multimedia applications, a generic application programming interface (API) has been implemented based on a sophisticated persistence layer that provides explicit support for ontology design patterns. To demonstrate applicability of the M3O API, we have integrated and applied it with our SemanticMM4U framework for the multi-channel generation of semantically annotated multimedia documents.

The integration of terminologies is still a challenging problem in medical informatics research and software applications, due to the high number of heterogeneous terminologies. In this paper, we present a generic API (Application Programming Interface) for a multi-terminology multilingual terminology service, and PyMedTermino, its open-source implementation in Python with 5 terminological resources (ICD10, SNOMED CT, MedDRA, CDF, VCM iconic language) and the UMLS compendium. This service has been designed for research and educational purpose. It offers various advanced functionalities rarely present in terminology services.

<p>The Free Evaluation System Framework (Freva - freva.met.fu-berlin.de) is a software infrastructure for standardized data and tool solutions in Earth system science. Freva runs on high performance computers to handle customizable evaluation systems of research projects, institutes or universities. It combines different software technologies into one common hybrid infrastructure, including all features present in the shell and web environment. The database interface satisfies the international standards provided by the Earth System Grid Federation (ESGF). Freva indexes different data projects into one common search environment by storing the meta data information of the self-describing model, reanalysis and observational data sets in a database. This implemented meta data system with its advanced but easy-to-handle search tool supports users, developers and their plugins to retrieve the required information. A generic application programming interface (API) allows scientific developers to connect their analysis tools with the evaluation system independently of the programming language used. Users of the evaluation techniques benefit from the common interface of the evaluation system without any need to understand the different scripting languages. Facilitation of the provision and usage of tools and climate data automatically increases the number of scientists working with the data sets and identifying discrepancies. The integrated webshell (shellinabox) adds a degree of freedom in the choice of the working environment and can be used as a gate to the research projects HPC. Plugins are able to integrate their e.g. post-processed results into the database of the user. This allows e.g. post-processing plugins to feed statistical analysis plugins, which fosters an active exchange between plugin developers of a research project. Additionally, the history and configuration sub-systemstores every analysis performed with the evaluation system in a database. Configurations and results of the toolscan be shared among scientists via shell or web system. Therefore, plugged-in tools benefit from transparency and reproducibility. Furthermore, if configurations match while starting an evaluation plugin, the system suggests touse results already produced by other users – saving CPU/h, I/O, disk space and time. The efficient interaction between different technologies improves the Earth system modeling science framed by Freva.</p><p>New Features and aspects of further development and collaboration are discussed.</p><p> </p>

Current approaches to manufacturing must evolve to respond to increasing demands for short product life cycles and customised products. Adaptive manufacturing systems integrate advanced technologies, automation, and data-driven methodologies to develop adaptable, efficient, and responsive production processes. Central to this concept is the emphasis on human involvement and fostering synergy between human operators and the manufacturing system. Significant changes to the system’s controller are required to achieve adaptivity, with programmable logic controllers (PLCs) being a common controller type. After the necessary changes to the configuration of the manufacturing system, the PLC should be reconfigured to orchestrate the new required behaviour. Automated reconfiguration is vital to rapidly responding to change, but some changes cannot be entirely achieved without human input in collaboration with automated methods. Conventional practices in PLC programming include manual, repetitive coding practices subject to errors. As a result, to ensure operational safety, the changes must be tested before being deployed to operations, ensuring it is error-free. This paper presents a methodology to automatically reconfigure the simulation environment and controller in response to a new product request. We automate the PLC code generation and testing practices to support and free up the operators when performing repetitive manufacturing reconfiguration tasks. The methodology is based on human learning, software automation, customised program development, knowledge graphs, and Graph Neural Networks (GNNs). The presented solution is a generic, vendor-agnostic, and interoperable solution that facilitates information exchange among multiple heterogeneous environments. Lastly, we have validated the methodology as a proof of concept at an adaptive assembly cell at the University of Nottingham in the United Kingdom.

This paper describes the design and development of a re‐configurable dual‐robot assembly system using off‐the‐shelf re‐configurable pneumatic modules, Hall‐effect sensors, a vision system, and a programmable logic controller (PLC). Each robot arm consists of three sets of pneumatic modules and a pneumatic gripper. Each module consists of a pneumatic housing, an air cylinder, and a Hall‐effect sensor, and provides one degree of freedom. Solenoids are used to redirect airflow and thereby extend and/or retract the air cylinder. A vision system is used for fixture inspection. A conveyor and part stopper are designed to transfer and stop pallets. All these modules, the gripper, the part stopper, and the vision system are controlled and synchronized using a PLC. At the end of this paper, a framework for making the system over the Web for remote operation and diagnosis is proposed and described.

Modular production system concept for a water tap assembly

We 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.

Software development for programmable logical controllers is usually based on low-level languages such as the instruction list or the ladder diagram. At the same time, the programmer looks at a machine or an assembly system in a bit-oriented way; he translates the operational sequences into logical and/or time based combinations of binary signals described by the means of Boolean algebra. This classical method causes a lot of problems in reality so it should be improved. It is the aim of the report to show a way developing PLC-software graphically and interactively within a Virtual Reality (VR) based system (VPLC).

The ATLAS Error Reporting provides a service that allows experts and shift crew to track and address errors relating to the data taking components and applications. This service, called the Error Reporting Service (ERS), gives to software applications the opportunity to collect and send comprehensive data about run-time errors, to a place where it can be intercepted in real-time by any other system component. Other ATLAS online control and monitoring tools use the ERS as one of their main inputs to address system problems in a timely manner and to improve the quality of acquired data.The actual destination of the error messages depends solely on the run-time environment, in which the online applications are operating. When an application sends information to ERS, depending on the configuration, it may end up in a local file, a database, distributed middleware which can transport it to an expert system or display it to users. Thanks to the open framework design of ERS, new information destinations can be added at any moment without touching the reporting and receiving applications.The ERS Application Program Interface (API) is provided in three programming languages used in the ATLAS online environment: C++, Java and Python. All APIs use exceptions for error reporting but each of them exploits advanced features of a given language to simplify the end-user program writing. For example, as C++ lacks language support for exceptions, a number of macros have been designed to generate hierarchies of C++ exception classes at compile time. Using this approach a software developer can write a single line of code to generate a boilerplate code for a fully qualified C++ exception class declaration with arbitrary number of parameters and multiple constructors, which encapsulates all relevant static information about the given type of issues. When a corresponding error occurs at run time, the program just need to create an instance of that class passing relevant values to one of the available class constructors and send this instance to ERS.This paper presents the original design solutions exploited for the ERS implementation and describes how it was used during the first ATLAS run period. The cross-system error reporting standardization introduced by ERS was one of the key points for the successful implementation of automated mechanisms for online error recovery.

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In this article, we present a client/server augmented reality (AR) system for viewing complex assembly models on mobile phones. Complex model information is located on a PC which takes care of all of the heavy AR tracking and rendering computation. A camera phone is used as a client to show this information, augmented on still images as animated view. The mobile phone interface also supports correct masking of the assembly pieces as they come together, as well as a graphics only viewing mode intended for better understanding of the assembly process. In addition to describing the mobile augmented assembly system we present results from two pilot user studies evaluating elements of the user interface. INTRODUCTION In order to remain competitive, today’s industry is employing a growing number of product variations with shorter and shorter life cycles, requiring efficient ways to handle the production planning and processing. Assembly line workers face more and more complex tasks and an increasing memory load is posed by the new production needs. Experienced workers may be able to handle several product variants at the same time, but new workers require training and guidance to handle the work tasks. Related activities such as maintenance and repair also require a lot of know-how of complex products. Guidance in assembly tasks is commonly provided by using printed blueprints or other documents. However, these are mainly two dimensional images or text while the real assembly task is three dimensional, making the relationship between parts hard to understand. Computer based technologies have been developed such as electronic guides, multimedia training material and interactive documents. However, these typically require the user to turn away from the assembly task to study a computer screen separate from the workspace. In our research we explore how augmented reality (AR) technology can be used to provide more intuitive guides to assist with assembly, repair and training tasks. With AR technology, synthetic objects can be merged with the user’s view of the real world so that the user can perform the assembly task without needing to look at a separate screen. The virtual objects appear in the correct position so that AR enables the creation of realistic looking 3D animated assembly “manuals”. Other researchers have developed prototype AR systems for supporting assembly tasks. These are typically based on head mounted displays (HMDs) connected to desktop or wearable computers. However, wearable computers are relatively expensive, they have a short battery life, and taking them into a harsh industrial environment is not always possible. Head mounted displays can also be bulky, they involve safety issues, and many workers are reluctant to wear them. To overcome these disadvantages, we are interested in developing a reliable mobile phone based AR assembly system. Today’s mobile phones have fast processors, significant memory, 3D graphics support, and high resolution displays. They contain various accessories that can be used for developing mobile AR applications such as good quality cameras, connectivity by Bluetooth, WLAN and GPRS, and various SAM.700.003.1155

UNIX on a loosely coupled architecture: The CHORUS/MiX approach

Modular fixtures are one of the important aspects of manufacturing. This paper presents a desktop VR system for modular fixture design. The virtual environment is designed and the design procedure is proposed. It assists the designer to make the feasible design decisions effectively and efficiently. A hierarchical data model is proposed to represent the modular fixture assembly. Based on this structure, the user can manipulate the virtual models precisely in VE during the design and assembly processes. Moreover, the machining simulation for manufacturing interaction checking is discussed and implemented. Finally, the case study has demonstrated the functionality of the proposed system. Compared with the immersive VR system, the proposed system has offered an affordable and portable solution for modular fixtures design

An integrated framework for design, management and operation of reconfigurable assembly systems

Assembly 4.0: Wheel Hub Nut Assembly Using a Cobot