4,386 research outputs found
Improving transferability between different engineering stages in the development of automated material flow modules
For improving flexibility and robustness of the engineering of automated
production systems (aPS) in case of extending, reducing or modifying parts,
several approaches propose an encapsulation and clustering of related
functions, e.g. from the electrical, mechanical or software engineering, based
on a modular architecture. Considering the development of these modules, there
are different stages, e.g. module planning or functional engineering, which
have to be completed. A reference model that addresses the different stages for
the engineering of aPS is proposed by AutomationML. Due to these different
stages and the integration of several engineering disciplines, e.g. mechanical,
electrical/electronic or software engineering, information not limited to one
discipline are stored redundantly increasing the effort to transfer information
and the risk of inconsistency. Although, data formats for the storage and
exchange of plant engineering information exist, e.g. AutomationML, fixed
domain specific structures and relations of the information, e.g. for automated
material flow systems (aMFS), are missing. This paper presents the integration
of a meta model into the development of modules for aMFS to improve the
transferability and consistency of information between the different
engineering stages and the increasing level of detail from the coarse-grained
plant planning to the fine-grained functional engineering.Comment: 11 pages, https://ieeexplore.ieee.org/abstract/document/7499821
Spacelab software development and integration concepts study report, volume 1
The proposed software guidelines to be followed by the European Space Research Organization in the development of software for the Spacelab being developed for use as a payload for the space shuttle are documented. Concepts, techniques, and tools needed to assure the success of a programming project are defined as they relate to operation of the data management subsystem, support of experiments and space applications, use with ground support equipment, and for integration testing
"The Shift from Belt Conveyor Line to Work-cell Based Assembly Systems to Cope with Increasing Demand Variation and Fluctuation in The Japanese Electronics Industries"
As consumption patterns become increasingly sophisticated and manufacturers strive to improve their competitiveness, not only offering higher quality at competitive costs, but also by providing broader mix of products, and keeping it attractive by launching successively new products, the turbulence in the markets has intensified. This has impelled leading manufacturers to search the development of alternative production systems supposed to enable them operate more responsively. This paper discusses the trend of abandoning the strategy of relying on factory automation technologies and conveyor-based assembly lines, and shifting towards more human-centered production systems based on autonomous work-cells, observed in some industries in Japan (e.g. consumer electronics, computers, printers) since mid-1990s. The purpose of this study is to investigate this trend which is seemingly uneconomic to manufacturers established in a country where labor costs are among the highest in the world, so as to contribute in the elucidation of its background and rationality. This work starts with a theoretical review linking the need to cope with nowadays' market turbulence with the issue of nurturing more agile organizations. Then, a general view of the diffusion trend of work-cell based assembly systems in Japanese electronics industries is presented, and some empirical facts gathered in field studies conducted in Japan are discussed. It is worthy mentioning that the abandonment of short cycle-time tasks performed along conveyor lines and the organization of workforce around work-cells do not imply a rejection of the lean production paradigm and its distinctive process improvement approach. High man-hour productivity is realized as a key goal to justify the implementation of work-cells usually devised to run in longer cycle-time, and the moves towards this direction has been strikingly influenced by the kaizen philosophy and techniques that underline typical initiatives of lean production system implementation. Finally, it speculates that even though the subject trend is finding wide diffusion in the considered industries, it should not be regarded as a panacea. In industries such as manufacturing of autoparts, despite the notable product diversification observed in the automobile market, its circumstances have still allowed the firms to rely on capital-intensive process, and this has sustained the development of advanced manufacturing technologies that enable the agile implementation and re-configuration of highly automated assembly lines.
State-of-the-Art Review and Synthesis: A Requirement-based Roadmap for Standardized Predictive Maintenance Automation Using Digital Twin Technologies
Recent digital advances have popularized predictive maintenance (PMx),
offering enhanced efficiency, automation, accuracy, cost savings, and
independence in maintenance. Yet, it continues to face numerous limitations
such as poor explainability, sample inefficiency of data-driven methods,
complexity of physics-based methods, and limited generalizability and
scalability of knowledge-based methods. This paper proposes leveraging Digital
Twins (DTs) to address these challenges and enable automated PMx adoption at
larger scales. While we argue that DTs have this transformative potential, they
have not yet reached the level of maturity needed to bridge these gaps in a
standardized way. Without a standard definition for such evolution, this
transformation lacks a solid foundation upon which to base its development.
This paper provides a requirement-based roadmap supporting standardized PMx
automation using DT technologies. A systematic approach comprising two primary
stages is presented. First, we methodically identify the Informational
Requirements (IRs) and Functional Requirements (FRs) for PMx, which serve as a
foundation from which any unified framework must emerge. Our approach to
defining and using IRs and FRs to form the backbone of any PMx DT is supported
by the track record of IRs and FRs being successfully used as blueprints in
other areas, such as for product development within the software industry.
Second, we conduct a thorough literature review spanning fields to determine
the ways in which these IRs and FRs are currently being used within DTs,
enabling us to point to the specific areas where further research is warranted
to support the progress and maturation of requirement-based PMx DTs.Comment: (1)This work has been submitted to the IEEE for possible publication.
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Knowledge discOvery And daTa minINg inteGrated (KOATING) Moderators for collaborative projects
A major issue in any multidiscipline collaborative project is how to best share and simultaneously exploit different types of expertise, without duplicating efforts or inadvertently causing conflicts or loss of efficiency through misunderstanding of individual or shared goals. Moderators are knowledge based systems designed to support collaborative teams by raising awareness of potential problems or conflicts. However, the functioning of a Moderator is limited by the knowledge it has about the team members. Knowledge acquisition, learning and updating of knowledge are the major challenges for a Moderator's implementation. To address these challenges a Knowledge discOvery And daTa minINg inteGrated (KOATING) framework is presented for Moderators to enable them to continuously learn from the operational databases of the company and semi-automatically update their knowledge about team members. This enables the reuse of discovered knowledge from operational databases within collaborative projects. The integration of knowledge discovery in database (KDD) techniques into the existing Knowledge Acquisition Module of a moderator enables hidden data dependencies and relationships to be utilised to facilitate the moderation process. The architecture for the Universal Knowledge Moderator (UKM) shows how Moderators can be extended to incorporate a learning element which enables them to provide better support for virtual enterprises. Unified Modelling Language diagrams were used to specify the ways to design and develop the proposed system. The functioning of a UKM is presented using an illustrative example
Machine learning in bioprocess development: From promise to practice
Fostered by novel analytical techniques, digitalization and automation, modern bioprocess development provides high amounts of heterogeneous experimental data, containing valuable process information. In this context, data-driven methods like machine learning (ML) approaches have a high potential to rationally explore large design spaces while exploiting experimental facilities most efficiently. The aim of this review is to demonstrate how ML methods have been applied so far in bioprocess development, especially in strain engineering and selection, bioprocess optimization, scale-up, monitoring and control of bioprocesses. For each topic, we will highlight successful application cases, current challenges and point out domains that can potentially benefit from technology transfer and further progress in the field of ML
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