The diversity of requirements and the frequency of change in the market can only be competed with dynamicity and responsiveness in both production and planning systems. In this sense, working principles of a novel workload control method, called continuous precise workload control are presented in this paper. The implementation of the method is based on a multi-agent based architecture. The presented approach generates dynamic non periodic release decisions exploiting real time shop floor information. The performance of the system and correlation of norm value against the assessment range are investigated through an experimented test case.
The variability in the market conditions is growing in terms of its frequency of change and range of diversity. In response to this new industrial panorama, research on production systems is aiming to achieve truly reconfigurable shop floors. Frequent changes in such systems require also frequent re-planning with updated information. In this regard the Continuous Precise Workload Control method, is a recent approach aiming at precise control of workload in the shop floor with the use of direct load graphs. Supported by a multi-agent platform, it generates dynamic non-periodic release decisions exploiting real time shop floor information. The study in this paper is two folded; (1) in order to highlight its distinctive characteristics, the presented workload approach is defined in terms of eight dimensions of the workload control concept and (2) the penalty of idleness which affects the decision of release is analyzed by an experiment design in order to investigate its correlation with two critical parameters, norm value and assessment range. The results show that the idleness penalty factor decreases the idleness of the resources up to a point where the adverse effect is initiated. Besides there are strong indications towards the correlation of idleness penalty factor with the norm value.
The variability in the market conditions is growing in terms of its frequency of change and range of diversity. In response to this new industrial panorama, research on production systems is aiming to achieve highly reconfigurable shop floors. Frequent changes in such systems require also frequent re-planning with updated information. In this regard the Continuous Precise Workload Control method, is a recent approach aiming at precise control of workload in shop floor with the use of direct load graphs. Supported by a multi-agent platform, it generates dynamic non-periodic release decisions exploiting real time shop floor information. The study in this paper is two folded; (1) the presented workload approach is defined in terms of eight dimensions of the workload control concept in order to highlight its distinctive characteristics and (2) the impact of idleness penalty factor is analyzed by an experiment design in order to investigate its effect on the job release decision. The results show that the idleness penalty factor decreases the idleness of the resources up to a point where the adverse effect is initiated.
Purpose – Evolvable production systems enable fully reconfiguration capabilities on the shop floor through process-oriented modularity and multiagent-based distributed control. To be able to benefit architectural and operational characteristics of evolvable systems, there is a need of a newplanning approach which links shop floor characteristics and planning operations. This paper seeks to address these issues.
Design/methodology/approach – Evolvable production system has a structured methodology in itself. Consistent to this, a reference planningarchitecture is developed aiming to achieve agility on planning activities. Besides a workload control method is proposed and implemented as a part ofthe planning architecture.
Findings – First applications of evolvable systems have been implemented through European research projects. Shop floor working principles andarchitectural characteristics are consistent to facilitate more agility on planning activities which are framed at a planning reference architecture calleddemand responsive planning. As an implementation case, an agent-based workload control method is proposed and implemented. The characteristicsof EPS and proposed planning architecture enable continuous and dynamic workload control of the shop floor to be implemented.
Originality/value – This paper presents a new planning model compatible with evolvable production systems targeting to agility to demand onplanning and control activities benefiting shop floor enhancements of a fully reconfigurable system which enables to relax constraints imposed fromproduction systems to planning. In addition, a continuous and dynamic workload control method is proposed and implemented.
The balance between assembly process optimality and their system’s ability to adapt to new requirements is a key to success for assembly companies. To increase SME’s survivability, an effective methodology is needed to handle the requirements of both agility and mass customization. Evolvable Assembly Systems (EAS) paradigm is a next generation assembly systems focused on these issues. Three key issues are here in focus: process-oriented approach, fine modular granularity, and module intelligence through lighter multi-agent technology at the shop floor level. These issues
Production planning and control strategies have been changing in line with the constant change on product and customer requirements, under the light of technological and scientific advancements. Production systems which are based on mass production became obsolete in time hence companies, being profit oriented, are in need of new solutions towards mass customization to handle rapidly changing market conditions. To deal with this issue, production systems and production planning strategies have to be complementing each other. In this paper Evolvable Production Systems and its compatibility to Just in Time (JIT) Production compared to Material Requirement Planning (MRP) will be discussed.
Europe, as most other OECD areas, is confronted with major potential opportunities in the decades to come. Although often portrayed as threats, the symptoms being denoted in the European economy are, in fact, part of a shift in knowledge and technology infrastructures created by these trends. These current challenges being faced by manufacturing companies nowadays require production systems to become ever more responsive and agile. This is particularly relevant to micro-products, since manual assembly becomes impossible, rendering outsourcing strategies less effective if not deliberately negative. Furthermore, traditional approaches to R&D in this field no longer suffice to cope with the challenges imposed since these imply new business methods, continuous technological evolution, and the increased tendency towards networks of enterprises. To meet such demands there is a need for new rapidly deployable and affordable (economically sustainable) microassembly systems based on reconfigurable, modular concepts that would allow continuous system evolution and seamless reconfiguration. Furthermore, as will be detailed later, one of the requiredfoundations to sustainable assembly system concepts lies within a new way of thinking and working: a methodology that could integrate the various aspects related to the life cycle of the production systems, with particular focus being placed on the re-engineering phase. This article will present some definitions, clarify the basic approach, and outline the serious requirements being posed by such a paradigm: Evolvable Assembly Systems.
Europe, as most other OECD areas, is confronted with major potential opportunities in the decades to come. Although often portrayed as threats, the symptoms being denoted in the European economy are, in fact, part of a shift in knowledge and technology infrastructures created by these trends. These current challenges being faced by manufacturing companies nowadays require production systems to become ever more responsive and agile. This is particularly relevant to micro-products, since manual assembly becomes impossible, rendering outsourcing strategies less effective if not deliberately negative. Furthermore, traditional approaches to R&D in this field no longer suffice to cope with the challenges imposed since these imply new business methods, continuous technological evolution, and the increased tendency towards networks of enterprises.
To meet such demands there is a need for new rapidly deployable and affordable (economically sustainable) microassembly systems based on reconfigurable, modular concepts that would allow continuous system evolution and seamless reconfiguration. Furthermore, as will be detailed later, one of the required foundations to sustainable assembly system concepts lies within a new way of thinking and working: a methodology that could integrate the various aspects related to the life cycle of the production systems, with particular focus being placed on the re-engineering phase. This article will present some definitions, clarify the basic approach, and outline the serious requirements being posed by such a paradigm: Evolvable Assembly Systems.
This paper presents the application of zero velocity detectors in the field of indoor positioning for industrial tightening tools particularly in tandem with an extended Kalman filter to achieve reliable estimates in position. Inertial measurement units are promising devices to use in positioning systems. Data has been collected from IMU while moving in a predefined trajectory on a tightening test rig and post-processed in MATLAB using the implemented algorithms and the results are presented. They indicate that the error accumulation can be effectively controlled to 25 cm/min for the commercial grade IMU and 15 cm/min for the navigation grade IMU.
The goal of this paper is to describe the research on Evolvable Production Systems (EPS) in the context of Reconfigurable Manufacturing Systems (RMS), and to briefly describe a multiagent based control solution. RMS, Holonic and EPS concepts are briefly described and compared. Novel inspiration areas and concepts to solve the demanding requirements set by RMS, such as artificial life and complexity theory, are described. Finally, the multiagent based control solution is described as the underlying infrastructure to support all future development in EPS, using concepts such as emergence and self-organisation.
Evolvable Production Systems (EPS) lies at the leading edge of the new paradigms currently emerging as a response to the continuously changing socio-economic challenges that modern enterprises have to deal with. Maximizing the profit under adverse market conditions is also a matter of cost cut and EPS targets this through an efficient diagnosis mechanism embedded in future production systems. Evolvable production systems goes beyond other manufacturing paradigms, and offers intelligent devices with biologically inspired behaviours, heavily dependent on self-diagnosis, self healing and other autonomous actions to ensure the systems' proper functioning and a timely response and recover from unpredictable situations.
A new paradigm, the Evolvable Assembly Systems (EAS), was recently proposed. This paradigm provides a complete new view on how assembly systems should be designed and developed. Because the control system is one of the key aspects for a successful implementation of EAS this chapter proposes a development roadmap to pinpoint directions of research on how control systems should be developed. It is expected that with this information the industry can envision the potential benefits in terms of competitiveness of this approach. The chapter focuses on the issues that highlight the importance self-organization, dynamical systems, complexity theory, collaborative networks theory, swarm intelligence, and Distributed Artificial Intelligence (DAI) have in the future of EAS. The chapter emphasizes the importance of these mechanisms in solving the increasing challenges imposed upon automatic precision assembly companies that constantly battle to attain agile or evolvable assembly systems.
The work presented in this paper intends to clarify how multiagents can be an adequate paradigm to solve the challenges imposed by Evolvable Assembly Systems (EAS). The article will therefore show that a multiagent architecture based on coalitions of assembly modules (CoBASA) can be successfully used to implement the control architecture for EAS.
This paper details the recent development within evolvable assembly systems, including ontological, methodological, and application developments. This paradigm was recently proposed as an answer to the requirements faced by assembly companies in the current world of business and technological changes. EAS, as with other similar approaches, offers great opportunities for attaining true agility and cost- effective, stepwise automation. EAS does imply that the manner in which we develop and create projects for the development of assembly systems are radically changed, assuming a more synthesis-based approach.
A new paradigm, the Evolvable Assembly Systems (EAS), was recently proposed. This paradigm provides a complete new view on how assembly systems should be designed and developed. Because the control system is one of the key aspects for a successful implementation of EAS this paper proposes a development roadmap to pinpoint directions of research on how control systems should be developed. It is expected that with this information the industry can envision the potential benefits in terms of competitiveness of this approach; still, this paper is especially targeted to motivate researchers from self-organisation and distributed assembly systems to engage in this endeavour together. In particular, topics on self-organisation, emergence, dynamical systems, and distributed artificial intelligence can be the backbone of truly self-adapting assembly systems. In fact EAS seems to be a really demanding and grounded case-study for the referred research communities.
Darwin's evolutionary theory of natural selection has had a strong impact on both science and culture, and has over the last decades become a popular inspiration in engineering sciences. Both the wide range of scientific areas where evolutionary theory is applied, and the simplistic metaphors used to explain evolution in schools and non-scientific situations have caused confusion of how key evolutionary concepts should be understood. In this paper, the cornerstones in biological and social evolutionary theory are identified and addressed from an engineering point of view. Previous efforts to apply evolutionary theories within engineering are then addressed and related to the needs and opportunities within manufacturing and assembly.
Since the introduction of the concept of learning curves in manufacturing, many articles have been applying the model to study learning phenomena. In assembly, several studies present a learning curve when an operator is trained over a new assembly task; however, when comparisons are made between learning curves corresponding to different training methods, unaware researchers can show misleading results. Often, these studies neglect either or both the stochastic nature of the learning curves produced by several operators under experimental conditions, and the high correlation of the experimental samples collected from each operator that constitute one learning curve. Furthermore, recent studies are testing newer technologies, such as assembly animations or augmented reality, to provide assembly aid, but they fail to observe deeper implications on how these digital training methods truly influence the learning curves of the operators. This article proposes a novel statistical study of the influence of expert video aid on the learning curves in terms of assembly time by means of functional analysis of variance (FANOVA). This method is better suited to compare learning curves than common analysis of variance (ANOVA), due to correlated data, or graphical comparisons, due to the stochastic nature of the aggregated learning curves. The results show that two main effects of the expert video aid influence the learning curves: one in the transient and another in the steady state of the learning curve. The transient effect of the expert video aid, where the statistical tests suffer from a high variance in the data, appears to be a reduction in terms of assembly time for the first assemblies: the operators seem to benefit from the expert video aid. As soon as the steady state is reached, a slower and statistically significant effect appears to favor the learning processes of the operators who do not receive any training aid. Since the steady state of the learning curves represents the long term production efficiency of the operators, the latter effect might require more attention from industry and researchers.
Literature shows that reinforcement learning (RL) and the well-known optimization algorithms derived from it have been applied to assembly sequence planning (ASP); however, the way this is done, as an offline process, ends up generating optimization methods that are not exploiting the full potential of RL. Today’s assembly lines need to be adaptive to changes, resilient to errors and attentive to the operators’ skills and needs. If all of these aspects need to evolve towards a new paradigm, called Industry 4.0, the way RL is applied to ASP needs to change as well: the RL phase has to be part of the assembly execution phase and be optimized with time and several repetitions of the process. This article presents an agile exploratory experiment in ASP to prove the effectiveness of RL techniques to execute ASP as an adaptive, online and experience-driven optimization process, directly at assembly time. The human-assembly interaction is modelled through the input-outputs of an assembly guidance system built as an assembly digital twin. Experimental assemblies are executed without pre-established assembly sequence plans and adapted to the operators’ needs. The experiments show that precedence and transition matrices for an assembly can be generated from the statistical knowledge of several different assembly executions. When the frequency of a given subassembly reinforces its importance, statistical results obtained from the experiments prove that online RL applications are not only possible but also effective for learning, teaching, executing and improving assembly tasks at the same time. This article paves the way towards the application of online RL algorithms to ASP.
This article argues that despite a citation review is a rarely used research tool, this can be very useful to assess the impact of new research topics, both from the future research direction and the bibliometric perspectives. An explorative study is presented around the research area marked as Industry 4.0 with the conference paper mentioned in the title of this citation review. Even though the given reference paper is relatively recent, there are already twenty-seven citations listed among three different scholar databases. These are Google Scholar, ResearchGate and Semantic Scholar. In light of this, the article provides a bibliometric confirmation and analysis for the progression of the line of research adopted by de Giorgio et al. in the exploration of non-traditional methods using virtual reality technology and human-robot collaboration for adaptive applications in Industry 4.0. Furthermore, it represents a model for the authors’ self-development and an example of an unconventional approach to scientific work that may help improve related bibliometric research and scholar database strategies to index new articles and topics in the future.
Can automatically-authored videos of industrial operators help other operators to learn procedural tasks? This question is relevant to the advent of the industrial internet of things (IIoT) and Industry 4.0, where smart machines to help human operators rather than replacing them, in order to benefit from the best of humans and machines. The study considers an industrial ecosystem where procedural knowledge (PK) is quickly and effectively transferred from one operator to another. Assembly tasks are procedural in nature and present a certain complexity that still does not allow machines and their sensors to capture all the details of the operations. Especially if the assembly operation is adaptive and not fixed in terms of assembly sequence plan. In order to help the operators, videos of other operators executing the complex procedural tasks can be automatically recorded and authored from machines. This study shows by means of statistical design and analysis of experiments that expert aid, provided before each subassembly, can reduce the assembly time of an untrained operator, whereas automatically authored video aids can transfer PK but producing an opposite effect on the assembly time. Therefore, hybrid training methods are still necessary and trade-offs have to be considered. Managerial insights from the results suggest an unneglectable impact of the choice to digitize industrial operations too early. The experimental studies presented can act as guidelines for the correct statistical testing of innovative solutions in industry.
This paper outlines the main steps towards an open and adaptive simulation method for human-robot collaboration (HRC) in production engineering supported by virtual reality (VR). The work is based on the latest software developments in the gaming industry, in addition to the already commercially available hardware that is robust and reliable. This allows to overcome VR limitations of the industrial software provided by manufacturing machine producers and it is based on an open-source community programming approach and also leads to significant advantages such as interfacing with the latest developed hardware for realistic user experience in immersive VR, as well as the possibility to share adaptive algorithms. A practical implementation in Unity is provided as a functional prototype for feasibility tests. However, at the time of this paper, no controlled human-subject studies on the implementation have been noted, in fact, this is solely provided to show preliminary proof of concept. Future work will formally address the questions that are raised in this first run.
The increasing market fluctuations and customized products demand have dramatically changed the focus of industry towards organizational sustainability and supply chain agility. Such critical changes inevitably have a direct impact on the shop-floor operational requirements. In this sense, a number of innovative production paradigms emerged, providing the necessary theoretical background to such systems. Due to similarities between innovative modular production floors and natural complex systems, modern paradigms theoretically rely on bio-inspired concepts to attain the characteristics of biological systems. Nevertheless, during the implementation phase, bio-inspired principles tend to be left behind in favor of more traditional approaches, resulting in simple distributed systems with considerable limitations regarding scalability, reconfigurable ability and distributed problem resolution.
This paper analyzes and presents a brief critical review on how bio-inspired concepts are currently being explored in the manufacturing environment, in an attempt to formulate a number of challenges and properties that need to be considered in order to implement manufacturing systems that closely follow the biological principles and consequently present overall characteristics of complex natural systems.
Biological collective systems have been an important source of inspiration for the design of production systems, due to their intrinsic characteristics. In this sense, several high level engineering design principles have been distilled and proposed on a wide number of reference system architectures for production systems. However, the application of bio-inspired concepts is often lost due to design and implementation choices or are simply used as heuristic approaches that solve specific hard optimization problems. This paper proposes a bio-inspired reference architecture for production systems, focused on highly dynamic environments, denominated BIO-inspired Self-Organising Architecture for Manufacturing (BIOSOARM). BIOSOARM aims to strictly adhere to bio-inspired principles. For this purpose, both shopfloor components and product parts are individualized and extended into the virtual environment as fully decoupled autonomous entities, where they interact and cooperate towards the emergence of a self-organising behaviour that leads to the emergence of the necessary production flows. BIOSOARM therefore introduces a fundamentally novel approach to production that decouples the system’s operation from eventual changes, uncertainty or even critical failures, while simultaneously ensures the performance levels and simplifies the deployment and reconfiguration procedures. BIOSOARM was tested into both flow-line and “job shop”-like scenarios to prove its applicability, robustness and performance, both under normal and highly dynamic conditions.
Sustainability is currently one of the biggest challenges and drivers of manufacturing industry. With traditional automation approaches becoming evermore inadequate to support sustainable mass customized production, the research focus is moving towards agile systems that enact companies with the ability to quickly reconfigure their shop-floors by seamlessly deploying or removing modules. Such systems are envisioned as key for attaining a profitable and sustainable industrial development. In this sense, this paper attempts to characterize an innovative approach that relies on bio-inspired concepts as the main control mechanism, in order to foster sustainability by attaining the necessary shop-floor agility. Furthermore an experimental setup is presented and the results are analysed, in order to understand the influence and impact of the main properties of the approach towards the system performance.
The emergence of modern manufacturing paradigms together with the growing interest on distributed architectures has been increasing the use of biologically inspired solutions. However, somehow along the way, developed approaches have converged towards more traditional systems where the physical and logical decoupled nature of the system has been partially lost. In this context, the presented work aims to introduce and analyse a new fully physically and logically decoupled bio-inspired self-organising approach that tries to bring to the mechatronic-agent based manufacturing architectures the dynamics of biological systems. Furthermore, the manufacturing systems are approached from a bottom-up perspective in an attempt to reduce the specification of the production processes to the minimum.
With the emergence of new modern manufacturing paradigms new concepts, originally from the complexity sciences started to be introduced in the manufacturing systems, rendering traditional control approaches insufficient. Therefore, new approaches were developed, supported by the modern manufacturing paradigms bio-inspired background. However, somehow along the way the physical and logical nature of the system was partially lost, leading to the convergence of approaches towards more traditional systems, 'neglecting' their bio-inspired principles. With the present work the authors aim to introduce and analyse two new different self-organising approaches that try to bring the focus of manufacturing systems, again to the bio-inspired principles. For this purpose, in the context of this work, manufacturing systems are approached from a bottom-up perspective, in an attempt to reduce the specification of the production processes to the minimum and foster the production emergence. A test case is considered, to draw initial conclusions.
There has been an increasing interest from industry in distributed architectures since they promote a plug-and-produce and robust environment, where adaptability and fault tolerance are native. Much research has been conducted in this field mainly supported by multi-agent and service oriented technologies. Nevertheless the retrieval and visualization of information in distributed systems is a relatively unexplored area. Although the dynamic nature of the multi-agent systems allows gathering information in a prompt manner, doing so might affect the performance of the mechatronic agents. In this sense, the present paper details the architecture of a visualization tool that introduces a reliable but non-invasive approach to retrieve data from distributed platforms as well as a new way to visualize and interpret the information gathered from mechatronic based systems.
Agility, reactivity and sustainability are key to cope with today's dynamic markets, as has been broadly recognized. Depending on the source, manufacturing systems are required to be modular, hierarchical or heterarchical, distributed, flexible or reconfigurable; companies can be represented using the Bionic, Fractal and Holonic concepts. Evolvable Production Systems fulfill the majority of the requirements elaborated by the Agile and Reconfigurable approaches and take nature as a metaphor. Modularity of fine granularity and local intelligence allow truly process-specific system design. EPS provide mechanisms for fast reconfiguration at mechanical as well as control level. They apply the Multi-Agent paradigm, which is intrinsically suited for Distributed systems. Inspired by Biology, Artificial Intelligence and Complexity Theory, EPS open the doors for the production systems of the future: the aim is to implement advanced concepts such as Self-Organization, Self-Diagnose and Self-Healing. Coping with emergent behavior will be fundamental, and taking profit of emergent capabilities will open considerable potential for new solutions.
The Assembly Systems Unit at the Royal Institute of Technology and IVF Stockholm has developed several Flexible Automatic Assembly (FAA) cell solutions over the years (Mark I. Mark II, Mark IIF and Mark III). The industrial reality, however, clearly points out that the basic notions of flexibility must be extended and be enhanced without increasing the complexity. This has led our research team to revise the ideas and solutions available for manual and automatic assembly, resulting in the Hyper Flexible Automatic Assembly (HFAA) project. The paper describes the driving factors behind the needs and objectives for the HFAA project, as well as how it will present a standardised set of assembly process-oriented system components. The paper also describes the new Mark IV application. This industrial HFAA system is being developed in order to test the concept's industrial viability. The HFAA concept will allow the user to start from a manual assembly station and gradually add assembly equipment. The basic concepts of stepwise automation, standard assembly machine and sub-batch principle emanate from our previous research.
The purpose of this paper is to introduce a proposed methodology to extend the evolvable assembly system (EAS) paradigm for product design by utilizing assembly features in a product. In this paper, assembly features are used to bridge the gap between product design and assembly process by matching features of a part in an assembly to operations of a process in the EAS ontology. This can be achieved by defining and extracting a new set of assembly features called process features, which are features significant to specific and well-defined assembly operations. The extracted assembly features are represented in a proposed model based on product topology. A case-study example is conducted to illustrate the new methodology. A process-feature ontology is proposed as well in order to match the assembly requirements represented by process features with the available processes and skills in the EAS ontology so that adaptation of the production system can be achieved.
This paper describes a novel approach to recognize and model assembly semantic knowledge enclosed in product assembly features. The proposed approach is based on two stages: assembly semantic recognition and assembly semantic modelling. In the first stage, the internal boundary representation (B-rep) recognition method is utilized to extract assembly semantic knowledge from assembly CAD models using SolidWorks' API functions. In the second stage, a multi-level semantic assembly model is generated. The proposed assembly semantic model is characterized by separating geometrical semantic data represented by form features (basic geometrical and topological entities such as holes, slots, notches etc.) from assembly features (features significant for assembly processes such as mating, alignment, handling, joining etc.). Another characteristic for of the proposed approach is the ability to generate application-specific features based on the extracted geometrical, dimensional and positional semantic data from the assembly design. The generated application specific features will be used to integrate assembly design knowledge to the required assembly processes and resources in the assembly process planning (APP) in product life-cycle. A case-study example is included for illustration of the proposed approach. The work is part of the research within the Evolvable Production Systems paradigm and aims at linking product features to production equipment modules.
The aim of this paper is to facilitate the transfer of product data semantics from Computer Aided Design (CAD) program to assembly process planning (APP) in product life-cycle. In this paper, an approach to capture, share and transfer assembly design semantic data from SolidWorks (SW) CAD software to assembly device (robot Sony SRX series) is proposed. The proposed approach is based, on its first stage, on defining and extracting assembly design semantics from a CAD model using SolidWorks Application Programmable Interface (SW-API). The second stage of the proposed approach includes sharing and integrating the extracted assembly design semantics with assembly robot device by using three-layer ontology structure. In this layered ontology, different types of ontologies are proposed for each layer: general foundation ontology for the first, domain ontologies for the second and application ontology for the third. Each of these layers aids in defining concepts, relations and properties in assembly design domain and APP domain. Ultimately, the proposed ontology will be used to integrate both domains in product-life cycle.
The desire to conquer markets through advanced product design and trendy business strategies are still predominant approaches in industry today. In fact, product development has acquired an ever more central role in the strategic planning of companies, and it has extended its influence to R&D funding levels as well. It is not surprising that many national R&D project frameworks within the EU today are dominated by product development topics, leaving production engineering, robotics, and systems on the sidelines. The reasons may be many but, unfortunately, the link between product development and the production processes they cater for are seldom treated in depth. The issue dealt with in this article relates to how product development is applied in order to attain the required production quality levels a company may desire, as well as how one may counter assembly defects and deviations through quantifiable design approaches.It is recognized that product verifications (tests, inspections, etc.) are necessary, but the application of these tactics often result in lead-time extensions and increased costs. Modular architectures improve this by simplifying the verification of the assembled product at module level. Furthermore, since Design for Assembly (DFA) has shown the possibility to identify defective assemblies, it may be possible to detect potential assembly defects already in the product and module design phase. The intention of this paper is to discuss and describe the link between verifications of modular architectures, defects and design for assembly. The paper is based on literature and case studies; tables and diagrams are included with the intention of increasing understanding of the relation between poor designs, defects and product verifications.
The current main challenge for the future production system lies in the correct integration of the issues related to sustainability and to agility. The "Evolvable Paradigm" addresses this concern with a new way of engineering the whole production system. The concept of Skill is declined as common denominator between the definitions of manufacturing process and manufacturing equipment. Each production module holds some of the skills that compose the process definition and it is endowed with the necessary intelligence to come together with the other modules in an organized society. This work introduces the approach adopted in the IDEAS project (Instantly Deployable Evolvable Assembly System) to cope with the above mentioned requirement through the presented paradigm. While fully featured and described IDEAS mechatronic architecture allows rapid reconfiguration of the system, the issue of sustainability is targeted by the open definition of the concepts of skill and skills interaction. The result of skill aggregation is hereby called Emergent Behavior and in the proposed model it can be seen as the main driver for the sustainable use of the system.
Current production paradigms and related biases concerning automation are an obstacle for the technological development and subsequent application of intelligent assembly solutions such as the automation based on the evolvable paradigm. A deeper understanding of the potential behind such technology is a fundamental step towards a proficient industrial embodiment. The concept of Value Proposition can be used as a holistic analytical tool able to support a full characterization of the appeal that such technology has on the assembly automation market. The two dimensional bottom-up approach proposed in this work allows the identification and description of six potential value offerings connected with an Evolvable Assembly system, which in turn pave the way to more efficient business models.
Virtual Reality, or VR, is a family of technologies defined in the 60s that aims at mimicking reality through computers with different purposes. VR is usually classified according to the level of user immersion achieved. VR has attracted increasing attention between academic and practitioners during the last decade due to technological progresses that achieved high reliability and relatively low cost. VR potential to visualize information, replace physical presence and stimulate interaction make of this technology an essential part in the toolbox of future engineers. Higher Education Institution must align their curricula to fulfill this purpose. At the same time VR can be a support to enhance the learning process itself. This work analyses the impact of fully-immersive VR technology on an average production engineering curricula based on the educational offer at KTH Royal Institute of Technology in Stockholm, Sweden. The results show that VR has a great potential to shape the production engineering curricula in the coming years both in term of content and design of the learning experiences.
In the field of production engineering the past paradigms have focused on the concept of system flexibility; introducing both automation and computer science at shop floor level. Nevertheless their limits in approaching some fundamental areas, such as modularization and control issues, make them unsuitable for tackling the challenges in the manufacturing scenario of today. In this paper the past approaches with their underlining weaknesses have been reviewed, which leads up to the proposal of a methodology for the creation of a manufacturing system that is based on the Evolvable Paradigm. The salient points of this scheme are: the process oriented approach to modularization, the link between the development of the system and the design of the product. Fundamental requirements in pursuing these issues are to deeply study the processes in order to represent them at the hardware level, and to develop a distributed control system to handle emergent behaviour. The potential economical benefits that come from the Evolvable Paradigm include that automation can be a sustainable approach both large enterprises and for SMEs.
Current major roadmapping efforts have all clearly underlined that true industrial sustainability will require far higher levels of systems' autonomy and adaptability. In accordance with these recommendations, the Evolvable Production Systems (EPS) has aimed at developing such technological solutions and support mechanisms. Since its inception in 2002 as a next generation of production systems, the concept is being further developed and tested to emerge as a production system paradigm. Characteristically, Evolvable systems have distributed control, and are composed of intelligent modules with embedded control. A concerted effort is being exerted through European research projects in collaboration with manufacturers, technology/equipment suppliers, and universities. After introducing EPS, this paper presents current developments and applications.
This paper introduces the assembly feature data schema instance modeling to pre-examine the schema functionality and output- as the preliminary step for data modeling. In order to link assembly with product design, it is essential to determine which entities of product design are involved at the automated assembly planning and operations. It is possible to assign meaningful attributes (assembly features) to the part model entities in a systematic and structured way. Using object-oriented design, the assembly feature data structure and its relationships are modeled. As a part of the research on product and assembly system data integration within the evolvable production system platform, the instance models for proposed assembly feature data structure provide a deeper understanding and error reduction that might possibly occur at the development of the database. Moreover through instance modeling, the assembly feature data query output format from the database prototype is simulated. An industrial assembly model example with its 3DPart models is chosen to demonstrate the realized assembly feature data set with string data type. The models support the desired simplicity at the database prototype implementation. The output format envisions the interoperability factor between product models and the assembly planning systems.
Purpose - This paper introduces a schema for the product assembly feature data in an object-oriented and module-based format using Unified Modeling Language (UML). To link production with product design, it is essential to determine at an early stage which entities of product design and development are involved and used at the automated assembly planning and operations. To this end, it is absolutely reasonable to assign meaningful attributes to the parts' design entities (assembly features) in a systematic and structured way. As such, this approach empowers processes such as motion planning and sequence planning in assembly design. Design/methodology/approach - The assembly feature data requirements are studied and definitions are analyzed and redefined. Using object-oriented techniques, the assembly feature data structure and relationships are modeled based on the identified requirements as five UML packages (Part, three-dimensional (3D) models, Mating, Joint and Handling). All geometric and non-geometric design data entities endorsed with assembly design perspective are extracted or assigned from 3D models and realized through the featured entity interface class. The featured entities are then associated (used) with the mating, handling and joints features. The AssemblyFeature interface is realized through mating, handling and joint packages related to the assembly and part classes. Each package contains all relevant classes which further classify the important attributes of the main class. Findings - This paper sets out to provide an explanatory approach using object-oriented techniques to model the schema of assembly features association and artifacts at the product design level, all of which are essential in several subsequent and parallel steps of the assembly planning process, as well as assembly feature entity assignments in design improvement cycle. Practical implications - The practical implication based on the identified advantages can be classified in three main features: module-based design, comprehensive classification, integration. These features help the automation and solution development processes based on the proposed models much easier and systematic. Originality/value - The proposed schema's comprehensiveness and reliability are verified through comparisons with other works and the advantages are discussed in detail.
Purpose: This paper addresses a comprehensive modeling and functionality evaluation of amodule-based quality system in production logistics at the highest domain abstract level ofbusiness processes.
Design/methodology/approach: All domain quality business processes and quality datatransactions are modeled using BPMN and UML tools and standards at the business process anddata modeling. A modular web-based prototype is developed to evaluate the models addressingthe quality information system functionality requirements and modularity in production logisticsthrough data scenarios and data queries.
Findings: Using the object-oriented technique in design at the highest domain level, theproposed models are subject further development in the lower levels for the implementing case.The models are specifically able to manipulate all quality operations including remedy and controlin a lot-based make-to-order production logistics system as an individual module.
Practical implications: Due to the specification of system as domain design structure, allproposed BPMs, data models, and the actual database prototype are seen referential if not asolution as a practical “to-be” quality business process re-engineering template.
Originality/value: this paper sets out to provide an explanatory approach using differentpractical technique at modeling steps as well as the prototype implementation.