The paper presents an Artificial Intelligence-driven approach to predictive maintenance for Product-Service System (PSS) development. This study focuses on time-based and condition-based maintenance, leveraging variational autoencoders to identify both predicted and unpredicted maintenance issues in autonomous haulers. By analyzing data patterns and forecasting future values, this approach enables proactive maintenance and informed decision-making in the early stages of PSS development.
The inclusion of interaction terms enhances the model’s ability to capture the interdependencies among system components, addressing hidden failure modes. Comprehensive evaluations demonstrate the effectiveness and robustness of the developed models, showcasing resilience to noise and variations in operational data.
The integration of predictive maintenance with PSS development offers a strategic advantage, providing insights into vehicle performance early in the development phases. This empowers decision-makers for efficient resource allocation and proactive maintenance planning. The research highlights the limitations and potential areas of improvement while also emphasizing the practical applicability and significance of the developed models in enhancing PSS development.
This paper presents an approach that utilizes artificial intelligence techniques to identify autonomous machine behavior patterns. The context for investigation involves a fleet of prototype autonomous haulers as part of a Product Service System solution under development in the construction and mining industry. The approach involves using deep learning-based object detection and computer vision to understand how prototype machines operate in different situations. The trained model accurately predicts and tracks the loaded and unloaded machines and helps to identify the data patterns such as course deviations, machine failures, unexpected slowdowns, battery life, machine activity, number of cycles per charge, and speed. PSS solutions hinge on efficiently allocating resources to meet the required site-level output. Solution providers can make more informed decisions at the earlier stages of development by using the AI techniques outlined in the paper, considering asset management and reallocation of resources to account for unplanned stoppages or unexpected slowdowns. Understanding machine behavioral aspects in early-stage PSS development could enable more efficient and customized PSS solutions.
A data analysis method based on artificial neural networks aiming to support cause-and-effect analysis in design exploration studies is presented. The method clusters and aggregates the effects of multiple design variables based on the structural hierarchy of the evaluated system. The proposed method is exemplified in a case study showing that the predictive capability of the created, clustered, a dataset is comparable to the original, unmodified, one. The proposed method is evaluated using coefficient-of-determination, root mean square error, average relative error, and mean square error. Data analysis approach with artificial neural networks is believed to significantly improve the comprehensibility of the evaluated cause-and-effect relationships studying PSS concepts in a cross-functional team and thereby assisting the difficult and resource-demanding negotiations process at the conceptual stage of the design.
Background: Traditionally, assessing the degree of ossification in the epiphyseal plate for growth plate development relies on manual evaluation, which can be inefficient due to the complexities of the distal femoral epiphysis anatomy. Existing methods lack efficient detection techniques.
Method: This study proposes an AI-based decision support system, designed within a product-service system (PSS) framework, to automate ossification assessment and detection of the distal femoral epiphysis in knee magnetic resonance imaging (MRI) data. The system leverages advanced machine learning techniques, specifically two Convolutional Neural Networks (CNNs), combined with computer vision techniques. This intelligent system analyzes MRI slices to predict the optimal slice for analysis and identify variations in the degree of ossification within individual datasets.
Results: The proposed method's effectiveness is demonstrated using a set of T2-weighted gradient echo grayscale knee MRI data. The system successfully detects the complex anatomy of the distal femoral epiphysis, revealing variations in the degree of ossification ranging from completely closed/open to fully open/closed regions.
Conclusions: This study presents a robust and efficient AI-based method, integrated within a PSS framework, for measuring the degree of ossification in the distal femoral epiphysis. This approach automates ossification assessment, providing valuable insights for clinical decision-making by clinicians and forensic practitioners. The PSS framework ensures seamless integration of the AI technology into existing workflows.
The paper presents a Model-Driven approach for Product-Service System (PSS) Design promoting an increased digitalization of the PSS design process based on the combination of data-driven design (DDD) activities and value-driven design (VDD) methods. The approach is the results of an 8-year long research profile named (omitted for blind review) featuring the collaboration between (omitted for blind review) and nine industrial companies, in the field of PSS Design. It combines VDD models and the supporting data-driven activities in the frame of PSS design and aligns with the product value stream and the knowledge value stream in the product innovation process as described by Kennedy et al. (2008). The paper provides a high-level overview of the approach describing the different stages and activities, and provides references to external scientific contributions for more exhaustive descriptions of the research rationale and validity. The approach is meant to ultimately drive the development and implementation of a simulation environment for cross-functional and multi-disciplinary decision making in PSS, named Model-Driven Decision Arena, describe in the concluding part of the paper.
The development of early-stage simulation capabilities is a critical step in the quest for ‘frontloading’ early stage PSS design activities, reducing the cost and risk for rework associated with sub-optimal decisions. This paper describes how life cycle simulations, based on a Discrete Event approach, can be applied to support cross-disciplinary decision making in PSS design, facilitating the identification of the most valuable hardware configuration for a given business model. The proposed approach is exemplified in a case study related to the design of a zero-emission asphalt compactor, which is part of a product-oriented and use-oriented PSS offer. Co-located physical meetings and interviews with industrial practitioners highlight the role played by the simulation as an enabler for leveraging tacit knowledge sharing across roles and disciplines in the organization, making possible to explore the design space with more rigor. They further reveal the need to exploit data mining techniques and to develop new constructs able to inform decision makers of maturity and impact of models used in a specific decision scenario.
The concept of Decision Theatre (DT) is of great interest to leverage knowledge sharing in early stage design decision events. Yet, few contributions show how to configure a DT to support design space exploration and concept selection in cross-functional teams. This paper describes the development of a model-driven decision arena (MDDA) for aero-engine sub-system design. After presenting the descriptive study findings, it illustrates the overall logic of the MDDA environment and exemplifies its use in a case study related to the design of a turbine real structure (TRS) for commercial use.
Rammer compactor machines perform dynamic soil compaction. The complexity of this machine type makes design optimisation through traditional prototype testing impractical. This has pointed to the need for a theoretical model and simulation procedure for prediction of the dynamic behaviour of the machine and a procedure for optimisation as design parameters are changed during product development. In this paper a theoretical model of the rammer machine in combination with a soil model is described. This multi-body dynamics system is solved numerically. The system is non-linear and chaotic behaviour is possible. This parameter sensitivity emphasises the need for this kind of simulations in the product development process. A fairly regular behaviour is necessary for a predictable and safe operation. Parameter combinations giving too irregular behaviour are non-feasible. The energy transfer rate from the rammer machine into the soil is used as the objective function for optimisation. Multi-start Sequential Quadratic Programming for optimum search is used. To cover the design space well a Uniform Experimental Design is used for selection of starting points. This procedure proves to work well for the problem of this introductory study. The study shows a significant potential for improved compaction capacity although considering only the three design parameters that are most easily changed in practice. Approximately the same optimum is obtained both for operation on soft soil and hard soil, so a good all-round design seems possible. Including this theoretical support in the product development process should make it much more effective in finding optimum designs, also for other machines of similar type.
In response to the increasingly competitive global market, there is a growing interest in design optimization. Being able to include aspects of socio-ecological sustainability in product design should aid companies to both improve current competitiveness and to identify viable long-term investment paths and new business opportunities in the evolving sustainability-driven market. A case study of a water jet cutting machine is used to illustrate a new iterative optimization procedure that combines a technical assessment with a sustainability assessment. Sustainability assessment methods/tools are first used to identify prominent sustainability problems from present-day flows and practices (“societal indicators”) and to generate ideas of long-term solutions and visions. Based on this, preliminary ideas about likely desirable changes in machine properties are obtained. Technical investigations are then performed to assess if/how these particularly desirable changes in machine properties could in principle be realized through changes in design variables. After that, obtainable changes are fed back to a new and more refined sustainability assessment to find out the societal implications of these changes. This may in turn result in other desirable design changes, which may call for a new and more refined technical assessment, etcetera. The experience from the case study indicates that the suggested integrated and iterative working procedure should be able to add information about socio-ecological impacts of product properties and influence design criteria used in prioritisation situations during product development.
Ubiquitous and pervasive computing holds great potential in the domain of Product-Service Systems to introduce a model-driven paradigm for decision support. Data-driven design is often discussed as a critical enabler for developing simulation models that comprehensively explore the PSS design space for complex systems, linking of performances to customer and provider value. Emerging from the findings of two empirical studies conducted in collaboration with multinational manufacturing companies in the business-to-business market, this paper defines a data-driven framework to support engineering teams in exploring, early in the design process, the available design space for Product-Service Systems from a value perspective. Verification activities show that the framework and modeling approach is considered to fill a gap when it comes to stimulating value discussions across functions and organizational roles, as well as to grow a clearer picture of how different disciplines contribute to the creation of value for new solutions.
To facilitate overall lay-out optimisation simplified component models for dynamics simulations of automobile exhaust systems are desired. Such optimisation could otherwise be computationally expensive, especially when non-linear analyses are necessary. Suggestions of simplified models of the mufflers and the catalyst are given. To account for the flexibility at the connections between those components and the pipes short beam elements with individual properties are introduced at these locations. An automated updating procedure is developed to determine the properties of these beam elements. Results from an experimental modal analysis are used as the reference. The theoretical model of the exhaust system is built in the finite element software ABAQUS. The updating procedure uses the sequential quadratic programming algorithm included in the Optimization Toolbox of the software MATLAB to minimise the sum of the differences between experimentally and theoretically obtained natural frequencies. Constraints are used on the correlation between the experimentally and theoretically obtained mode shapes by considering the MAC-matrix. Communication between the two software packages is established by an in-house MATLAB script. The correlation between results from the updated theoretical model and the experimental results is very good, which indicates that the updating procedure works well.
A bellows combined with an inside liner and an outside braid is commonly used as a flexible joint in automobile exhaust systems to reduce transmission of engine movements to the exhaust system. It greatly influences the dynamics of the complete system. Understanding of its dynamic characteristics and a modelling method that facilitates systems simulation are therefore desired. This has been obtained in earlier works for the bellows itself. In this work an approach to the modelling of the combined bellows and liner joint is suggested and experimentally verified. Simulations and measurements show that the liner adds significant non-linearity and makes the characteristics of the joint complex. Results are presented for the axial and the bending load cases. In torsion, influence of the liner is negligible. Peak responses are significantly reduced when the excitation level approximately corresponds to the friction limit of the liner. The complexity of the combined bellows and liner joint is important to know of and consider in exhaust system design and proves the necessity of including a model of the liner in the theoretical joint model when this type of liner is present in the real joint to be simulated.
To facilitate overall lay-out optimisation inexpensive dynamics simulation of automobile exhaust systems is desired. Identification of possible non-linearity as well as finding simplified component models is then important. A flexible joint is used between the manifold and the catalyst to allow for the motion of the engine and to reduce the transmission of vibrations to the rest of the exhaust system. This joint is significantly non-linear due to internal friction, which makes some kind of non-linear analysis necessary for the complete exhaust system. To investigate the significance of non-linearity and internal vibrations of other components a theoretical and experimental modal analysis of the part of a typical exhaust system that is downstream the flexible joint is performed. It is shown that non-linearity in this part is negligible. It is also shown that shell vibrations of the catalyst and mufflers as well as ovalling of the pipes are negligible in the frequency interval of interest. The results implies, for further dynamics studies, that the complete system could be idealised into a linear sub-system that is excited via the non-linear flexible joint, that the pipes could be modelled with beam elements and that the other components within the linear sub-system could also be modelled in a simplified way. Such simplified component models are suggested. The agreement between theoretical and experimental results is very good, which indicates the validity of the simplified modelling.
Global society is encountering many challenges such as climate change, resource depletion, etc., which comes with a set of challenges and opportunities for businesses. Applied research in operational tools and methods that support sustainable product- and service systems innovation, aims to strengthen businesses to overcome these challenges. In recent years, several tools and methods have been developed in the sustainable product development field with focus on modelling and digitalization. This paper explores how sustainability has been integrated in modelling and simulation, and presents results from a literature review with the purpose of highlighting opportunities and challenges in the field. Furthermore, an initial model-based engineering support toolbox (MBE) is presented, with focus on support tools for socio-ecological sustainability integration in the early product development stages.
Societies across the globe are facing many unprecedented challenges; climate change, pandemics, and resource depletion, just to name a few. These societal challenges, the 2030 Sustainable Development Agenda, and companies’ demands about knowledge and skills required from future employees have put pressure on academia to develop suitable education programmes in many disciplines, including product development and mechanical engineering. In this position paper, we present our work undertaken in phase-1 of the development of a new MSc programme in the field of product development and mechanical engineering at Blekinge Institute of Technology, aimed at addressing changing societal needs and demands of the future industry. We employ a generic design thinking approach, starting from key stakeholder needs with iterative execution of needfinding, benchmarking, and ideation. In these steps, we use several data collection and generation methods such as interviews, surveys, and workshops. The main outcome of phase-1 is the overall programme structure, consisting of three main focus streams — the engineering design core, three academic specializations (Product-Service Systems Design, Data-Driven Design, and Simulation- Driven Design), and the practical application profiling. Based on our experience of developing the overall programme structure, we offer recommendations for developing new programmes in this area.
To reduce uncertainty in decisions, engineers experiment with models, such as, exploring what-if scenarios, and thus increase knowledge. Still, because modelling is an idealisation of reality, there is often substantial uncertainty involved, and this decision makers less confident to lean onto models alone when making decisions. The aim of this paper is to conceptualize a design support for improving confidence and validity in models, by communicating uncertainties from modelling and simulation to relevant stakeholders. The paper reports on empirical data from a research profile workshop. The findings illustrate the importance of communicating uncertainties from models between relevant stakeholders in order to drive action. The paper then presents an approach to visualize model maturity levels as well as impact levels in relation to one or several aggregated models. With this approach, focus can move to discuss the knowledge about the knowledge that is created from modelling, and to facilitate discussions on a meta-level about the modelling and simulation. This is exemplified by a test scenario where a multi-disciplinary modelling and simulation of an asphalt roller is presented.
When designing CNC machine tools it is important to consider the dynamics of the control, the electrical components and the mechanical structure of the machine simultaneously. This paper describes the structure and implementation of a concept for real-time simulation of such machine tools using a water jet cutting machine as an application. The concept includes a real control system, simulation models of the dynamics of the machine and a virtual reality model for visualisation. The real-time capability of the concept, including the simulation of electrical and rather detailed mechanical component models is proofed. The validation process indicates good agreement between simulation and measurement, but suggests further studies on servo motor, connection and flexibility modelling. However, already from the initial simulation results presented in this paper it can be concluded that the influence of structural flexibility on manufacturing accuracy is of importance at desired feeding rates and accelerations. The fully automated implementation developed in this work is a promising base for dealing with this trade-off between productivity and accuracy of the manufacturing process through multidisciplinary optimisation.
The design of Product-Service Systems (PSS) is challenging due to the inherent complexities and the associated uncertainties. This challenge aggravates when the PSS being considered has a longer lifespan, is expected to encounter a dynamic context, and integrates many novel technologies. From systems engineering literature, one of the measures for mitigating the risks associated with the uncertainties is incorporating means in the system to change internally as a response to change externally. Such systems are referred to as value-robust systems, and their development largely relies on Tradespace exploration and synthesis. Tradespace exploration and synthesis can be challenging and a time-consuming task due to dimensionality. In this light, this paper aims to present an approach that enables the population of the Tradespace and then, supports the synthesis of such a Tradespace using a clustering algorithm for support changeability quantification in PSS. The proposed method is also implemented on a demonstrative case from the construction machinery industry.
The ongoing servitization journey of the manufacturing industries instills a through-life perspective of value, where a combination of products and services is delivered to meet expectations. Often described as a product-service system (PSS), these systems are poised with many complexity aspects, introducing uncertainties during the design phase. Incorporating changeability is one of the known strategies to deal with such uncertainties, where the system changes in the face of uncertainty to sustain value, thereby achieving value robustness. While the theme of dealing with multiple uncertainties has been discussed since the inception of PSS, changeability is still poorly addressed. To bridge this gap, an integrative literature review is performed to outline various complexities aspects and their link to uncertainty from a PSS perspective. Also, the state-of-the-art approach to achieving value robustness is presented via changeability incorporation. Subsequently, a reference framework is proposed to guide decision-makers in changeability incorporation in PSS, especially during the early design stages.
Due to ever increasing challenges faced by our global society, circular design and the idea of product-service systems (PSS) isgaining traction within businesses. However, ‘predicting’ the value of a future PSS solution in the early design phases is difficult,since it requires the ability to balance long term potential with short term decisions. Modelling and simulation is believed to beable to support this challenging task. A simulation framework for circular design of PSS is presented. The simulation processenables the comparison between functional and non-functional performances and their life cycle contributions depending on adefined PSS-like business model strategy. Such integrated simulation framework is intended to exploit engineering modelsoutside their specific discipline, enabling cross-functional collaboration and help decision makers understand how a design cancontribute in satisfying customer and stakeholders needs during the lifecycle of a PSS.
The topic of ‘design for value’ has lately attracted a great deal of attention within the engineering design community. ‘Predicting’ the value of a future solution is however difficult, especially in early design phases. Modelling and simulation is believed to be able to support this challenging task.
A simulation process for value-driven engineering design is presented. The performances of a design concept along the lifecycle are aggregated to a monetary system value function. The results of this multi-model simulation environment for value are displayed through a colour-coded CAD model for easier interaction.
Verification activities indicate that enabling effective design space exploration and visualization of cause-effect relationships become important elements in order to ‘think together’ using a simulation driven design approach. Furthermore, the proposed multidisciplinary ‘value model’ fosters cross-functional knowledge sharing and collective deliberation about the value, forcing stakeholders to synthetize their perceptions about the value of a design and to discuss where conclusions differ.
Sheet metal forming (SMF) simulations are used extensively throughout the development phase of industrialstamping dies. In these SMF simulations, the die and press are normally considered as rigid. Previous research has howevershown that elastic deformation in these parts has a significant negative impact on process performance. This paperdemonstrates methods for counteracting these negative effects, with a high potential for improved production support anda reduced lead time through a shorter try-out process. A structural finite element model (FE-model) of a simplified die isstudied. To account for elastic deformation, the blankholder surfaces are first virtually reworked by adjusting the nodalpositions on the die surfaces attaining a pressure distribution in accordance to the design phase SMF simulations with rigidsurfaces. The elastic FE-model with reworked surfaces then represents a stamping die in running production. The die isnow assumed to be exposed to changed process conditions giving an undesired blankholder pressure distribution. Thechanged process conditions could for example be due to a change of press line. An optimization routine is applied tocompensate the negative effects of the new process conditions. The optimization routine uses the contact forces acting onthe shims of the spacer blocks and cushion pins as optimization variables. A flexible simulation environment usingMATLAB and ABAQUS is used. ABAQUS is executed from MATLAB and the results are automatically read back intoMATLAB. The suggested optimization procedure reaches a pressure distribution very similar to the initial distributionassumed to be the optimum, and thereby verifying the method. Further research is needed for a method to transform thecalculated forces in the optimization routine back to shims thicknesses. Furthermore, the optimization time is relativelylong and needs to be reduced in the future for the method to reach its full potential.
Since its introduction in 2011, industry 4.0 has been coined the“4th industrial revolution” following mechanization, industrialization and IT/automation as the first three, and represents the current trend of automation technologies (cyber‐physical systems, internet of things, cloudcomputing, etc.,) in the manufacturing industry, with their potential for disruption of the manufacturing paradigm as we know it. However, the effect and role of industry 4.0 on the design and development of the new products to be manufactured in industry 4.0 facilities is not clear. This research presents a literature review to; 1) understand the concept of industry 4.0 from an implementation (state of practice) viewpoint, 2) learn about approaches and considerations currently deployed for developing products to be produced in manufacturing plants progressively transforming into industry 4.0 environments. Results reveal that the potential of industry 4.0 is underexploited within product design and development, especially in the conceptual stages lacking methods, tools, and approaches.While later stages of the product development (production planning,ramp‐up) have received some attention in regards with optimizing production operations, several publications acknowledge its potential to benefit earlier process stages.
The ability to control quality of a part is gaining increased importance with desires to achieve zero-defect manufacturing. Two significant factors affecting process robustness in production of deep drawn automotive parts are variations in material properties of the blanks and the tribology conditions of the process. It is imperative to understand how these factors influence the forming process in order to control the quality of a formed part. This paper presents a preliminary investigation on the front door inner of a Volvo XC90 using a simulation-based approach. The simulations investigate how variation of material and lubrication properties affect the numerical predictions of part quality. To create a realistic lubrication profile in simulations, data of pre-lube lubrication amount, which is measured from the blanking line, is used. Friction models with localized friction conditions are created using TriboForm and is incorporated into the simulations. Finally, the Autoform-Sigmaplus software module is used to create and vary parameters related to material and lubrication properties within a user defined range. On comparing and analysing the numerical investigation results, it is observed that a correlation between the lubrication profile and the predicted part quality exists. However, variation in material properties seems to have a low influence on the predicted part quality. The paper concludes by discussing the relevance of such investigations for improved part quality and proposing suggestions for future work.
The ability to predict and control the outcome of the sheet metal forming process demands holistic knowledge of the product/process parameter influences and their contribution in shaping the output product quality. Recent improvements in the ability to harvest in-line production data and the increased capability to understand complex process behaviour through computer simulations open up the possibility for new approaches to monitor and control production process performance and output product quality. This research presents an overview of the common process monitoring and control approaches while highlighting their limitations in handling the dynamics of the sheet metal forming process. The current paper envisions the need for a collaborative monitoring and control system for enhancing production process performance. Such a system must incorporate comprehensive knowledge regarding process behaviour and parameter influences in addition to the current-system-state derived using in-line production data to function effectively. Accordingly, a framework for monitoring and control within automotive sheet metal forming is proposed. The framework addresses the current limitations through the use of real-time production data and reduced process models. Lastly, the significance of the presented framework in transitioning to the digital manufacturing paradigm is reflected upon.
With growing demands on quality of produced parts, concepts like zero-defect manufacturing are gaining increasing importance. As one of the means to achieve this, industries strive to attain the ability to control product/process parameters through connected manufacturing technologies and model-based control systems that utilize process/machine data for predicting optimum system conditions without human intervention. Present work demonstrates an automated approach to process in-line measured data of tribology conditions and incorporate it within sheet metal forming (SMF) simulations to enhance the prediction accuracy while reducing overall modelling effort. The automated procedure is realized using a client-server model with an in-house developed application as the server and numerical computing platform/commercial CAD software as clients. Firstly, the server launches the computing platform for processing measured data from the production line. Based on this analysis, the client then executes CAD software for modifying the blank model thereby enabling assignment of localized friction conditions. Finally, the modified blank geometry and accompanied friction values is incorporated into SMF simulations. The presented procedure reduces time required for setting up SMF simulations as well as improves the prediction accuracy. In addition to outlining suggestions for future work, paper concludes by discussing the importance of the presented procedure and its significance in the context of Industry 4.0.
Ability to predict and control involved parameters and hence the outcome of sheet metal forming processes demand holistic knowledge of the product/-process parameter influences and their contribution in shaping the output product quality. Recent improvements in the ability to harvest inline production data and the capability to understand complex process behaviour through computer simulations opens up the possibility for new monitoring and control approaches forimproving production process performance and output product quality. Current work presents a framework for monitoring and control of sheet metal forming processes which incorporates a hybrid data-and-model-based approach. An initial attempt to evaluate the proposed frameworks’ ability to support output product quality and process performance enhancements is made by implementing the proposed approach via an in-house built wire-bending machine prototype. Initial experiments conducted using the built prototype indicate that the proposed framework has the potential to support such enhancements and further work is needed to validate the overall framework.
The presented work springs from the hypothesis that the learning process can beaugmented by a course design that caters to peer learning in diversified groups. Thepresented work focuses on the assessment part of the course design as the type and designof assessments in a course greatly influence students' learning and can therefore be used tostimulate a desired behavior in students.
Two, timewise parallel, engineering courses on the same topic, given on campus and atdistance respectively, are studied. The current situation and potential changes areinvestigated with the ambition of being able to provide common learning activities to harvestthe potential interaction effects originating from peer learning in diversified groups,specifically aiming to mix life-long learners with “regular” students.
As a considerable part of the students within the anticipated diversified cohort are expectedto be gainfully employed (life-long learners), learning activities are preferred to begeographically and temporally unbound. In order to fulfill this design requirement anexamination process is proposed where the student initially independently chooses a topicto research and explore. The students then share their findings with fellow students via thelearning platform. An examination process based on peer review, asynchronously via forumson the learning platform, and self-assessment is proposed to motivate and support learning.The Universal Design for Learning guidelines are considered while proposing theseactivities aiming to provide good conditions for learning and potentially increase retention inthe diversified student group.
Low vibration levels are a critical objective in automobile exhaust system design. It is therefore important for design engineers to be able to predict, describe and assess the dynamics of various system design proposals during product development. The aim of this thesis is to provide a deeper understanding of the dynamics of automobile exhaust systems to form a basis for improved design and the development of a computationally inexpensive theoretical system model. Modelling, simulation and experimental investigation of a typical exhaust system are performed to gain such an understanding and to evaluate modelling ideas. Special attention is given to the influence of the bellows-type flexible joint on the dynamics of the exhaust system. The investigations show that the exhaust system is essentially linear downstream of the flexible joint. Highly simplified finite element models of the major components within this part are suggested. These models incorporate adjustable flexibility in their connection to the exhaust pipes and a procedure is developed for automatic updating of these parameters to obtain better correlation with experimental results. The agreement between the simulation results of the updated models and the experimental results is very good, which confirms the usability of these models. Furthermore, the investigations show the great reduction of vibration transmission to the exhaust system that the bellows-type joint, either with or without an inside liner, gives in comparison with a stiff joint. For the combined bellows and liner joint, vibration transmission is, however, higher than for the bellows alone. Inclusion of the liner also makes the exhaust system behaviour significantly non-linear and complex, whereas the system behaviour proves to be essentially linear when the joint has no liner. This shows the importance of including a model of the liner in the theoretical system model when the liner is present in the real system. The choice of whether or not to include a liner in the real system is obviously a complex issue. The advantages of reduced bellows temperature and improved flow conditions should be weighed against the disadvantages found in this work. By combining the above findings it is concluded that in coming studies of how engine vibrations affect the exhaust system, the latter may be considered as a linear system if the flexible joint consists of a bellows. If the joint also includes a liner, the system may be considered as a linear subsystem that is excited via a non-linear joint.
Learning by reflection on doing
Experiential learning may be defined as “learning by reflection on doing”. The “doing” part in this case refers to work on open-ended engineering problems. Open-ended problems are problems that, in contrast to traditional closed exercises, have more than one possible solution. In engineering design these problems are also commonly ill-defined and wicked. Open-ended problem solving, besides reinforcing theoretical disciplinary knowledge, promotes skills such as critical thinking, problem solving, self-efficacy, confidence etc. Transitioning from closed to open-ended problems, learners develop their self-directed learning skills in accordance to Grow‘s stages in learning autonomy.
Effective and efficient product development is critical to business success on the increasingly competitive global market, and simulation has proven to support this in many sectors. The aim of this thesis is to study how properties of complex mechanical and mechatronic systems can be more efficiently and systematically predicted, described, assessed and improved in product development. The purpose is to elaborate an approach that can, rather than only verifying solutions that are already decided upon, support dialogues with customers, stimulate creation of new concepts and provide guidance towards more optimised designs, especially in early development stages. This is here termed simulation-driven design. To be useful for this, product models and simulation and optimisation procedures must be efficient, that is, they must accurately answer posed questions and point towards better solutions while consuming an acceptable amount of time and other resources. In this thesis a coordinated approach to create such efficient decision support is elaborated. This is done by action research through two industrial case studies; an automobile exhaust system representing a complex mechanical system and a water jet cutting machine representing a mechatronic system. The general knowledge gained from these case studies should be a good base for coming implementation of this approach as an inherent working routine in companies developing complex mechanical and mechatronic products. A specific result is a validated virtual model of the exhaust system, which facilitates fast structural dynamics simulation of customer proposed design layouts. It is also shown that the non-linear flexible joint between the manifold and the rest of the exhaust system makes the system behaviour complex. This has resulted in an additional general research question, namely how systems that are linear, except for small but significant non-linear parts, can be simulated in an efficient way. Another specific result is a validated real-time virtual machine concept for simulation of the water jet cutting machine, which facilitates early-stage design optimisation. As the mechanics and the control system are considered simultaneously, interaction effects can be utilised. An introductory optimisation study shows a significant potential for improved manufacturing accuracy and a more light-weight design. This potential would not likely have been found through a conventional sequential design approach. The results of this thesis indicate that there is a great potential for improved product development performance in small and medium-sized companies. By incorporating modern simulation support these companies can improve their competitiveness as well as contribute to improved resource efficiency of society at large. In doing so, it is important to find a good balance between model fidelity, validity and cost for achieving a relevant decision support. The coordinated approach to simulation-driven design elaborated in this thesis is a promising and systematic way of finding this balance.
A data analysis method aiming to support cause and effect analysis in design exploration studies is presented. The method clusters and aggregates effects of multiple design variables based on the structural hierarchy of the evaluated system. The resulting dataset is intended as input to a visualization construct based on colour-coding CAD models. The proposed method is exemplified in a case study showing that the predictive capability of the created, clustered, dataset is comparable to the original, unmodified, one
Design has become an intense ‘social activity’: working with others and sharing a common understanding are of critical importance to find satisfying solutions for customers and stakeholders. This leads to the issue of how to set up a collaborative, model-based physical environment to foster collaboration and knowledge sharing when different disciplines get together in the ‘design exercise’.This paper describes the development of such an environment, named the ‘Decision Arena‘. It further presents the results of an experimental study involving a cross-disciplinary team of industrial practitioners.
A wide variety of expert competencies, transcending traditional disciplines, are needed to foresee and evaluate the impact of decisions in the conceptual phase of engineering design. Where this previously was a trade-off regarding design and development of the pure physical artefact it is now a complex ambiguity game involving all disciplines touching a solution during its lifecycle, due to the movement towards integrated product-service solutions. Gathering the involved, normally diverse, group of stakeholders in a collaborative setting for design exploration exercises, sharing knowledge and values, is believed to augment decision making ability in early design. A model-driven environment for collaborative decision making is proposed as a solution that potentially may help harvesting these benefits. In this environment stakeholders interact with each other using digital models, model generated information, simulation data and product data collected in the field in order to evaluate design proposals by playing out potential usage scenarios and investigating cause and effect relationships. Initial work on conceptualizing, developing, and testing such an environment is done through a pilot study based on two industrial use cases. The development process iteratively unveils demands and constraints related to the environment. These discoveries go hand in hand with developing an infrastructure regarding both hardware and software as well as required human resources in a functional environment. Fully realizing the envisioned model-driven environment for collaborative decision making entails new ways of working requiring new knowledge as well as technological innovation. In that aspect, environment infrastructure and usage are elaborated on and direction for further research and development is indicated.
The shift towards Product-Service Systems (PSS) stresses the need to embed new and unique capabilities in Decision Support Systems, with the aim of helping the engineering team in handling the pool of information and knowledge available during decision events. Emerging from a multiple case study in the Swedish manufacturing industry, this paper describes the development of the Model-Driven Decision Arena (MDDA), an environment for collaborative decision-making that focuses on the early design phases of PSS. Based on the findings from multiple case studies, this paper illustrates the main goals of the MDDA, detailing its main functions, its physical environment, and its software architecture and models. This paper demonstrates the use of the MDDA in a case study related to the development of an asphalt compactor, presenting and discussing the results of verification activities conducted with industrial practitioners on the current MDDA prototype.
Most modern cars have a bellows-type flexible joint between the manifold and the catalytic converter to allow for thermal expansion and to decouple large engine movements and vibrations from the rest of the exhaust system. To obtain better understanding of the influence of this joint, the dynamic response of a typical exhaust system is studied when excited via different joint configurations. Measurements show the great order of reduction of vibration transmission to the exhaust system that a bellows joint, with and without an inside liner, gives in comparison with a stiff joint. For the combined bellows and liner joint vibration transmission is however higher than for the bellows alone. Together with some other aspects this makes the choice of including a liner in the exhaust system application complex. For a system in general the possibility of tuning the friction limit of the liner, to minimise overall vibrations through friction based damping, depends on how close to ideal the excitation source is and its location. Anyhow, the combined bellows and liner joint makes the exhaust system behaviour significantly non-linear, whereas the system behaviour proves to be essentially linear when the bellows has no liner, which imply that the liner needs to be included in theoretical models when present in the real system.
Bellows flexible joints are included in automobile exhaust systems to allow for engine movements and thermal expansion and to reduce vibration transmission. Generally the joint consists of a flexible bellows, an inside liner and an outside braid. In this work the bellows is considered. A straightforward way to model the bellows is to use shell finite elements. Due to the convoluted geometry of the bellows that procedure requires however a high number of elements, meaning that the bellows model would constitute a large part of the model of the exhaust system. For more effective dynamics simulations a beam finite element representation of the bellows has been presented in a prior work. This modelling procedure was implemented in the commercial software I-DEAS and was verified against experimental results available in the literature for single-ply bellows of constant mean radius. This paper suggests adjustments by which this procedure can be extended to model also multi-ply bellows of variable mean radius. Experimental investigations of a double-ply bellows having decreasing mean radius towards its ends are included for verification. The agreement between theoretical and experimental results is very good, implying that the suggested extension of the modelling procedure is valid. It is also shown that the procedure can easily be implemented into other commercial software (in this case ABAQUS). The experimental investigation reveals an intriguing resonance frequency shift at small excitation force levels. Although considered to be of minor significance for the present application of the bellows, a hypothetic qualitative explanation to the observed phenomenon is given.
Dynamic characteristics of a water jet cutting machine, to be used in a virtual machine implemented in an analysis tool for engineering design, are derived. Machine users need for more cost effective production put demands on faster cutting. Faster cutting results in higher dynamic loads. As a consequence, problems with unwanted vibrations that decrease cutting precision may occur. Prediction of such potential problems is facilitated by an analysis tool for evaluation of suggested design solutions early in the product development process. The present work contributes to ongoing development of such an analysis tool for design engineers. An iterative approach including both theoretical and experimental analysis is applied in order to derive a structural dynamics model of the studied machine. A complex dynamic behaviour of the machine is found. High correlation between results obtained from theoretical and experimental modal analysis implies that the developed model can be used with confidence in future studies of the machine’s total system behaviour.