Reduce Product Development Time Research Articles

Development and functional testing of battery management system algorithm for an electric bicycle using hardware in the loop testbench

An embedded Battery Management System (BMS) ensures the effective functionality and longevity of the vehicle battery systems. Testing the BMS using the Hardware in Loop (HIL) approach effectively increases safety and reduces product development time in the manufacturing sector. This research aims to develop an efficient battery management system with two-level protection for electric bicycles and test its functionality in the HIL configuration. The bicycle traction model and battery management system were first developed using a model-based design. Further, the model is tested and validated using battery emulators in the HIL methodology. The battery management system receives input data, such as current, voltage, and temperature, and monitors these parameters. The first level of protection involves the vehicle user receiving the warning when the monitoring parameters values exceed the given first safety threshold. As per the second safety threshold values, the BMS trips off the charging or discharging process when the voltage is 51V, the charge current is 5A, the discharge current is -5A and the IC temperature is 80 degrees. Also, BMS balances the cells in 3.84 min using passive balancing. Additionally, the BMS delivers a controlled current of 2.5A for safe battery charging. This methodology increases safety by reducing the potential risks of testing the BMS algorithms in the actual electric bicycle.

Investigating the Impact of Productivity on Surface Roughness and Dimensional Accuracy in FDM 3D Printing

Over the past three decades, 3D printing technologies have undergone significant advancements, revolutionizing various industries, such as automotive. Additive manufacturing has played a crucial role in reducing product development time and enabling the direct printing of functional parts. One of the key advantages of additive manufacturing is its ability to provide greater design freedom compared to traditional manufacturing methods. This means that complex geometries and varying material properties can be easily printed. In this research paper, the author focused on investigating the impact of layer thickness and part orientation on the surface roughness and accuracy of printed parts. The main objective was to identify the optimal combination of layer thickness and part orientation that would yield the best results in terms of surface roughness and accuracy, considering printing time as a variable. The results from printing time, accuracy and surface roughness measurements showed that the vertical orientation is the superior for cylindrical orientation.

Optimizing Automotive Manufacturing Systems through TOGAF Modelling

The objective of this research is to examine the viability of implementing the Open Group Architecture Framework to enhance the efficiency and performance of automotive manufacturing systems. The automotive industry remains confronted with challenges pertaining to the enhancement of manufacturing processes, the reduction of product development time, and the adjustment to swift technological progressions. The primary obstacles encountered in implementing process innovation, the complexity of the IT infrastructure, and the absence of system integration constitute the most significant challenges. The primary aim of this study is to present a resolution through the application of the TOGAF framework. By implementing this strategy, system synchronization will be enhanced, IT infrastructure will be simplified, and process innovation will be able to respond to market fluctuations more rapidly. The existing business processes are streamlined and consistent with the strategic progress of vehicle manufacturing firms. Nonetheless, business processes involving architectural applications continue to diverge from market demands and fail to align with evolving business requirements. In the context of automotive manufacturing, the TOGAF modeling methodology will be applied to analyze the data architecture, application architecture, strategic elements, and information technology infrastructure. Advise stakeholders in the automotive industry, facilitating the integration of TOGAF principles into endeavors to redesign systems. This will reduce the attainment of innovation, adaptability, and efficiency, all of which are critical for sustaining competitiveness in a dynamic marketplace. By applying TOGAF principles to the automotive manufacturing system, Enterprise Architecture can support ever more complex business requirements.

Multivariate statistical visualisation and modelling of GC–MS data for sensory quality prediction of flavoured cider as influenced by storage time and temperature

It is important to cider producers to ensure the optimal quality of their products directly after production, and after extended shelf life. Quality assessments usually involve regular and continuous sensory evaluation conducted by trained panels. The competitive cider production environment necessitates extensive sensory analysis for new product launches, as part of quality control of existing products and during the production process. This could potentially lead to panel fatigue, less accuracy in sensory evaluation and delays in product launches. This paper describes the development of a partial least squares (PLS) model for the prediction of cider quality based on multivariate correlation of sensory and gas chromatography-mass spectroscopy (GC–MS) volatile compound profile data of a flavoured cider. Clear differences between cider samples of various batches and storage conditions could be visualised using principal component analysis (PCA). However, the developed PLS model was able to predict the commercial cider’s quality irrespective of differences in batch, storage temperature or storage time. The main compounds that are strongly associated with sensory quality and its decline during shelf-life storage were identified. This model is the first quality prediction model to be developed for South African flavoured cider which could be used to facilitate fast, consistent and accurate quality assessment in the high-pressure cider production and trade environment. Furthermore, since the model captures the sensory data obtained from a trained technical panel, it can be used to facilitate the calibration of sensory panels across production sites, reduce product development time and better optimise processes that impact sensory quality.

Digital Twins and Smart Manufacturing for Wire Bonding

Low cost, excellent flexibility, and high yield rate have long been the drivers of wire bonding technology. In the past decade, advancements in wire bonding technology have significantly improved wire bond reliability and strengthened the adoption of the technology while maintaining its competitive advantage. Digital twins of wire bonding can now simulate and optimize 3D wire loop shapes to facilitate design-for-manufacturing (DFM), increase design flexibility, reduce product development time, and improve overall package yields. In particular, the benefits of digital twins have been realized in system-in-package (SiPs), large stack-die memory applications, and complex high pin count packages with multiple looping tiers. With increasing package complexity and modular package configurations, the need for smarter functionalities is imperative. More recently, technological developments in wire bonding have been targeted toward furthering design, quality, and time-to-market (TTM) from an Industry 4.0 smart manufacturing perspective. In this paper, we will introduce new digital twin simulation techniques to detect potential interference between wire bond capillaries and wire loops, various dies, passive components, and other structures within the package. These advanced capabilities are demonstrated on a real application and shown to help in the detection of design issues early in the product cycle and aid in the selection of capillary, wire, as well as optimization of the package layout. All these factors significantly improve the overall TTM of semiconductor packages. Technologies that provide improvements via autonomous monitoring and optimization are also strongly desired. We will also explore new on-bonder process monitoring capabilities to detect wire sway such that wire shorts and resultant yield losses can be minimized. Additionally, vision-guided enhancements to on-bonder loop height monitoring capabilities will also be discussed. These new advancements significantly improve production quality and yield, paving the way for smarter factories

A Sensitivity Study of a Thermal Propagation Model in an Automotive Battery Module

Thermal runaway is a major concern for lithium-ion batteries in electric vehicles. A manufacturing fault or unusual operating conditions may lead to this event. Starting from a single battery cell, more cells may be triggered into thermal runaway, and the battery pack may be destroyed. To prevent this from happening, safety solutions need to be evaluated. Physical testing is an effective, yet costly, method to assessing battery safety performance. As such, the potential of a numerical tool, which can cut costs and reduce product development times, is investigated in terms of capturing a battery module’s tolerance to a single cell failure. A 3D-FE model of a battery module was built, using a commercial software, to study thermal runaway propagation. The model assumes that when the cell jelly roll reaches a critical value, thermal runaway occurs. This approach was considered to study the module’s tolerance to a single cell failure, which was in reasonable agreement with what had been observed in full-scale experiments. In addition, quantitative sensitivity study on the i) model input parameters, ii) model space, and iii) time resolutions on the computed start time instant and time duration of thermal runaway were performed. The critical temperature was found to have the greatest influence on thermal runaway propagation. The specific heat capacity of jelly roll was found to significantly impact the thermal runaway time duration. The multi-physics model for battery thermal propagation is promising and worth to be applied with care for designing safer batteries in combination with physical testing.

Remaining useful life prognostics of lithium-ion batteries based on a coordinate reconfiguration of degradation trajectory and multiple linear regression

Lithium battery has been widely applied as new energy to cope with pressures in both form environment and energy. The remaining useful life (RUL) prognostics of lithium-ion batteries have become more critical. Convenient battery life prediction allows early detection of performance deficiencies to help maintain the battery system promptly. This paper proposes a RUL prognostics model of lithium-ion batteries based on a coordinate reconfiguration of degradation trajectory and multiple linear regression. First, a new sampling rule is used to reconfigure the coordinates of degradation data of new batteries and truncated similar batteries. Then, the relationship between similar and new lithium-ion batteries is established by using the reconfiguration data. Moreover, a new RUL prognostics model based on a coordinate reconfiguration of degradation trajectory and multiple linear regression is established by considering the influence of time-varying factors, which can improve prediction accuracy with small sample data and significantly reduce product development time and cost.

IDeS (Industrial Design Structure) Method Applied to the Automotive Design Framework: Two Sports Cars with Shared Platform

The present study was set to validate two different suburban-type sportscar bodies with shared common underpinnings. The chosen method to develop this project was the Industrial Design Structure (IDeS), which characterizes the ability to use the different innovative techniques known within the industrial field, across the whole organization. This method is embodied by following a series of structured analysis tools, such as QFD (Quality Function Deployment), Benchmarking (BM), Top-Flop analysis (TFA), Stylistic Design Engineering (SDE), Prototyping, Testing, Budgeting and Planning. This project aims to study the present-day car market and to foresee deployment in the near future. This attempt was confirmed by delivering the complete styling and technical feasibility characteristics of two different sports cars, obtained by the IDeS methodology. This approach of embodying design together with phases of product development would provide a better engineered, target-oriented product, that uses state-of-the-art style and CAD environments to reduce product development time and, hence, overall Time to Market (TTM).

FEM as a Package Design Tool for Corrugated Paperboard

Physical and virtual prototyping are common techniques to improve the product design process and quality in the engineering field. However, due to the complex mechanical nature of corrugated board, which requires specific material models and finite element techniques, the corrugated board packaging industry has been unable to benefit from virtual prototyping at the same scale as the other industrial fields. This article investigates the advantages and disadvantages of physical and virtual prototyping, focusing on the effect of virtual prototyping in four aspects: its impact on design process time, on the established workflow of designers, the effect on material optimization of the products and virtual prototyping reliability assessment in corrugated paperboard design. An experiment is implemented with comparative design processes in the corrugated board packaging company to examine these key parameters. The finite element model-based tool has been developed to improve the product design process and quality. Results indicate that a virtually assisted product design process significantly reduces product development time, enhances material optimization and adds value to visual 3D content. Virtual prototyping’s reliability was found acceptable compared to physical prototyping. However, to interpret any strength analysis results, deeper knowledge of the subject and corrugated materials is needed.

Research of Impregnated Carbon Fiber Tow Quality for 3D Composites Printing

AbstractTime nowadays becoming more and more important resource in the life. Additive manufacturing technologies allow to produce very complex shapes of products reducing product development time. Moreover, additive manufacturing of composite parts allows to produce structural parts with perfect mechanical properties. Though production of composites is still very complicated because reinforcement material needs to be prepared for the process. Moreover, preparation process can significantly influence on quality of produced part. This article focusing on preparation procedure of continuous carbon fiber (CCF) tow for 3D printing of composite structures. Visual analysis of impregnated CCF showed that internal air voids area in the analyzed cross‐sections fluctuates from 11.1% to 22.8%. Meanwhile, after pull‐out test, significant effect of impregnation on adhesion is observed. Not impregnated CCF is pulled‐out from matrix material with the tensile force 38 N, however impregnated CCF is not even pulled‐out with the force 138 N.

Potential applications of additive manufacturing technologies in the vehicle industry

One of the most competitive fields on the planet is the automotive industry. Newmarket and innovative designs regularly arise, necessitating the development of new manufacturing methods to keep up with the automotive industry. Additive manufacturing offers a significant competitive advantage in this industry, serving as a disruptive strategy by increasing production flexibility, reducing product development time, and providing optimal automotive components and bespoke vehicle products on demand. Additive manufacturing on soft assembly tools or specialised tools to make automotive components enhances automotive production. Additive Manufacturing’s freeform capability allows for the design and direct fabrication of optimised automotive components aimed at improving vehicle performance, as well as tailored assembly tools to boost productivity. Another related technological advantage of additive manufacturing is the ability to create lightweight components with the help of generative design algorithms. Furthermore, the time to market for Additive Manufacturing parts has fallen dramatically, allowing mass customisation to become a reality. The strong downward trend in fuel consumption offers new automobile design, performance, and compliance with regulations. Considering the actual example switch from the conventional combustion engine to other motion systems, Additive Manufacturing is a critical enabler technology for modern automobiles. This paper provides an overview of Additive Manufacturing applications in the automobile sector, focusing on the technical and economic benefits of this manufacturing technology.

How to successfully introduce concurrent engineering into new product development?

Today, three conditions are crucial for a company to be competitive on the market: quality, reduced time and low costs for the development of new products. The paper shows how companies developing new products (NPD) for the market can successfully implement concurrent engineering as an improvement of project management, in order to reduce product development time and costs and to ensure the quality expected by customers. The methodology presented in this paper is based on three main pillars of knowledge: project management, teamwork and concurrent engineering. The methodology provides a step-by-step guideline for the introduction of concurrent engineering in a company. This paper also presents the results of 10 Slovenian companies where this methodology has been tested on 20 pilot projects. The results show that managed projects upgraded with the principles of concurrent engineering lead to cost reduction, shorter development time and fewer discrepancies.

Research on DSM-based Product Development Coupling Activity Overlapped Execution Model

Aiming at the problem of overlapping execution of coupling activities in the product development process, using Markov Chain method to describe the iterative process of coupling activities based on the design structure matrix (DSM). Then introduced the information output, input time factor matrix and rework risk matrix to describe the complex information interaction between design activities, constructed a model of rework time caused by design activity coupling and iteration by quantifying the overlap of design activities, and then established the entire project time cost model for coupled activity sets. Finally, an application analysis was performed with examples. The research shows that this method can effectively reduce product development time and provide a certain theoretical basis for the rational planning and scientific guidance of the overlapping execution mode of coupled activities in the product development process.

Study the Bioprinting Process in Biomedical and Tissue Engineering Fields

3D bioprinting is faster and more accurate than ever it has been in biomedical and tissue engineering. The facility to quickly generate multiple iterations of a physical evaluation model through 3D ptinting can dramatically reduce product development times, allowing medical designers to explore more variations and eliminate failures faster. These techniques are helping medical educators create detailed anatomical models, letting surgeons devise more ergonomic and patients-specific surgical tools, also helping device manufactures compress their time to market. Using 3D bioprinting in medical field is quite complex task which implies a multidisciplinary approach and very good knowledge of engineering as well as medicine. In this study we will discuss various types of 3D bioprinter and their functionality in biomedical fields.

Empirical High Cycle Fatigue Assessment Model of MEMS Devices

Abstract Many microelectromechanical systems (MEMS) devices generate large deflections and stresses under some severe loads, and this cumulative stress often causes structural fatigue when applying high cyclic loads. It affects the reliability and quality of the product and can easily damage structures in harsh environments. For example, accelerometers and gyroscopes in motion sensors always combine a movable mass component with a bending or torsion spring, which can severely deform their structure at some large accelerations or angular accelerations. After this high cycle of deformation, the spring structure will be damaged and cause device failure, we call this failure mode high cycle fatigue (HCF). This is very common for MEMS products, but it is difficult for designers to predict it at design stage. To prevent early fatigue problems and reduce product development time, we developed a simulation process and empirical prediction model to help designers predict HCF and improve fatigue strength of moving structures used in MEMS devices. In this study, a bending and a torsion beam are used as test vehicles. A combination of dynamic and electromechanical coupling simulations was developed and applied to analyze the effects of frequency under HCF testing. The test structures were fabricated using silicon-on-insulator (SOI) MEMS technique and these test structures were used to validate empirical life prediction equation developed in this research. The frequency effect of HCF was also to be included in the developed prediction model. Based on the test results, the accuracy of the empirical prediction equation is improved by including frequency effect.

Solving the Difficulties and Challenges Facing Construction Based on Concurrent Engineering in Yemen

Due to the highly competitive commercial environment in the market in Yemen at present, the construction industry in Yemen, like other industries, is under pressure to reduce product development time and overall project costs, improve product quality, and satisfy customers. To keep pace with the competitive environment of the market in Yemen, most enterprises tend to adopt the best and new technologies, new management concepts and philosophies such as Total Quality Management (TQM) and concurrent engineering (CE) to achieve improvements in the process of product development. In this paper, the problem of fragmentation brought by the serial engineering in construction in Yemen is discussed firstly. Then, the integration process and CE adoption by the construction industry in Yemen are explained for enabling construction agencies in Yemen to improve the development process of their projects and to solve the current fragmentation problems such as the lack of communication, adversarial culture and the lack of customer focus, which allows the construction process to improve and become more effective and efficient.

Two-stage product design selection by using PROMETHEE and Taguchi method: A case study

The main goal of this paper was to introduce the methodology for product design selection. The proposed methodology combines two classical methods to find the most appropriate design for the new product, through a reduced number of alternatives (product variants) and experiments for the selection process. In the first stage, the multi-criteria decision-making method, PROMETHEE was used for selecting the most suitable design, according to the chosen preferences and criteria. In the second stage, the Taguchi method was used in order to define the most appropriate parameters for selected suitable design. The fundamental scientific contribution of this paper refers to a benefit introduced by combining these methods. This benefit is related to the reduction of product development time which has a significant effect on manufacturing process time due to the high market pressure. The proposed methodology was applied to find the appropriate table design for CNC milling machine located in the Lean Learning factory. However, this is just one case study to present the proposed methodology which can be applied for other optimization of other product designs. Before applying the proposed methodology for this case study, the methodology is validated on a simple example.

Sine-Sweep qualification test for engine components: The choice of simulation technique

Most of mechanical components, especially those belonging to aerospace sector, vehicles and, in particular, the automotive sector need an experimental qualification phase aimed to determine both their functionalities and their structural strength. Regarding the structural strength, the tests most commonly required by regulatory standards and typically performed belong to two categories, so similar as different: Sine-Sweep test and Random test. The present work is part of a consolidated research topic aimed to develop design techniques making them as much simpler and faster as possible in order to reduce product development times up to the virtual verification of test conditions. In particular, the present work is aimed to propose a frequency domain methodology for dynamic simulation and evaluation of the fatigue behavior for Sine-Sweep test, comparing it with the time domain technique that is considered as reference. The activity carried out in collaboration with a well-known automotive industry (HPE-COXA S.p.A.) verified these methodologies on a test case proposed by the company itself, i.e. the qualification of a set of supplying pipe of a high performance engine. The comparison between the time domain approach and the proposed approach in frequency domain certifies the extreme reliability of the latter as well as the advantages it offers to the designer in terms of computational times that results to be extremely reduced. The activity then created the prerequisites for the development of future research activities aimed to reduce calculation times as much as possible making such calculation tools of easily accessible to the industrial community.

Model - Based Design and Control of Lead-Acid Batteries: Is There Any More Juice Left in a System That Is 158 Years Old?

The low initial cost, ease of manufacture and relatively mature state of technology make lead-acid batteries the most popular energy storage choice for many applications. Lead-acid batteries exist in different configurations, each suitable for different applications and performance requirements. It is worth addressing the question as to whether model-based strategies can help realize even greater improvements in interrelated overall performance characteristics such as rate performance, cycle life and cost, and in overcoming factors that limit operational performance besides reducing product development time and cost by reducing the amount of testing required for development and validation. Some potential uses of model-based approaches are listed below: For phenomena within lead-acid batteries for which no reliable or physically meaningful models exist, model development to provide a quantitative description may be useful. This may be a new physics-based model based on existing theory, a combination of existing models (e.g. extension to multiple spatial dimensions) or an empirical model with adjustable parameters which may be obtained by fitting experimental data. These mathematical models may then be used to simulate the time evolution of the relevant variables. Several continuum-level models with varying predictive capabilities have been reported in the literature1-2. At the same time, there is scope for more complete descriptions of degradation phenomena such as irreversible sulfation, which is a major cause of cell failure.3 For situations where mathematical models exist, computationally efficient simulations may be performed by exploiting the mathematical structure of model equations to create suitable formulations.4-5 Existing models may also be used to obtain useful qualitative and quantitative design insights. Parametric optimization of design parameters for a certain objective function is also possible, but is especially suitable with computationally efficient physics-based models.6 Different objective functions may be defined – total charge, local overpotentials etc. The optimization problem formulation can include mathematically equivalent constraints to prevent undesirable phenomena (e.g. sulfation, gas evolution). The use of physics-based models gives us predictions of state variables internal to the cell, which allows us to formulate a far more complete description of the problem than would be possible by simple empirical models. Acknowledgements The authors acknowledge financial support from the Department of Chemical Engineering and the Clean Energy Institute at the University of Washington. References H. Gu, T.V. Nguyen, and R.E. White, J. Electrochem. Soc., 134, 2953 – 2960 (1987).M. Cugnet, S. Laruelle, S. Grugeon, B. Sahut, J. Sabatier, J-M Tarascon, and A. Oustaloup, J. Electrochem. Soc., 156, A974 – A985 (2009).K.S. Gandhi, J. Electrochem. Soc., 164, E3092 – E3101 (2017).A.B. Ansari, V. Esfahanian, and F. Torabi, Appl. Energy, 173, 152-167 (2016).V. Esfahanian, F. Torabi, and A. Mosahebi, J. Power Sources, 176, 373-380 (2008).G. Kujundzic, S. Iles, J. Matusko, and M. Vasak, Appl. Energy, 187, 189-202 (2017).

On the tolerable limits of granulated recycled material additives to maintain structural integrity

Production and maker spaces are increasingly generating mixed plastic material waste of varying quality from 3-D printers. Industrial interest is growing in embedding granulated recycled particulate material additives into a virgin binding matrix. Examples include the introduction of granulated mixed recycled materials into 3-D printer material, concrete, and pavement. The stress load-sharing between the particulate additive and the binding matrix is an important factor in design and development of these composite materials. With mixed material additives, a designer is interested in the variation of such predicted load-sharing. However, experimental development is costly and time-consuming, thus analytical and semi-analytical estimates are desired for accelerated development. In this work, we expand on previous analytically correlated phase-averaged micro- and macrostructural loading to include variational effects present in mixed recycled material. In addition, model trade-offs are provided to aid designers in quickly selecting application specific mixtures. This framework identifies the stress contributions, and their variation, to reduce product development time and costs, which could greatly accelerate material recycling and reuse for improved infrastructure materials, low-cost 3-D printer filament, and reduced waste towards a more circular economy.