Accelerate Product Development Research Articles

Artificial Intelligence in Strategic Business Decisions: Enhancing Market Competitiveness

Abstract: Integrating Artificial Intelligence (AI) into strategic decision-making is essential for enhancing market competitiveness in today's dynamic business environment. AI technologies such as machine learning, natural language processing (NLP), and predictive analytics optimize operations, personalize customer experiences, and drive product innovation. Machine learning algorithms analyze vast data to uncover patterns, aiding better decision-making. Predictive analytics forecasts market trends and consumer behaviors, allowing companies to anticipate demand and streamline supply chains, reducing risks like overproduction and stockouts. NLP-powered chatbots improve customer interactions by handling routine inquiries, freeing human agents for complex issues, and enabling personalized marketing. AI also accelerates product development by analyzing market data and consumer feedback, simulating scenarios, and predicting outcomes. Operational efficiency is enhanced through automation and optimized workflows, saving costs and increasing productivity. Despite these benefits, challenges such as data privacy, algorithmic bias, significant investment, and a shift to a data-driven culture must be managed. Effective AI integration offers significant competitive advantages, positioning companies to leverage predictive analytics, personalized customer interactions, and operational efficiency for growth and innovation.

Harmonising humans and technology: Exploring the dynamics of cognitive production, artificial intelligence and social communication in cybernetic systems

Agile cognitive production systems mark a manufacturing paradigm shift, propelled by the demand for accelerated product development and the adoption of digitalised production systems across extensive supply networks. Cognitive manufacturing emphasises the role of technology and automation in the learning and adaptation process. These systems independently analyse data, make real-time adjustments and optimise processes, sometimes minimising the need for human intervention. Based on a conceptual framework that draws on the diversity of living systems and cognitive processes, cybernetics provides a solid theoretical background. It explores the intricate connections between cognition, self-organising systems and the challenges arising from the autonomy of such systems. The concept of "cognition" in "agile cognitive systems" moves away from the conventional understanding of purely technical processes and towards human thought processes. This departure fosters a dynamic exchange where individual thoughts resonate in social communication. Addressing the role of artificial intelligence (AI), the article emphasises examining computers from a social science standpoint, exploring the relationship between computers and mental systems, capturing human faculties such as cognition, utterance, and understanding. The integration of AI into computer-mediated communication leads to the question how AI-equipped computers intersect with societal intelligence notions. The inherent intransparency of AI, often viewed as a black box, prompts queries about the potential black-box nature of an autonomously controlled AI factory or supply chain. In this hypothetical scenario, the idea of the supply chain as a communication network is challenged, emphasising the importance of human involvement. Research on human-centric cognitive production emphasises explainable AI and human-in-the-loop. This orientation goes beyond the technical dimensions and incorporates social science considerations, which emphasises the holistic nature of current research. In essence, research in the field of cognitive production is a comprehensive exploration of the complex interplay between human cognition, artificial intelligence and the evolving landscape of modern production systems.

Toward trustworthy medical device in silico clinical trials: a hierarchical framework for establishing credibility and strategies for overcoming key challenges.

Computational models of patients and medical devices can be combined to perform an in silico clinical trial (ISCT) to investigate questions related to device safety and/or effectiveness across the total product life cycle. ISCTs can potentially accelerate product development by more quickly informing device design and testing or they could be used to refine, reduce, or in some cases to completely replace human subjects in a clinical trial. There are numerous potential benefits of ISCTs. An important caveat, however, is that an ISCT is a virtual representation of the real world that has to be shown to be credible before being relied upon to make decisions that have the potential to cause patient harm. There are many challenges to establishing ISCT credibility. ISCTs can integrate many different submodels that potentially use different modeling types (e.g., physics-based, data-driven, rule-based) that necessitate different strategies and approaches for generating credibility evidence. ISCT submodels can include those for the medical device, the patient, the interaction of the device and patient, generating virtual patients, clinical decision making and simulating an intervention (e.g., device implantation), and translating acute physics-based simulation outputs to health-related clinical outcomes (e.g., device safety and/or effectiveness endpoints). Establishing the credibility of each ISCT submodel is challenging, but is nonetheless important because inaccurate output from a single submodel could potentially compromise the credibility of the entire ISCT. The objective of this study is to begin addressing some of these challenges and to identify general strategies for establishing ISCT credibility. Most notably, we propose a hierarchical approach for assessing the credibility of an ISCT that involves systematically gathering credibility evidence for each ISCT submodel in isolation before demonstrating credibility of the full ISCT. Also, following FDA Guidance for assessing computational model credibility, we provide suggestions for ways to clearly describe each of the ISCT submodels and the full ISCT, discuss considerations for performing an ISCT model risk assessment, identify common challenges to demonstrating ISCT credibility, and present strategies for addressing these challenges using our proposed hierarchical approach. Finally, in the Appendix we illustrate the many concepts described here using a hypothetical ISCT example.

A Model Study to Assess Fibrillation and Product Stability to Support Peptide Drug Design.

The fibrillation of therapeutic peptides can present significant quality concerns and poses challenges for manufacturing and storage. A fundamental understanding of the mechanisms of fibrillation is critical for the rational design of fibrillation-resistant peptide drugs and can accelerate product development by guiding the selection of solution-stable candidates and formulations. The studies reported here investigated the effects of structural modifications on the fibrillation of a 29-residue peptide (PepA) and two sequence modified variants (PepB, PepC). The C-terminus of PepA was amidated, whereas both PepB and PepC retained the carboxylate, and Ser16 in PepA and PepB was substituted with a helix-stabilizing residue, α-aminoisobutyric acid (Aib), in PepC. In thermal denaturation studies by far-UV CD spectroscopy and fibrillation kinetic studies by fluorescence and turbidity measurements, PepA and PepB showed heat-induced conformational changes and were found to form fibrils, whereas PepC did not fibrillate and showed only minor changes in the CD signal. Pulsed hydrogen-deuterium exchange mass spectrometry (HDX-MS) showed a high degree of protection from HD exchange in mature PepA fibrils and its proteolytic fragments, indicating that most of the sequence had been incorporated into the fibril structure and occurred nearly simultaneously throughout the sequence. The effects of the net peptide charge and formulation pH on fibrillation kinetics were investigated. In real-time stability studies of two formulations of PepA at pH's 7.4 and 8.0, analytical methods detected significant changes in the stability of the formulations at different time points during the study, which were not observed during accelerated studies. Additionally, PepA samples were withdrawn from real-time stability and subjected to additional stress (40 °C, continuous shaking) to induce fibrillation; an approach that successfully amplified oligomers or prefibrillar species previously undetected in a thioflavin T assay. Taken together, these studies present an approach to differentiate and characterize fibrillation risk in structurally related peptides under accelerated and real-time conditions, providing a model for rapid, iterative structural design to optimize the stability of therapeutic peptides.

PROCESS DEVELOPMENT IN MECHANICAL ENGINEERING: INNOVATIONS, CHALLENGES, AND OPPORTUNITIES

Process development in mechanical engineering encompasses a broad spectrum of innovations, challenges, and opportunities that drive advancements in various industries. This review delves into the multifaceted landscape of process development within mechanical engineering, highlighting key themes and trends. Innovations in process development are propelled by the continuous quest for efficiency, sustainability, and enhanced performance. Advances in additive manufacturing, automation, and digitalization have revolutionized traditional manufacturing processes, enabling the creation of complex geometries with unprecedented precision and speed. Additive manufacturing techniques such as 3D printing offer versatility in material selection and design freedom, facilitating rapid prototyping and customization while minimizing material wastage. Automation technologies, including robotics and AI-driven systems, optimize production workflows, augmenting productivity and reducing human error. Moreover, digital twins and simulation tools empower engineers to simulate and optimize processes virtually, accelerating product development cycles and minimizing costly experimentation. However, alongside these innovations, mechanical engineers face a myriad of challenges. The integration of new technologies often requires substantial investment in infrastructure and workforce training. Quality control and assurance remain critical concerns, particularly in additive manufacturing, where ensuring part integrity and repeatability is paramount. Furthermore, the sustainability implications of emerging processes must be carefully evaluated to mitigate environmental impact and resource depletion. Despite these challenges, process development in mechanical engineering presents abundant opportunities for growth and advancement. The rise of Industry 4.0 initiatives fosters collaboration between academia, industry, and government, driving research and development efforts towards sustainable and interconnected manufacturing ecosystems. The advent of advanced materials, including composites and biomaterials, unlocks new possibilities for lightweight structures, enhanced performance, and tailored functionalities. Additionally, the pursuit of circular economy principles promotes resource efficiency and waste reduction throughout the product lifecycle. In conclusion, process development in mechanical engineering is characterized by a dynamic interplay of innovation, challenges, and opportunities. By embracing emerging technologies, addressing key challenges, and leveraging collaborative partnerships, mechanical engineers can drive transformative change across industries, paving the way for a more efficient, sustainable, and interconnected future.
 Keywords: Process, Development, Mechanical, Engineering, Innovation, Review.

Pembinaan UMKM Melalui Inovasi Produk Pemanfaatan Belimbing Wuluh Menjadi Masker Organik

Product innovation is one way for UMKM to win the competition. Skin care is the most sought after product lately. Therefore, the innovation of skin care facial masks from starfruit is the choice of the fostered UMKM. This UMKM development was carried out in South Rabangodu Subdistrict in the UMKM group. The implementation method is by introducing innovation, producing face masks using abundant local materials in locations, then marketing them through online social media and offline sales. The innovation of using starfruit to make organic facial masks is quite popular with the public. Promotion via online and offline social media supports accelerated product development and adoption. The innovation of the starfruit mask has become a new business option for UMKM in the South Rabangodu Region

Remanufacturing and pricing strategies under modular architecture

Modular design is an approach that accelerates product development and facilitates product remanufacturing. We consider three product categories under modular architecture: the new product, the partially remanufactured product, and the fully remanufactured product. The new product consists solely of the new modules, the partially remanufactured product is composed of both the new and remanufactured modules, and the fully remanufactured product comprises entirely the remanufactured modules. In the market, there are environmentally conscious consumers known as green consumers, who place equal value on both new and remanufactured modules. However, other consumers known as primary consumers assign a lower value to the remanufactured module in comparison to the new one. This paper proposes an analytical model to investigate a manufacturer’s optimal remanufacturing and pricing strategies. Our results show that the manufacturer’s choice of the remanufacturing strategy depends on the production costs of the partially and fully remanufactured product, as well as the proportion of green consumers. In the absence of green consumers, the manufacturer should only produce the new product when the production costs of both the partially and fully remanufactured products are high. Otherwise, the manufacturer will produce the partially or the fully remanufactured product. Differently, in the presence of green consumers, the manufacturer should consistently engage in remanufacturing activities, and the specific remanufacturing and pricing strategies depend on the production costs. Importantly, regardless of whether there are green consumers, the manufacturer should adopt the partial remanufacturing strategy when the production cost of the partially remanufactured product is low. Regarding consumer surplus and social welfare, we find that in the absence of green consumers, the manufacturer’s optimal remanufacturing strategy consistently achieves the highest level of consumer surplus and social welfare, but this may not hold true in the presence of green consumers. Furthermore, a higher proportion of green consumers can sometimes decrease the manufacturer’s profit, consumer surplus, and even social welfare.

Agile approach to accelerate product development using an MVP framework

ABSTRACT Customers are looking for suppliers to deliver complex systems at faster rates, targeting three year cycle. This timeframe is challenging for low Technology Readiness Level (TRL) developments, increasing requirements engineering effort, leaving engineers little time and scope for innovation. Test and Evaluation (T&E) activities are often performed in Australia near the end of the process diminishing their value , compensating for a lack of modelling and simulation in early stages. Waterfall Project Management dominates where capability is hardware focused, leading to overruns and deliver capability that falls short of customer expectations in some areas. The Agile approach has been successfully used in software-focused developments. Project managers have been slow to adopt Agile for developments in areas like Defence where the safety is hardware dominant claiming the Agile process lacks necessary governance , increasing risk in the development. This paper examines the extant developmental process in a Defence context and proposes a Minimal Viable Product (MVP)-based framework using Agile to accelerate the development and mitigate risk escalation.

EFFICIENCY OF ACTIVITY AND MANAGEMENT OF THE ENTERPRISE IN THE CONDITIONS OF POST-WAR RECONSTRUCTION

The economic growth of the national economy, first of all, depends on the level of production development. It is production that forms the basis of the economy of any state. Successful functioning of enterprises in modern economic conditions largely depends on various factors of external and internal environment, as well as on how effectively and purposefully the enterprise is engaged in innovation activities. Growth of economy of any country occurs due to two factors only: accumulation of capital (means of production, raw materials) and deepening of division of labor. The creation and accumulation of capital is carried out by entrepreneurs when they invest part of their profits in means of production, raw materials and inputs. The greater the profit of entrepreneurs, the more they invest in the creation of new capital. The development and implementation of innovations at the enterprise should contribute to the growth of the technical and technological base of the enterprise, which is a part of the production capital materialized in buildings, structures, machinery, equipment and other means of labor, which are repeatedly used in production, transferring their value to the finished product. Manufacturing, services, transportation, and even agriculture are using an increasingly wide range of digital technologies. The underlying technologies and processes have far-reaching implications for the organization of work, production and commerce, reinforcing the existing organizational and geographic dispersion of knowledge-intensive production functions and occupational groups. Companies using digital technologies can improve the efficiency of their organizations and gain opportunities to access and serve consumers more easily, accelerate product development, and create new goods and services at lower costs without the need for extensive systems-level expertise or in-house IT staff.

Information Embedding for Secure Manufacturing: Challenges and Research Opportunities

Abstract The digitization of manufacturing has transformed the product realization process across many industries, from aerospace and automotive to medicine and healthcare. While this progress has accelerated product development cycles and enabled designers to create products with previously unachievable complexity and precision, it has also opened the door to a broad array of unique security concerns, from theft of intellectual property to supply chain attacks and counterfeiting. To address these concerns, information embedding (e.g., watermarks and fingerprints) has emerged as a promising solution that enhances product security and traceability. Information embedding techniques involve storing unique and secure information within parts, making these parts easier to track and to verify for authenticity. However, a successful information embedding scheme requires information to be transmitted in physical parts both securely and in a way that is accessible to end sers. Ensuring these qualities introduces unique computational and engineering challenges. For instance, these qualities require the designer of the embedding scheme to have an accurate model of the cyber-physical processes needed to embed information during manufacturing and read it later in the product life cycle, as well as models of the phenomena that may degrade that information through natural wear-and-tear, or through adversarial attacks. This article discusses challenges and research opportunities for the engineering design and manufacturing community in developing methods for efficient information embedding in manufactured products.

The Role of Information Technology in Driving Innovation and Entrepreneurial Business Growth

In the era of globalisation and rapid advances in information technology, the role of IT in driving innovation and growth of entrepreneurial businesses has become increasingly important. In this research, an in-depth analysis of the role of information technology in driving innovation and growth of entrepreneurial businesses will be conducted. This research will involve collecting secondary data from various sources. The focus of this study is primarily qualitative. Methods for gathering data include paying close attention to detail while seeing and recording data, and then using analytical techniques like data reduction, visualization, and inference to draw conclusions. The results of this study conclude that IT has a very important role in driving innovation and growth of entrepreneurial businesses. In today's digital era, entrepreneurs need to utilise IT effectively to accelerate product development, improve operational efficiency, expand market reach, drive business innovation, and enhance customer experience.

Review of coating cracking and barrier integrity on paperboard substrates

Barrier packaging formats are major growth areas for the pulp and paper industry. It is technically challenging to maintain barrier properties during converting and end-use applications. Improved manufacturing capabilities and coating formulation knowledge will help maintain barrier integrity and enable growth of barrier products in challenging applications. These improvements will accelerate product development and commercialization, and allow faster response to product performance issues such as cracking. The literature on coating cracking provides knowledge mostly on the effects of coating formulations and to a lesser extent on substrate effects. Despite a large number of publications dedicated to coating failures, the approach to improve coating cracking remains empirical, and the transferability between studies and to real life applications has not been well established. Model development that successfully predicts commercial performance is in its infancy. However, some of these simplified models do a fairly good job predicting experimental data. The current work reviews the state of understanding as regards coating and barrier cracking and highlights the need for more research on cracking and barrier integrity.

An Automated Hardware-in-Loop Testbed for Evaluating Hemorrhagic Shock Resuscitation Controllers.

Hemorrhage remains a leading cause of death, with early goal-directed fluid resuscitation being a pillar of mortality prevention. While closed-loop resuscitation can potentially benefit this effort, development of these systems is resource-intensive, making it a challenge to compare infusion controllers and respective hardware within a range of physiologically relevant hemorrhage scenarios. Here, we present a hardware-in-loop automated testbed for resuscitation controllers (HATRC) that provides a simple yet robust methodology to evaluate controllers. HATRC is a flow-loop benchtop system comprised of multiple PhysioVessels which mimic pressure-volume responsiveness for different resuscitation infusates. Subject variability and infusate switching were integrated for more complex testing. Further, HATRC can modulate fluidic resistance to mimic arterial resistance changes after vasopressor administration. Finally, all outflow rates are computer-controlled, with rules to dictate hemorrhage, clotting, and urine rates. Using HATRC, we evaluated a decision-table controller at two sampling rates with different hemorrhage scenarios. HATRC allows quantification of twelve performance metrics for each controller configuration and scenario, producing heterogeneous results and highlighting the need for controller evaluation with multiple hemorrhage scenarios. In conclusion, HATRC can be used to evaluate closed-loop controllers through user-defined hemorrhage scenarios while rating their performance. Extensive controller troubleshooting using HATRC can accelerate product development and subsequent translation.

Development and Characterization of an Ex Vivo Testing Platform for Evaluating Automated Central Vascular Access Device Performance.

Access to the central vasculature is critical for hemodynamic monitoring and for delivery of life-saving therapeutics during emergency medicine and battlefield trauma situations but requires skill often unavailable in austere environments. Automated central vascular access devices (ACVADs) using ultrasound and robotics are being developed. Here, we present an ex vivo lower-body porcine model as a testing platform for evaluation of vascular devices and compare its features to commercially available platforms. While the commercially available trainers were simpler to set-up and use, the scope of their utility was limited as they were unable to provide realistic anatomic, physiologic, and sonographic properties that were provided by the ex vivo model. However, the ex vivo model was more cumbersome to set-up and use. Overall, both have a place in the development and evaluation pipeline for ACVADs before testing on live animals, thus accelerating product development and translation.

Predictability of mechanical behavior of additively manufactured particulate composites using machine learning and data-driven approaches

Additive manufacturing and data analytics are independently flourishing research areas, where the latter can be leveraged to gain a great insight into the former. In this paper, the mechanical responses of additively manufactured samples using vat polymerization process with different weight ratios of magnetic microparticles were used to develop, train, and validate a neural network model. Samples with six different compositions, ranging from neat photopolymer to a composite of photopolymer with 4 wt.% of magnetic particles, were manufactured and mechanically tested at quasi-static strain rate and ambient environmental conditions. The experimental data were also synthesized using a data-driven approach based on shape-preserving piecewise interpolations while leveraging the concept of simple micromechanics rule of mixture. The overarching objective is to forecast the mechanical behavior of new compositions to eliminate or reduce the need for exhaustive post-manufacturing testing, resulting in an accelerated product development cycle. The ML model predictions were found to be in excellent agreement with the experimental data for prognostication of the mechanical behavior of physically tested samples with near-unity correlation coefficients. Furthermore, the ML model performed reasonably well in predicting the mechanical response of untested, newly formulated compositions of photopolymers and magnetic particles. On the other hand, the data-driven approach predictions suffered from processing artifacts, demonstrating the superiority of ML algorithms in handling this type of data. Overall, this analysis approach holds great potential in advancing the prospects of additive manufacturing and model-less mechanics of material analyses. A byproduct of the ML approach is using the results for quality assurance, accelerating the acceptance of additively manufactured parts into industrial deployments.

Toward digital validation for rapid product development based on digital twin: a framework

Product development should cover product design, validation, and manufacturing. In traditional product development, physical validation based on physical trial manufacturing is the key step to confirm the design scheme before physical manufacturing. However, physical validation is costly and inefficient, which could be the main obstacle to achieving rapid product development. The emergence of digital twin provides an opportunity to accelerate product development by eliminating physical validation toward digital validation in the smart manufacturing era. Therefore, a framework of rapid product development based on digital twin is proposed in this paper. During product development, the new product is designed according to the new requirements in the virtual space, in which the existing digital twins of products can be referenced. Then, an ultrahigh-fidelity virtual manufacturing system is constructed for digital trial manufacturing based on the digital twin of the manufacturing system and the design scheme of the new product. An ultrahigh-fidelity digital prototype can be obtained from digital trial manufacturing for digital validation. The new product validation is executed on the digital prototype to test its performance. The digital validation results can be used to improve the design scheme of the new product and boost the corresponding manufacturing processes. In addition, the core characteristics and key technologies of rapid product development based on digital twin are discussed. Finally, a case study is presented to implement the proposed framework and to show the effectiveness of accelerating product development.

Using Analytical Platform Technologies to Support Accelerated Product Development-Concept Review and Case Study.

The number of products being developed for serious conditions that are eligible for expedited programs has been increasing in recent years. This article presents an industry perspective on how to reduce analytical life cycle steps when using analytical platform technologies (APT) in support of accelerated biological product development. Strategies for life cycle steps for APT methods are conceptually reviewed within the framework of supporting chemistry, manufacturing, and control (CMC) development acceleration. Reduced method qualification, transfer, and validation studies could be performed, provided that the initially validated test method remains unchanged. A detailed case study is used to illustrate considerations for the initial method validation and subsequent APT verification studies. Considerations for APT implementation are discussed and suggestions are provided for the submission of APT information in regulatory filings.

Should Firms Accelerate Product Development During Market Emergence?

This study challenges the notion that speeding products to market is beneficial by examining conditions under which accelerating product development as a strategy can be suboptimal. I argue that the extent to which acceleration enhances market evaluation is contingent upon (a) whether the product aligns with or deviates from market convention, and (b) the average market intensity on product development; both contingencies should be especially salient for new entrants during market emergence. Using a uniquely detailed dataset on the EnergyStar program of LED lightbulbs from 2010 to 2017, I find that although incumbent firms benefit from frequent product adaptation, new entrants may suffer from adopting such a strategy. To avoid being discounted by market audience, new entrants should (a) decelerate when introducing unconventional products, and (b) resist the temptation to rush when peer pressure for speed is strong. By presenting an alternative view on the implication of product development frequency, this study enriches understanding on winning strategies for firms competing in nascent market.

Structural Response Prediction of Thin-Walled Additively Manufactured Parts Considering Orthotropy, Thickness Dependency and Scatter.

Besides the design freedom offered by additive manufacturing, another asset lies within its potential to accelerate product development processes by rapid fabrication of functional prototypes. The premise to fully exploit this benefit for lightweight design is the accurate structural response prediction prior to part production. However, the peculiar material behavior, characterized by anisotropy, thickness dependency and scatter, still constitutes a major challenge. Hence, a modeling approach for finite element analysis that accounts for this inhomogeneous behavior is developed by example of laser-sintered short-fiber-reinforced polyamide 12. Orthotropic and thickness-dependent Young’s moduli and Poisson’s ratios were determined via quasi-static tensile tests. Thereof, material models were generated and implemented in a property mapping routine for finite element models. Additionally, a framework for stochastic finite element analysis was set up for the consideration of scatter in material properties. For validation, thin-walled parts on sub-component level were fabricated and tested in quasi-static three-point bending experiments. Elastic parameters showed considerable anisotropy, thickness dependency and scatter. A comparison of the predicted forces with experimentally evaluated reaction forces disclosed substantially improved accuracy when utilizing the novel inhomogeneous approach instead of conventional homogeneous approaches. Furthermore, the variability observed in the structural response of loaded parts could be reproduced by the stochastic simulations.

Design of Aircraft for Best Value

The effect of aircraft performance, quantity, and schedule on aircraft cost has been analyzed in order to create a method for making informed decisions about aircraft optimization. Operations analysis and parametric costing were used to compare the operational value of increased aircraft performance to the cost of increasing aircraft performance. In addition to the direct cost of performance, this analysis includes the hidden costs to the manufacturer and user resulting from a reduction in aircraft quantities delivered due to incremental increases in their unit cost. It is shown that accelerating product development in order to deliver an 80% solution provides the best value to the user and the greatest return to the manufacturer. It is also shown how this analysis can be used to develop a proposal strategy based on a price to win.