Efficient Product Development Research Articles

Fostering product development efficiency through cross-functional team leadership: Insights and strategies from industry experts

This study investigates the impact of leadership models on the efficiency and innovation outcomes of cross-functional teams (CFTs) in product development contexts. With the aim of identifying effective leadership practices, the research focuses on how transformational, shared, and situational leadership models influence team dynamics, communication, collaboration, and ultimately, product development efficiency. Employing a systematic literature review combined with content analysis, the study analyzes peer-reviewed articles and scholarly books published from 2013 to 2024. This methodology facilitates a comprehensive examination of current leadership models and their applicability to CFTs. Key findings reveal that transformational leadership inspires and motivates team members, shared leadership enhances ownership and accountability, and situational leadership adapts to the dynamic needs of product development projects. These leadership models significantly contribute to fostering an environment conducive to open communication and collaboration, driving innovation and efficiency in product development processes. Based on these insights, strategic recommendations for industry leaders include adopting flexible leadership styles, promoting open communication, encouraging shared leadership, and investing in leadership development. These strategies are pivotal for leveraging the diverse expertise within CFTs and enhancing product development outcomes. The study underscores the critical role of leadership in maximizing the potential of CFTs for innovation and efficiency. It highlights the need for leaders to adapt their strategies to the unique challenges of managing diverse teams, offering a path forward for effective team leadership in product development. Keywords: Cross-functional teams, Leadership models, Product development efficiency, Innovation outcomes.

Simulating Elastoplastic and Anisotropic Behavior in Thermoplastic Additively Manufactured Components: An Application-Oriented Modeling Approach.

This paper presents a comprehensive approach aimed at developing a coupled process-structure simulation that integrates anisotropic and elastoplastic material behavior for plastic components manufactured through Fused Filament Fabrication (FFF) 3D printing. The simulation incorporates material orientation considerations, linking the process simulation with structural simulation. Subsequently, stress and strain values from the simulations are compared with the test results. Moreover, the fracture behavior of components manufactured in this way is also taken into account in relation to material orientation. The executed simulations have yielded successful outcomes, affirming the efficacy of the anisotropic and elastoplastic simulation across all strand orientations. Special attention is paid to the application of the method. Here, the simulation method introduced in this contribution with the approaches for describing the material behavior under mechanical load can be used in the future in the dimensioning of FFF manufactured plastic components to predict the deformation behavior and failure, especially under consideration of a well economic and efficient virtual product development.

Aligning restaurants and artificial intelligence computing of food delivery service with product development

PurposeThis study aims to analyze how restaurants' collaboration with mobile food delivery applications (MFDAs) affects product development efficiency and argues that technological capabilities moderate relational ties impact the joint decision-making and development efficiency of restaurant products.Design/methodology/approachA product development efficiency model was formulated using a resource-based view and real options theory. In all, 472 samples were collected from restaurants collaborating with MFDAs, and partial least squares structural equation modeling was applied to the proposed model.FindingsThe findings of this study indicate three factors are critical to the product development efficiency between restaurants and MFDAs; restaurants must develop a strong connection with the latter to ensure meals are consistently served promptly. Developers of MFDAs should use artificial intelligence analysis, such as order records of different genders and ages or various consumption attributes, to collaborate with restaurants.Originality/valueTo the best of the authors’ knowledge, this study is one of the few that considers the role of MFDAs as a product strategy for restaurant operations, and the factors the authors found can enhance restaurants’ product development efficiency. Second, as strategic artificial intelligence adaptation changes, collaborating firms and restaurants use such applications for product development to help consumers identify products.

Optimization of a commercial vehicle powertrain mounting system based on new rubber mounts

In order to improve the vibration isolation, environmental adaptability and development efficiency of rubber mounts, a novel rubber mount with adjustable parameters such as stiffness, support height and limit distance was proposed, and its structural composition and working principle were described. And then, a commercial vehicle was taken as the research object to conduct the calculation of mounts stiffness by employing the energy decoupling method and genetic algorithm. On the basis of the influence of cone angle, thickness and height on the ratio of axial-radial stiffness, the detailed structural design of the mounts was carried out, and the relationship between the preloading displacement and axial-radial stiffness was studied by the method of theoretical calculation and test, which made the process of the stiffness adjustment more specific and accurate. Finally, the vibration isolation performance test of the Powertrain Mounting System (PMS) before and after stiffness adjustment was completed. Results show that the adjusted PMS indicates better vibration isolation performance at idle speed and slow acceleration in place, and the new mounts can effectively improve the vibration performance of vehicle, environmental adaptability of mounts and product development efficiency.

Do consumer perceptions of a product category relate to their sensory properties? A case study on energy bars with consumers of high and low familiarity

AbstractGoods in a market are typically presented in discrete categories so that consumers can easily find their way among the myriad of products available. However, sub‐categorical distinctions are often less clear. This study aimed to explore how consumer perceptions of products within a category relate to their sensory properties. By analyzing how consumers sorted energy bars and the vocabulary used to describe the resulting clusters, we found that consumers generally agree on how they perceive bars high in protein. However, energy bar consumers with high familiarity demonstrated greater levels of differentiation between clusters compared to energy bar consumers with low familiarity. They were also more consensual in their sorting. Furthermore, sensory properties were found to play a larger role in determining product clusters for consumers with high familiarity than with low familiarity. These findings shed light on the factors influencing consumer perception of energy bars. Additionally, this approach offers a simple way to investigate consumer perception of a product category and could be useful to marketers and product developers who wish to refine their offerings to better meet consumer expectations.Practical ApplicationsThe method for category appraisal described in this paper emphasizes consumer perception of products and factors, such as sensory properties and nutrition facts, that influence these perceptions. It departs from traditional approaches that focus on individual product descriptions and instead focuses on product groupings perceived by consumers. This approach allows for deeper insights to be obtained about product categories as a whole, which can inform effective marketing strategies and efficient product development.

Competitive Advantagein Increasing Income in Indonesia Small and Medium-Sized Businesses Increasing

Purpose: This research aims to look at important factors in increasing competitive advantage. SMEs need a competitive advantage to compete in the era of the industrial revolution 4.0, where industries have touched cyberspace, resulting in human, machine, and data connectivity, all of which are vying to survive and be the best.
 
 Theoretical framework: The goal of strategic thinking and the primary focus in achieving business success is competitive advantage (Hunitie, 2018). According to (Greenhow & Galvin, 2020), social media is a collection of mobile or web-based technologies that allow people to interact with and share various types of content. Innovation is a level of change in the development of new products and the introduction of new products into the market (Habib, Kristiansen, Rana, & Ritala, 2020). Market orientation, in general, refers to the fundamental orientation that governs a company's relationship with its market, and more specifically with its customers (Bamfo & Kraa, 2019).
 
 Method:This study uses an explanatory research approach to examine the influence of social media, innovation, and market orientation on competitive advantage. The population of this research is SMEs in East Java Province, Indonesia. Quantitative data from SMEs was obtained from 294 respondents who provided responses in the form of a questionnaire. By using Smart PLS, social media, innovation and market orientation that can help SMEs gain a competitive advantage.
 
 Result and conclusion: The results of this research are that SMEs must always utilize social media to carry out promotions in an effort to gain an identity of competitive advantage so that they are easily recognized by the market, then carry out product innovation so that the products offered are not easily imitated by competitors. so that it becomes a competitive advantage, and is market oriented to maintain competitive advantage for business sustainability. Thus, it can be concluded that social media, innovation and market orientation can increase the competitive advantage of SMEs.
 
 Implication of research: SMEs must have management capabilities and company information technology through social media to promote in an effort to gain an identity of competitive advantage so that they are easily recognized by the market. Innovations carried out by SME entrepreneurs in effective and efficient product development are able to produce products that are difficult for competitors to imitate, thus creating a competitive advantage. It is important for SME entrepreneurs to understand market orientation so they are able to understand consumer needs and competitors' abilities in order to gain a competitive advantage in winning business competition.
 
 Originality/value: The novelty of this research is the formation of a theoretical model of social media, innovation and market orientation in increasing the competitive advantage of SMEs. SME entrepreneurs must have management and company information technology capabilities through social media, innovate in effective and efficient product development, and understand market orientation in order to gain a competitive advantage in winning business competition.

Analyzing The Mediating Role of Green Creativity Climate on Green Product Performance: Evidence Form Industrial Manufacturing Sector of Pakistan

This paper aimed to explore the effects of EIP dimensions' success factors, in particular, environmental management, climate creativity, creative sustainability, and the environmental effects of products. innovation on organizational success of Pakistani manufacturers at different levels of execution, including environmental performance, economic performance, and operational performance. It also highlights the need for further research on EIP practices in developing nations such as Pakistan. Using a Convenient sample technique, survey questionnaires were used to gather data for this study, from the management of 185 companies in Pakistan. PLS-SEM was used to examine data related to the intended target market. which was managerial staff members (business experts & executives) from private business firms. Our results demonstrate that EIP, with its creative climate and green technology, has a favorable effect on the performance of green product development. We also learn that consumers with low standards for the environment and little desire to purchase goods can be found in manufacturing enterprises. According to our research, which supports the organizational innovation theory, raw art is the most crucial component of an organization that encourages the creation of a green manufacturing product. One finding from the research is that the presence of a green creative atmosphere is a crucial component in explaining the beneficial effects of EIP on the efficiency of green product development. Second, the EIP encourages the growth of organizational qualities in addition to raw material development. but additionally offers the advantages of organizational performance. Researchers may be able to gain a better understanding of the intermediary mechanisms linking green creativity, raw product innovation, and EIP with the use of these studies.

The strategic role of R&D outsourcing practices and partners in the relationship between product modularization and new product development efficiency

PurposeThe study aims to explore the conditional relationships between product modularization and new product development (NPD) efficiency. It is postulated that R&D outsourcing plays an important mediating role. Furthermore, the level of competency trust is considered an essential factor in moderating the indirect effect of product modularization on NPD efficiency via R&D outsourcing practices.Design/methodology/approachDrawing on transaction cost economics theory, this study suggests a moderated mediation model that addresses how product modularization effectively promotes NPD efficiency via outsourcing practices. The hierarchical regression and PROCESS macro model were conducted to test the hypotheses based on survey data from 273 manufacturing firms in China.FindingsProduct modularization enhances NPD efficiency directly and indirectly through the external collaboration of R&D outsourcing. Furthermore, the role of product modularization in R&D outsourcing practices is more effective when the competency trust in R&D outsourcing partners is high.Originality/valueBy showing the critical role of external collaboration, this study provides valuable insights into how manufacturing firms utilize product modularization to achieve desired NPD performance more effectively.

Data-driven implicit design preference prediction model for product concept evaluation via BP neural network and EEG

Customer preference-involved product concept evaluation is a vital stage for developing new products. One of the key factors in this stage is to mine the potential relationships between customers’ needs and technical requirements. In most new product development (NPD), design characteristics (DCs) are employed as performance indicators to describe the technical requirements of a scheme. Previous studies have focused on evaluating the degree to which a scheme meets the performance value of DCs, disregarding the relationship between DCs and potential user preferences. This oversight leads to an inability to accurately predict customer satisfaction with the candidate schemes based on their preferences. Previous research, which was aimed at ensuring the preference value of schemes by utilizing mapping data between design preference (DP) and DCs, overlooked users' psychological states and thus failed to accurately capture their cognitive preferences for the schemes. To address these issues, an electroencephalogram (EEG) data-driven, implicit DP prediction approach is proposed. The method characterizes the implicit cognitive relationship between DP and DCs by mining EEG data and utilizes a back propagation (BP) neural network to predict DP. First, a user's DP word pairs were constructed based on the approach of statistical analysis, and the best-worst method (BWM) was introduced to obtain the importance of DCs. Second, an experiment was designed based on the extracted preference word pairs to collect EEG data that reflect a user's DC preference, record the user's stimulation state toward the DCs, and label their DP based on the segmentation results of preference evaluation. Third, a BP neural network was employed to construct a preference prediction model for DCs, and the reliability of the proposed preference prediction model was validated by using the forklift design example. The prediction results further exhibited the potential association between user preferences and DCs that can be acquired by EEG data mining. The results also provide support for designers to promptly acquire design concepts that satisfy user requirements (URs), thereby enhancing the efficiency and quality of product development in a highly competitive market.

Enhanced Genetic and Imperialist Competitive Based Algorithms for Reducing Design Feedbacks in the Design Structure Matrix

Nowadays, finding an appropriate interrelated activities sequence in designing complex engineering products, leading to efficient product development, is known as a major concern for managers. Recently, a variety of efforts aim to help the design managers tackle this issue, and one of the most useful management tools among them is the sequencing analysis method in an activity-based design structure matrix (DSM). The sequencing analysis method is the process of reordering the DSM rows and columns to minimize the detrimental effects of feedback loops in the design process. Therefore, in this article, an enhanced imperialist competitive algorithm (ICA), an enhanced genetic algorithm (GA), and a hybrid ICA–GA method are presented to find an activity sequence in DSM with a minimum total feedback length, which is a proper criterion for diminishing the detrimental effects of the feedback loops. To this end, we have improved the ICA and GA methods utilizing two techniques: applying the operators dynamically and tuning the main parameters adaptively. Subsequently, some experiments are designed to evaluate the proposed methods’ performance in terms of the cost value, computational time, and convergence rate on a remote sensing satellite DSM as a case study and eight other DSMs. The performance results demonstrate the superiority of ICA over two other methods. Eventually, an exhaustive comparison with the four well-known methods involving Antares, efficient-simple GA, insertion-based heuristic, and insertion-based simulated annealing illustrates the superiority of the ICA in large-scale problems, yielding the best-known solution in a reasonable computational time.

Heteroprotein complex coacervation of ovalbumin and lysozyme: Phase behavior, microstructure and processing properties

Egg white protein is a complex network system formed by the aggregation and interaction of multiple proteins, in which two oppositely charged proteins can induce the formation of heteroprotein complex coacervate (HPCC). This investigation aims to probe the complexation between ovalbumin (OVA) and lysozyme (LYS) via the heteroproteins phase diagram model, exploring the relationship between differential processing properties and complex state, protein molecular structure and intermolecular interactions. Results showed that the characteristic pH (pHc, pHɸ1, pHmax, pHɸ2) intensely relied on the protein ratios. Consequences of ζ-potential and the phase diagram manifested that OVA-LYS complex formation was predominantly triggered by electrostatic interactions. With the increasing OVA-LYS mixing ratio, the characteristic pH of the complex moved towards a higher pH value. By comparing the microphase structure of different phase regions induced by pH, we found that the protein structure unfolded at low pH, elevating the foaming and emulsifying capacity. Moreover, further increases in pH value brought on larger insoluble complex formation, which enhanced the foaming stability while decreased the emulsifying stability. Noteworthy, the coacervates obtained in the narrow range of pH 6.5–9.5 presented the strongest gel strength and highest water holding capacity, which was considered to be an efficacious way to regulate the gel properties of egg white protein. On the whole, the findings of this paper developed prominent insight for understanding the interaction between heteroproteins, which would lay a theoretical foundation for improving the quality and efficiency of functional egg powder and product development.

Bridging the Gap between Geometry and User Intent: Retrieval of CAD Models via Regions of Interest

CAD model retrieval is a key functionality for increasing the efficiency of product design and development. A major challenge for content-based retrieval solutions is to bridge the semantic gap between geometric information and design intent. Current retrieval solutions lack capabilities to tailor search results to user interpretation and application context. This work presents an interactive retrieval system on heterogeneous CAD model collections that leverages user-defined regions of interest (ROIs) to express design intent in an intuitive manner. Our proposed system uses self-supervised learning techniques to capture nuanced semantic shape relationships and employs non-exhaustive search techniques to perform large-scale partial shape matching in real-time. We report significant performance increases over global retrieval on three mechanical component datasets. We also outline the scalability of the approach to large datasets and multi-modal data.

Discussion on Key Control Points and Common Problems of Molecular Diagnostic Reagents in the Process of Design and Development

Design and development process of molecular diagnostic reagents is critical to quality management system of in vitro diagnostic reagent. Based on the technical characteristics of molecular diagnostic reagents, the study analyzed the concerned key control points and common problems in the process of design and development from the view of registration quality management system. It aimed at offering technical guidance on design and development process of molecular reagents and registration quality management system to enterprises, thus improving the product development efficiency, optimizing the quality management system, and increasing the efficiency and quality of registration and declaration.

Supporting product lifecycle collaboration and knowledge-related evaluation: an active-passive collaboration mechanism and fuzzy evaluation method

Collaboration is essential to improve the efficiency of product research and development (R&D), shorten the R&D cycle, and reduce the R&D costs in complex product lifecycle model management (CPLMM). However, disorganized processes and the unreliability of the result evaluation remain enormous challenges for efficient collaboration. This article proposes an active-passive collaboration mechanism to enable a regulated collaboration system, which can direct the self-organized collaboration of stakeholders. C-D-Petri Net is presented for the formal collaboration process modeling. The result evaluation in active-passive collaboration involves multi-source knowledge across disciplines and phases. To address the unreliable collaboration evaluation (Co-evaluation) caused by insufficient evaluation knowledge and weak correlation between expertise and evaluation task, the collaborative fuzzy comprehensive evaluation (CFCE) model is established to support Co-evaluation actions, and its core improvement lies in the definition and introduction of collaboration volume. Finally, a simulated aircraft horizontal tail control system is regarded as an engineering application case to demonstrate and verify the effectiveness of the proposed method.

Prediction of cutting forces in drilling of aluminum 6061-T6 alloy

Drilling is the most common machining operation and arguably the most crucial of the traditional machining processes. Cutting force predictions for every given set of cutting conditions are crucial for efficient product development. It has been hypothesized that the force produced during cutting is responsible for the majority of the issues seen in hole creating processes like drilling. Calculating forces accurately also aids in the development and assessment of cutting equipment and fixtures. The purpose of this article is to examine the effect of significant machining factors like thrust force and torque on the drilling operations of Aluminum 6061-T6 alloy. Theory and experiment will be compared with different types of drill bits. An average error of 5.81% was found in the Axial Force (N) and 0.85% was observed in Torque (N-cm). The error % of desired responses is found to be accepted.

A systematic review of knowledge management and new product development projects: Trends, issues, and challenges

This research aims to show that knowledge management is integral to business strategy and can lead to more efficient new product development in high-tech companies. Organizations have been increasingly focused on knowledge management methods as they have realized how important it is to manage knowledge to stay competitive in their marketplaces. Knowledge Management (KM) is responsible for a company's efficiency, effectiveness, and innovation. Project outcomes, individual outcomes, and organizational outcomes are linked to knowledge in New Product Development (NPD). More than 28,548 KM papers published in the previous 22 years were examined in this research using Scopus and Web of Science; the original sample was narrowed down to items that contributed to KM literature. The R Studio and VOS Viewer software executed the descriptive statistics and scientific mapping approaches using co-citation analysis. The descriptive analysis involved studying publishing patterns over time, the geographical localization of the contributing institutions, journals, the most prolific authors, the top-performing institutions, and the most-cited papers. Scholars and practitioners have been paying close attention to knowledge management and organizational performance in recent years. Once implemented, the integrated approach may significantly influence organizational processes and performance. This study examines both KM ideas in NDP initiatives. Several intriguing discoveries are presented, with extensive explanations of their future direction, a conceptual framework for the study, and practice based on the literature.

Construction of nano slow-release systems for antibacterial active substances and its applications: A comprehensive review.

At present, nano-carrier materials with antibacterial activity are of great significance. Due to the widespread resistance of many pathogenic microorganisms, it has seriously threatened human health. The natural antimicrobial substances extracted from fruits and vegetables can significantly improve their stability combined with nano-carrier materials. The resistance of pathogenic microorganisms will be substantially reduced, greatly enhancing the effect of active antimicrobial substances. Nanotechnology has excellent research prospects in the food industry, antibacterial preservation, food additives, food packaging, and other fields. This paper introduces nano-carrier materials and preparation techniques for loading and encapsulating active antibacterial substances in detail by constructing a nano-release system for active antibacterial substances. The antibacterial effect can be achieved by protecting them from adverse external conditions and destroying the membrane of pathogenic microorganisms. The mechanism of the slow release of the bacteriostatic active substance is also described. The mechanism of carrier loading and release is mainly through non-covalent forces between the bacteriostatic active substance and the carrier material, such as hydrogen bonding, π-π stacking, van der Waals forces, electrostatic interactions, etc., as well as the loading and adsorption of the bacteriostatic active substance by the chemical assembly. Finally, its wide application in food and medicine is introduced. It is hoped to provide a theoretical basis and technical support for the efficient utilization and product development of bacteriostatic active substances.

The Relationship between Structure and Performance of Different Polyimides Based on Molecular Simulations.

A polyimide (PI) molecular model was successfully constructed to compare the performance of PIs with different structures. In detail, the structure of the cross-linked PI resin, the prepolymer melt viscosity, and the glass-transition temperature (Tg) were investigated using molecular simulations. The results indicate that benzene ring and polyene-type cross-linked structures dominate the properties of the PIs. Moreover, the prepolymer melt viscosity simulations show that the 6FDA-APB and the ODPA-APB systems have a low viscosity. The results for the Tg and the distribution dihedral angle reveal that the key factor affecting bond flexibility may be the formation of a new dihedral angle after cross-linking, which affects the Tg. The above results provide an important reference for the design of PIs and have important value from the perspective of improving the efficiency of new product development.

A contradiction solving method for complex product conceptual design based on deep learning and technological evolution patterns

Contradictions caused by the various design constraints present increasing challenges to efficiency and innovation in product development. TRIZ provides Inventive Principles (IPs) and Contradiction Matrix that are the most frequently applied in conflict resolution. However, the high-level abstraction and subjective selection of IPs inhibit achieving the transformation process from paradoxical states to physical structures. To fill this gap, a contradiction solving method by integrating deep learning and technological evolution patterns for product conceptual design is proposed, which illustrates the mechanism of contradiction transition from the perspective of system evolution and supplies a systematic and model-based design approach. Firstly, generic engineering parameters are extracted to define the underlying contradictions transformed from critical defects which are found out through function modeling and root-conflict analysis. Then, a fully-connected deep neural network with excellent performance is developed to uncover the non-linear relationships between engineering parameters and evolution patterns. Finally, an evolution tree based on the predicted patterns is constructed to visualize transformation potentials of a technical system and help designers generate innovative specific solutions. In addition, a case study concerning design conflict resolution for beat-up system of three-dimensional tubular weaving machine is used to validate the adaptability and reliability of the proposed approach.

Home Automation using Android

Automation has become the key for smart homes, Implementation of such a system leads to energy conservation and also provides the user with a comfortable and convenient way to control their home appliances. Automation can also be employed to help disabled people with their daily tasks. This paper presents such a system which uses sensors to automate our home appliances. A connection to this system can be established via Bluetooth using applications developed with the Android operating system. Automation was done to reduce industrial accidents as and when people are get exposed to dangerous situations by the help of automation, we can have more effective and efficient product development, With the help of the automation, we can reduce manual labor and reduce the accidents associated with the high voltage devices. This project was developed to create simple but reliable and in expensive home automation model with the help of mobile phone. As the mobile phone has become irreplaceable, the mobile phone is used to control the appliances. With the help of mobile phone, home automation is done easily. A complete but a simple automation model using mobile phone is done in this project.