Product Development Life Cycle Research Articles

Distributed Asymmetric Virtual Reality in Industrial Context: Enhancing the Collaboration of Geographically Dispersed Teams in the Pipeline of Maintenance Method Development and Technical Documentation Creation

Virtual Reality (VR) is a critical emerging technology in industrial contexts, as it facilitates collaboration and supports the product development lifecycle. However, its broad adoption is constrained by complex and high-cost integration. The use of VR among devices with various immersion and control levels may solve this obstacle, and increase the scalability of VR technologies. This article presents a case study on applying asymmetry between the COVE-VR platform and Microsoft Teams to enable distributed collaboration of multinational departments and enhance the maintenance method and documentation creation processes. Overall, five remote collaborative sessions were held with 20 experts from four countries. Our findings suggest that asymmetry between head-mounted display and Teams users enhances the quality of communication among geographically dispersed teams and their spatial understanding, which positively influences knowledge transfer and efficiency of industrial processes. Based on qualitative evaluation of the asymmetric VR setup, we further suggest a list of guidelines on how to enhance the collaboration efficiency for low-cost distributed asymmetric VR from three perspectives: organization, collaboration and technology.

Intelligent Systems Using Sensors and/or Machine Learning to Mitigate Wildlife-Vehicle Collisions: A Review, Challenges, and New Perspectives.

Worldwide, the persistent trend of human and animal life losses, as well as damage to properties due to wildlife–vehicle collisions (WVCs) remains a significant source of concerns for a broad range of stakeholders. To mitigate their occurrences and impact, many approaches are being adopted, with varying successes. Because of their increased versatility and increasing efficiency, Artificial Intelligence-based methods have been experiencing a significant level of adoption. The present work extensively reviews the literature on intelligent systems incorporating sensor technologies and/or machine learning methods to mitigate WVCs. Included in our review is an investigation of key factors contributing to human–wildlife conflicts, as well as a discussion of dominant state-of-the-art datasets used in the mitigation of WVCs. Our study combines a systematic review with bibliometric analysis. We find that most animal detection systems (excluding autonomous vehicles) are relying neither on state-of-the-art datasets nor on recent breakthrough machine learning approaches. We, therefore, argue that the use of the latest datasets and machine learning techniques will minimize false detection and improve model performance. In addition, the present work covers a comprehensive list of associated challenges ranging from failure to detect hotspot areas to limitations in training datasets. Future research directions identified include the design and development of algorithms for real-time animal detection systems. The latter provides a rationale for the applicability of our proposed solutions, for which we designed a continuous product development lifecycle to determine their feasibility.

Editorial and News

Editorial and News

A Comprehensive IT Infrastructure for an Enzymatic Product Development in a Digitalized Biotechnological Laboratory.

Typical product development in biotechnological laboratories is a distributed and versatile process. Today's biotechnological laboratory devices are usually equipped with multiple sensors and a variety of interfaces. The existing software for biotechnological research and development is often specialized on specific tasks and thus generates task-specific information. Scientific personnel is confronted with an abundance of information from a variety of sources. Hence a comprehensive software backbone that structures the developmental process and maintains data from various sources is missing. Thus, it is not possible to maintain data access, documentation, reporting, availability, and proper data exchange. This chapter envisions a comprehensive digital infrastructure handling the data throughout an enzymatic product development process in a laboratory. The platform integrates a variety of software products, databases, and devices to make all product development life cycle (PDLC) data available and accessible to the scientific staff.

A theoretical framework for identifying appropriate marketing approaches across the product development life cycle for biomedical science SMEs

PurposeAn investigation of the marketing approaches for biomedical science small- and medium-sized enterprises (SMEs) and organisations in the United Kingdom (UK) was carried out; the research question is as follows: Should the marketing approaches for biomedical science SMEs change as their product or service moves along the development life cycle?Design/methodology/approachAn online questionnaire was used, which petitioned biomedical science SMEs and organisations in the UK to investigate the marketing tactics or approaches used for the different products and services they offered; the results were analysed by comparing the results to recognised marketing approaches in the literature and by mapping those approaches against the established technology readiness levels (TRLs).FindingsA direct relationship was seen between the status of a product or service in relation to its development life cycle, and therefore the relevant TRL of the product and service, and the appropriate marketing approach for that product or service.Originality/valueThis paper offers a contribution to the literature, in which a theoretical framework is proposed for determining the appropriate marketing approach for biomedical science SMEs by understanding the maturity of the products offered by a company using the established TRL. The theoretical framework maps the TRL against known marketing approaches; this framework should be used as a guide for biomedical science SMEs as a tool to refine and evolve their overall marketing approach as the product portfolio matures along the TRL.

Traceable and Intelligent Supply Chain based on Blockchain and Artificial Intelligence

Smart manufacturing focuses on maximizing the capabilities to increase multiple objectives, like cost, delivery, and quality, in manufacturing enterprises. This requires implementing product development lifecycle, production system lifecycle, and business cycle for supply chain management. In short, a considerable amount of data is generated in a given manufacturing enterprise. Likewise, progress has been made to adopt blockchain in financial industries, but the adoption is slow in non-financial sectors. The article elaborates a methodology for the realization of a traceable and intelligent supply chain. First, the methodology elaborates on the realization of traceability of enterprise entities, which are an integral part of the supply chain. In this case, each participating stakeholder of the supply chain is required internally to realize a smart manufacturing system with an extension to write critical control data to the blockchain (i.e., a subset of process data). Artificial Intelligence (AI) is being adopted in most industries. A supply chain stakeholder has access to its data and can employ AI to derive new insights. The data available with the stakeholder provides a narrow context. With blockchain, all the stakeholders have access to the data from other stakeholders. Subsequently, the insights derived by a stakeholder will be more meaningful. This will assist in realizing an intelligent supply chain.

Leadership approach towards Agile, Waterfall and Iterative implementation of the software development products

The automotive industry is one of the most dynamic markets, gathering around many different sectors from material extractions to robotics and cloud computing. The current research analyses the influences and particularities of leadership and identifies the challenges and advantages of the two principal methodologies in software development projects within the automotive industry, Agile and Waterfall. Some aspects of reducing methodological disadvantages are suggested and presented. The aim is to arrive at a sustainable solution that can ensure the delivery of reliable and flexible software products. The impact of these methodologies on the quality standards and project documentation is analyzed, which is a vital part of automotive software development. By influencing the product development lifecycle, there is an opportunity to develop a structured framework that can be adopted to build software products in a more flexible and agile way.

Survey on set‐based design (SBD) quantitative methods

AbstractProduct development efforts now more than ever are in need of methodologies that can address the challenges of increased system complexities, shortening time to market, increased demands in mass customization, market instabilities, geographical barriers, improved innovation, and adaptability to emerging technologies. To address these challenges most companies will need to make key decisions early in the product development life‐cycle. In this early phase there are high levels of information uncertainty and information ambiguity. Under these circumstances many companies will converge too early to a point design (Point Based Design—PBD) which will lead to increased cost and schedule delays due to reworking the design later in the product development life cycle. To overcome these challenges many researchers have proposed the Set‐Based Design (SBD) methodology. However, there has been limited guidance on how to define, reason, and narrow sets while improving the level of abstraction of the design. To address such concerns, a literature review was conducted. The contributions of this research include: (1) aggregated literature from over 100 sources on quantitative methods (QM) that has not been considered SBD but does support set‐based thinking, (2) consolidated body of knowledge on QM to help industrial practitioners implement SBD, (3) ​defined gaps and opportunities for future research, and (4) defined strengths and limitations of QM and techniques to define, reason and narrow sets.

Opportunities and challenges for applying model-informed drug development approaches to gene therapies.

As part of the US Food and Drug Administration (FDA)’s Prescription Drug User Fee Act (PDUFA) VI commitments, the Center for Biologics Evaluation and Research (CBER) and Center for Drug Evaluation and Research (CDER) are conducting a model‐informed drug development (MIDD) pilot program. Sponsor(s) who apply and are selected will be granted meetings that aim to facilitate the application of MIDD approaches throughout the product development lifecycle and the regulatory process. Due to their complex mechanisms of action and limited clinical experience, cell and gene therapies have the potential to benefit from the application of MIDD methods, which may facilitate their safety and efficacy evaluations. Leveraging data that are generated from all stages of drug development into appropriate modeling and simulation techniques that inform decisions remains challenging. Additional discussions regarding the application of quantitative modeling approaches to drug development decisions, such as through the MIDD pilot program, may be crucial for both the sponsor(s) and regulatory review teams. Here, we share some perspectives on the opportunities and challenges for utilizing MIDD approaches for product review, which we hope will encourage investigators to publish their experiences and application of MIDD in gene therapy product development.

Managing manufacturing data and information in product lifecycle management systems considering changes and revisions

Manufacturing data and information are produced and used during the lifecycle of product development. Product lifecycle management (PLM) systems provide a suitable platform for managing them. For a...

Life Cycles of Firm Disclosures

We examine the link between product life cycles and disclosure using a novel 4-stage text-based life cycle model and report two main results. First, the standard link between competition and less disclosure holds primarily in the early product development life cycle stage, when product strategies are not fully public. Second, firms with mature-stage products disclose more, consistent with lowering search costs for an outward-focused investment strategy seeking synergistic partners. These results obtain across a wide array of disclosure policies and in a quasi natural experiment. Our interpretations are further supported by tests examining not only the sender of disclosure, but also the intended receiver.

Sustainable Solutions for Wearable Technologies: Mapping the Product Development Life Cycle

Wearable technologies involve the integration of technology into clothing or accessories to bring new functionalities for people on the move. Many examples of wearables are emerging, from simple fitness tracking watches to electronics deeply embedded into garments for multi-touch sensing and control for personal music players. Without careful development, wearables can have a negative impact on the environment due to increased production of electronic components, increased e-waste from abandoned devices, and increased energy usage. We examine environmental sustainability issues through a review of recent research and cases across three broad areas including the fashion industry, information and communications technology (ICT), and wearable technologies. In the analysis, we examine stages in the product life cycle and identify the unique issues for each sector, including the extraction of materials, production process, distribution of products, use, and disposal of products that have reached the end of their life. The findings are gathered as implications for design so that researchers, educators, designers, developers, and product managers will gain an overview of the issues related to environmental sustainability. Related examples of products and prototypes are provided to enable informed choices during the design and development of wearables that are more environmentally sustainable.

Development and Application of a Patient Group Engagement Prioritization Tool for Use in Medical Product Development

IntroductionPatient group engagement is increasingly used to inform the design, conduct, and dissemination of clinical trials and other medical research activities. However, the priorities of industry sponsors and patient groups differ, and there is currently no framework to help these groups identify mutually beneficial engagement activities.MethodsWe conducted 28 qualitative, semi-structured interviews with representatives from research sponsor organizations (n = 14) and patient groups (n = 14) to determine: (1) how representatives define benefits and investments of patient group engagement in medical product development, and (2) to refine a list of 31 predefined patient group engagement activities.ResultsPatient group and sponsor representatives described similar benefits: engagement activities can enhance the quality and efficiency of clinical trials by improving patient recruitment and retention, reduce costs, and help trials meet expectations of regulators and payers. All representatives indicated that investments include both dedicated staff time and expertise, and financial resources. Factors to consider when evaluating benefits and investments were also identified as were suggestions for clarifying the list of engagement activities.DiscussionUsing these findings, we refined the 31 engagement activities to 24 unique activities across the medical product development lifecycle. We also developed a web-based prioritization tool (https://prioritizationtool.ctti-clinicaltrials.org/) to help clinical research sponsors and patient groups identify high-priority engagement activities. Use of this tool can help sponsors and patient groups identify the engagement activities that they believe will provide the most benefit for the least investment and may lead to more meaningful and mutually beneficial partnerships in medical product development.

Foundations of information governance for smart manufacturing.

The manufacturing systems of the future will be even more dependent on data than they are today. More and more data and information are being collected and communicated throughout product development lifecycles and across manufacturing value chains. To enable smarter manufacturing operations, new equipment often includes built-in data collection capabilities. Older equipment can be retrofitted inexpensively with sensors to collect a wide variety of data. Many manufacturers are in a quandary as to what to do with increasing quantities of data. Much hype currently surrounds the use of AI to process large data sets, but manufacturers struggle to understand how AI can be applied to improve manufacturing system performance. The gap lies in the lack of good information governance practices for manufacturing. This paper defines information governance in the manufacturing context as the set of principles that allow for consistent, repeatable, and trustworthy processing and use of data. The paper identifies three foundations for good information governance that are needed in the manufacturing environment-data quality, semantic context, and system context-and reviews the surrounding and evolving body of work. The work includes a broad base of standard methods that combines to create reusable information from raw data formats. An example from an additive manufacturing case study is used to show how those detailed specifications create the governance needed to build trust in the systems.

Abstract IA16: Accelerating innovation for children with cancer in the new regulatory environment

Abstract Over the last 20 years, several pieces of regulation have been launched, in the US and in Europe, to mandate and incentivize the development of safe and effective medicines for children. It has been a success in several pediatric specialties such as rheumatology, infection diseases, cardiovascular diseases, allergy, and several rare pediatric diseases. In oncology, the landscape of pediatric drug development has significantly changed, but very few new anticancer medicines have been approved for the treatment of pediatric malignancies over the last 10 years as compared to the high number of anticancer drugs approved for the treatment of cancer in adults: dinutuximab for neuroblastoma, blinatumomab and tisagenlecleucel for acute lymphoblastic leukemia, and larotrectinib for NTRK positive malignancies. So far, the regulations mandated the pediatric development of any drug if the indicated disease in adults occurred in children. If not, a waiver was issued and the company did not have to study the drug in children. In oncology, malignancies in children and in adults are different, but the same drugs are used to treat both, and often the same biologic alterations (targets) are found in both adult and pediatric malignancies. Too many oncology drugs have been waived. In addition, the pediatric trials of oncology products as part of Pediatric Investigation Plans and Pediatric Study Plans started late in the life cycle of product development and often close to or after the marketing authorization. There is a crucial need to improve and accelerate new drug development for children and adolescents with cancer. The goal is to drive pediatric oncology drug developments through science (using biology, preclinical evaluation, and precision medicine), to better meet patients’ unmet medical needs and to facilitate prioritization among all compounds in development. The FDA Race for Children Act is setting a new regulatory environment that will improve the situation by asking pediatric development of oncology products if their target is “directed at a molecular target that the Secretary determines to be substantially relevant to the growth or progression of a pediatric cancer.” In addition, over the last 5 years, the value of having all stakeholders, i.e. academia, parents, industry and regulators, working together has been demonstrated by ACCELERATE, the international multistakeholder platform (www.accelerate-platform.org). Accelerating innovation for pediatric cancers is urgently needed and feasible in the new regulatory environment and requires international cooperation of all stakeholders. Citation Format: Gilles Vassal. Accelerating innovation for children with cancer in the new regulatory environment [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr IA16.

Set‐based design: The state‐of‐practice and research opportunities

AbstractIncreasing system complexity has provided the impetus to develop new and novel systems engineering methodologies. One of these methodologies is set‐based design (SBD), a concurrent design methodology well suited for complex systems subject to significant uncertainty. Since the 1990s, numerous private, public, and defense sector design programs have successfully implemented SBD. However, concerns regarding SBD's complexity, tendency toward qualitative methods, and lack of quantitative tools have limited its use. To address these issues, our research surveys 122 refereed journal articles and conference papers to assess SBD's state‐of‐practice and identify relevant research opportunities. To accomplish these tasks, we perform a structured literature review to identify and assess relevant and influential research. We found that SBD's state‐of‐practice relies heavily upon decision and tradespace analysis with increasing emphasis on uncertainty modeling and MBSE. We found that the majority of SBD research consists of quantitative methodologies focusing on component and small system applications. We also found that complex system applications used mostly qualitative methodologies. We identify SBD research opportunities for requirements development, MBSE, uncertainty modeling, multiresolution modeling, adversarial analysis, and program management. Finally, we recommend the development of a comprehensive SBD methodology and toolkit, suited for complex system design across all stages of the product development life cycle.

Application of tractor virtual test technology in product innovation design

As a necessary link for product development and evaluation, tractor testing covers new technologies in multidisciplinary fields and plays an important role in the research and development of product life cycle. This study discusses the research status of tractor test and evaluation technology and analyzes the new technology associated with the test and evaluation technology. Aiming at the problem of poor reusability, poor interoperability and weak expansion of the current tractor virtual test model, a virtual tractor-based test technology based on the architecture was proposed. The middleware technology, test data management technology, modeling technology and test environment construction technology in the tractor virtual test system were analyzed. Taking the tractor power shift transmission as an example, the application of the architecture-based virtual test system was verified, which pointed out the direction for the design verification of tractor innovative products.

Checkpoints in New Product Development

Outsourcing the development of new products requires firms to establish strategies to monitor and control progress. We explore the value of establishing checkpoints within the product development lifecycle and provide a basis for determining the most appropriate point at which to review the progress of a development project. We find that establishing checkpoints reduces risk and allows firms to adjust their revenue-sharing ratio according to the progress of the project. We determine that the success of outsourcing is affected by the feasibility of the project and the level of effort and capabilities of the agent.

Explicitly semantic representation of pattern and combined geometrical specification

AbstractModel‐based definition (MBD) containing all product and manufacturing information (PMI) has become the data source of future product development because of its incomparable advantages over traditional two‐dimensional drawings. In the whole life cycle of product development, it is an urgent problem to realize the sharing of geometric tolerance specification information of PMI among different CAx (CAD, CAE, CAM, etc.) and the automatic interpretation of its semantics by computer. In this paper, the semantic representation ontology of pattern and combined geometrical specification is studied based on the new generation GPS theory and the construction process is introduced in detail through an example. Benefiting from the logic‐based semantics of the web ontology language (OWL) and semantic web rule language (SWRL), the pattern and combined geometrical specification semantic can be interpreted directly by computer and has the advantages of clear, unambiguous, and consistent at different stages of the product life cycle. At the same time, it can automatically check the consistency of knowledge, reason new knowledge, and semantic query.

SysML Based Modelling of Gear Shifting Strategy and Drivability for Automatic Transmission

In this project SysML modelling of gear shifting strategy and drivability are done for the development of the transmission control system. Gear shifting is the complex system operation and drivability is also important for driving pleasure. The work starts by developing system functions to capture system-level requirements such as grade compensator, hot mode manager, shift scheduler, torque converter state selection, transmission speed calculator, manual mode manager, etc. The next phase includes designing and developing structure models, behavioural models, and the analysis of system requirements. Thus, the functionality of the design patterns is verified in the earlier stage of the product development life cycle.