Phases Of Product Life Cycle Research Articles

Integrated inventory and pricing decisions for pre-existing and new entrance products considering product life-cycle

Today’s business landscape requires understanding the dynamic nature of the product life cycle (PLC) when making inventory decisions. This paper presented an integrated inventory-pricing model for a supply chain consisting of a single retailer, a pre-existing product manufacturer, and a new entrance product manufacturer. The model incorporated the PLC framework, encompassing the introduction-growth, maturity, and decline phases. In this competitive setting, the pre-existing product (PEP) has already progressed through part of its PLC when the new pro-environmental product (NPP) enters the market. To address the unique characteristics of each PLC phase, each manufacturer offers distinct incentive policies to the retailer in each phase. The demand for PEP is influenced by time and the progressively decreasing retail prices of both products, while the demand for NPP depends on time, retail prices, and the product’s greenness level. The results demonstrated that manufacturer incentive policies, including credit payments during the maturity phase, significantly increase profits for all three supply chain members. Moreover, extending the maturity phase of PEP and the introduction-growth and maturity phases of NPP enhances the retailer’s profitability.

A dynamic bi-objective optimization model for a closed loop supply chain design under environmental policies

Given the increasing focus on sustainability and environmental policy constraints, companies are required to redesign their supply chains. This paper explores the optimization of a closed loop supply chain (CLSC) network under both economic and environmental considerations. To achieve this, a bi-objective mixed integer linear model was developed. The proposed model identifies the optimal selection of CLSC facilities and manages both forward and reverse flows between them. The economic objective is reached by minimizing the total CLSC costs, while the environmental objective is satisfied by reducing CO2 emissions throughout the network. Products can be returned throughout their entire life cycle, which is why our model incorporates a dynamic aspect by considering product life cycle phases as time periods for the decision horizon. The model was tested through numerical experiments using a meta-heuristic approach based on the non-dominated sorting genetic algorithm NSGA-II. This algorithm produces a set of Pareto-optimal solutions that balance both objectives effectively. The results showed good performance in terms of computational time and optimization. Pareto solutions offered various options for managers and decision makers aiming for a sustainable closed loop supply chain design.

Design measures to address carbon emissions in products’ lifecycle: an empirical analysis

AbstractCompanies need to implement low-carbon operations, including product-related innovation initiatives. The literature on low-carbon product design has grown, but existing studies are primarily theoretical. This empirical study identifies design measures adopted by companies committed to GHG emission reduction. A qualitative analysis of the climate change reports from a sample of companies reporting to the CDP was conducted. Design measures were identified and classified. The findings shed light on design measures contributing to emission reduction in different product lifecycle phases.

Eco-design tool to support the design of industrial electric vehicles. The case studies of an electric shuttle and an autonomous mobile robot

The benefits of process optimization brought by multiple tools that appeared in shopfloors with the fourth industrial revolution are undiscussed; however, they need electricity to run and require critical materials. Additionally, the significant impact on sustainability that early design decisions can have over the entire lifecycle is well-recognized. The literature counts several environmental analyses of electric vehicles but narrows almost uniquely on passengers’ cars. Currently, the literature should i) enwiden the range of analyzed products, ii) consider all stages of the product life cycle, iii) provide tools suitable for the early stage of design, able to return consistent results handling very little data. As electrification is concerned, in the literature there are approaches intended to assess the environmental impacts or focused on the design tool. The proposed approach, further applied to develop an eco-design tool, overcomes the existing literature by providing a tool i) able to handle few data, ii) that considers all the product lifecycle phases, and iii) allows designers to assess and compare alternative scenarios. A method is proposed, and a tool derived. Two applications concern an electric shuttle and an autonomous mobile robot; with the latter the gap of assessing the environmental impact of autonomous mobile robots is also filled. The obtained results are reasonably comparable with other existing works. Results are compared to a full LCA for the frame assembly and prove that i) the tool is reliable, and it more likely overestimates the impacts; ii) the design phase is subjected to high variability, and this affects the tool results. Future works may introduce additional types of batteries, deeper focus on the manufacturing phase; machine learning techniques may support future extension of the tool and create parametric models for conceptual and early design. The proposed method and tool can be extended to the economic sphere.

Strategi Pemasaran Kedai Kopi Janji Jiwa Tondano Jilid 571

The research objectives were to identify the product life cycle phase of the café business and identify the marketing strategy of Kedai Kopi Janji Jiwa Tondano Jilid 571. The research was conducted for 3 months from June 2023 to August 2023. The research took place at Kedai Kopi Janji Jiwa Tondano Jilid 571, Liningaan Village, East Tondano District, Minahasa Regency. This research uses two types of data, namely primary data obtained through observation, interviews and questionnaires. Secondary data were obtained from company documents, seminar papers, and literature relevant to the research. Sampling using purposive sampling and the research sample taken was 40 people. The results showed that the product life cycle of Kedai Kopi Janji Jiwa Tondano Jilid 571 is in the maturity stage, especially at the stable maturity stage, namely sales that have reached their peak or are still growing or decreasing and do not have daily, monthly or annual targets. Marketing strategies based on the aspects of place and people aspects are a good choice of consumers because all consumers answer 100% good, and the less good ones are in the promotion aspect, due to the lack of promotion carried out and not many consumers know.

Automated Design of Experiments supporting Feature-based Optimisation of Manufacturing Processes

This paper presents a novel process design to enhance time and cost-efficient AI training in manufacturing. As an alternative to time and resource expensive trial-and-error loops, the data basis of the proposed design enables data-driven parameter selection, where the parameter range in which the optimal solution is likely to reside, can be explored in a reproducible and systematical manner. A full-factorial DOE is generated and implemented from within the CAM software. Necessary production artefacts, like NC code, bill-of-material or work plan, are supplied per experiment. The heterogeneous data of different product life cycle phases are collected and related to the according manufacturing feature (i.e., drilling, face-milling, etc.). From within the CAM software, the NC-Code is manipulated to enable the identification of features during production, using feature markers. Instantiated as Siemens NX CAM extension, the novel design was tested on a 5-axis milling and drilling process on aluminium parts. The automated data set generation with feature correlation between different live-cycle phases was verified. As a result, the design supports feature optimization strategies for decision support systems - either as input for CAD/CAM, PLM, ERP and MES.

Analysing Industry 4.0 technology-solution dependencies: a support framework for successful Industry 4.0 adoption in the product generation process

Industry 4.0 (i4.0) is central to advanced manufacturing. Building on novel digital technologies, it enables smart and flexible manufacturing with systems connected across company boundaries and product lifecycle phases. Despite its benefits, the adoption of i4.0 has been limited, especially in small and medium-sized enterprises. A key challenge is the technological complexity of i4.0. While advanced functionality requires technological complexity, it complicates an understanding of which enabling technologies are particularly useful and required. This article presents a framework to support successful i4.0 adoption across the entire product generation process through a systematic matrix-based dependency analysis of i4.0 solutions and underlying i4.0 technologies. Through increasing transparency around technological complexity of i4.0 solutions, this research contributes to a better understanding of which technologies are required for specific i4.0 solutions and which technologies could be strategic enablers for a broad variety of i4.0 applications. Knowing these technological dependencies supports both, the systematic adoption of existing i4.0 solutions and the development of new i4.0 solutions. This also sets the basis for a future socio-technical investigation.

A process model representation of the end-of-life phase of a product in a circular economy to identify standards needs

The development of secondary sources as industrial feedstocks is important to creating resilient supply chains that contribute towards diverting resources away from landfills, mitigating deleterious environmental impacts, and minimizing market volatility. A major challenge to develop secondary feedstocks is the coordination and digitalization of the large quantities of generated information at each phase of a product’s life cycle. This paper builds upon earlier work that illustrates a top-level model of the activities and information needs to integrate product manufacturing with circular practices. This paper extends the initial work to explore the cyclical nature of Circular Economy (CE) information flows specifically related to product End-of-life. Using the Integrated Definition 0, IDEF0, modeling technique this paper examines the End-of-life function envisioned under a CE manufacturing model [ISO, 2012]. This function is decomposed into subsequent child functions and is analyzed relative to other product life cycle phases. The paper reviews the current global product EoL practices and in the context of the developed IDEF0 model. The proposed framework contributes a detailed description and presentation of information flows and the drivers of change (i.e., feedback loops) that are essential for creating secondary material streams based on the critically analyzing the reviewed literature. The novelty of this study includes the identification of standards and metrics gaps to facilitate quantitative assessment and evaluation in a CE. The study further elucidates the discussion around CE in terms of resource regeneration by ‘designing out waste’ and decoupling economic growth from resource depletion.

Relations of Digital Twin Fidelity and Benefits: A Design-to-Value Approach

Digital Twin (DT) is an important concept in research and practice. Its relevance spans across all product life cycle phases, including design, prototyping, manufacturing, service, and disposal. Despite its attention, practical examples of DTs in product design and manufacturing are scarce. One of the reasons for this is little understanding of the benefits. Organizations face problems in predicting whether applying DTs will achieve benefits. However, realistic benefit expectations and a qualitative understanding of the evolution of benefits are essential for successfully applying DTs. Fidelity is thereby a crucial factor influencing costs and savings potential. Consequently, the Digital Twin Benefit Curves (DT-BC) were developed using Design Science Research while drawing on existing literature. Results were evaluated in a focus group with 5 DT experts from 3 different aerospace and automotive OEMs and 1 university, along with additional interviews. The developed curves serve as a reference for managerial decisions concerning DT design and application. Additionally, they strengthen the understanding of DT benefits and prevent stakeholders from developing false expectations that lead to acceptance issues. By doing so, DT-BCs facilitate Digital Transformation. The results provide a novel approach to make DT benefit evolution clear and tangible by visualizing its relation to fidelity.

Design for Circularity – Identification of Fields of Action for Ecodesign for the Circular Economy

The prevailing production and consumption patterns mostly follow a linear logic: produce, consume and dispose. This orientation of the economic system is highly resource-intensive and exceeds planetary boundaries. In order to decouple the economic growth from resource consumption circular economy is an important enabler by creating and closing resource loops. The goal of a circular economy is the sustainable return of resources into the value chain. Thereby, the design of the products plays a decisive role. Ecodesign is a systematic design approach for products in order to reduce environmental impacts over the entire life cycle by defining design principles. Therefore, ecodesign has the potential to allow the implementation of a circular economy by identifying design principles that enable critical resources to be preserved in cycles. For this reason, a framework with nine fields of action for the realization of circular economy by ecodesign was derived. The fields of action are based on the circular economy strategies "Closing the Loop" and "Slowing the Loop" as well as the product lifecycle phases addressed by ecodesign “production”, “use” and “recycling”. Practical use cases deal with the impact of the various design principles at the material, component and product levels of analysis.

Sustainable product lifecycle management with Digital Twins: A systematic literature review

A Digital Twin (DT) is a virtual replica of a product or product-service system, which can be used to provide transparency of a product's sustainability and to positively influence the ecological impact throughout its lifecycle by means of intelligent data analytics. This paper identifies current sustainability-focused application scenarios of DTs in the manufacturing industry and outlines the results of a systematic literature review (SLR). The identification of the state-of-the-art and the assessment of current DT concepts with regard to the addressed product lifecycle phases, technological maturity and sustainability scope point towards key directions to guide future research.

The Rαβγ categorisation framework for dexterous robotic manufacturing processes

Dexterous robotics systems integrate advanced manipulation and perception capabilities, facilitating advanced process automation. However, the inherent complexities of such processes may induce vulnerabilities, impeding overall performance. A parsimonious categorisation of dexterous robotic processes can disambiguate process attributes and highlight intricacies. Existing robotic categorisations focusing on a single attribute (e.g. manipulator structure) lack a processes view. Existing production process categorisations lack valuation of robotic characteristics. The current work suggests Rαβγ, a holistic categorisation of dexterous robotic processes. Rαβγ integrates robotic concepts within the classical [α|β|γ] production process categorisation and is similarly divided into tiers: Workcell, Task, and Objective. Each tier is defined by qualitative descriptors and quantitative characteristics. The intricacies of each characteristic were quantified by an analytic hierarchical process (AHP), semi-structured interviews with robotic experts were conducted for validation, and utility is demonstrated by three case studies. The AHP results are consistent and interpretable. The interviewees determined that Rαβγ is valuable and comprehensive. The case studies demonstrate the categorisation’s ability to highlight major process attributes. The analysis asserts that Rαβγ can be valuable during different product life cycle phases, e.g. designing, commissioning, etc. Rαβγ uniquely integrates the manufacturing and robotic domains, offering a holistic mechanism for highlighting characteristics of dexterous robotic processes.

Carbon footprint of atrial fibrillation catheter ablation.

Climate change represents the biggest global health threat of the 21st century. Health care system is itself a large contributor to greenhouse gas (GHG) emissions. In cardiology, atrial fibrillation (AF) catheter ablation is an increasing activity using numerous non-reusable materials that could contribute to GHG emission. Determining a detailed carbon footprint analysis of an AF catheter ablation procedure allows the identification of the main polluting sources that give opportunities for reduction of environmental impact. To assess the carbon footprint of AF catheter ablation procedure. To determine priority actions to decrease pollution. An eco-audit method used to predict the GHG emission of an AF catheter ablation procedure was investigated. Two workstations were considered including surgery and anaesthesia. In the operating room, every waste produced by single-use medical devices, pharmaceutical drugs, and energy consumption during intervention were evaluated. All analyses were limited to the operating room. Thirty procedures were analysed over a period of 8 weeks: 18 pulmonary veins isolation RF ablations, 7 complex RF procedures including PVI, roof and mitral isthmus lines, ethanol infusion of the Marshall vein and cavo tricuspid isthmus line, and 5 pulmonary vein isolation with cryoballoon. The mean emission during AF catheter ablation procedures was 76.9 kg of carbon dioxide equivalent (CO2-e). The operating field accounted for 75.4% of the carbon footprint, while only 24.6% for the anaesthesia workstation. On one hand, material production and manufacturing were the most polluting phases of product life cycle which, respectively, represented 71.3% (54.8 kg of CO2-e) and 17.0% (13.1 kg of CO2-e) of total pollution. On the other hand, transport contributed in 10.6% (8.1 kg of CO2-e), while product use resulted in 1.1% (0.9 kg of CO2-e) of GHG production. Electrophysiology catheters were demonstrated to be the main contributors of environmental impact with 29.9 kg of CO2-e (i.e. 38.8%). Three dimensional mapping system and electrocardiogram patches were accounting for 6.8 kg of CO2-e (i.e. 8.8% of total). AF catheter ablation involves a mean of 76.9 kg of CO2-e. With an estimated 600 000 annual worldwide procedures, the environmental impact of AF catheter ablation activity is estimated equal to 125 tons of CO2 emission each day. It represents an equivalent of 700 000 km of car ride every day. Electrophysiology catheters and patches are the main contributors of the carbon footprint. The focus must be on reducing, reusing, and recycling these items to limit the impact of AF ablation on the environment. A road map of steps to implement in different time frames is proposed.

Learning Factories and Sustainable Engineering—Competencies for Students and Industrial Workforce

Sustainability and the circular economy are becoming increasingly important for industry and academia. Learning factories at higher education institutions around the globe attempt to educate students and industrial workers on these topics through specially developed training modules. To successfully implement measures to mitigate issues, such as climate change, product life cycle considerations—in which different phases may require different worker competencies—are indispensable. In this context, we provide some evaluation of learning factory use cases regarding sustainability. The use cases are evaluated on product life cycle phases and respective worker sustainability and circular economy competencies. The results show that the majority of the use cases focus on the production life cycle phase; product development, product use, and end-of-life have either not or very rarely been addressed. Our general conclusions and implications relate to these findings with a recommendation that learning factories expand their training capabilities.

Knowledge framework for production planning and controlling considering sustainability aspects in smart factories

As the human population increases, the demand for products rises. Mass production and the use of these products cause different kinds of sustainable impacts, such as consumption of local and global non-renewable resources or different types of emissions during each stage of the product life-cycle (PLC). Through a systematic overview of these sustainable impacts during the production planning and controlling (PPC) process, sustainability impacts can be identified and possibly avoided. Identifying sustainability impacts is enabled through current developments for manufacturing and product systems digitalization. Data, information, and knowledge are available from each phase from the PLC and can be used for operational, as well as tactical and strategic production management processes. Companies exist, which are unprepared for the impending changes caused by digitalization and related applications. They do not know what and when to measure, as well as how measured data can be connected and analyzed to create new information and knowledge to meet management requirements. To contribute to this problem, the paper proposes a knowledge framework for the collection of data from different PLC phases, analysis of such data to create information, and generation and collection of knowledge for PPC processes. The knowledge framework seeks to answer the research question, which data, information, and knowledge from different PLC phases can be used in PPC processes to identify and avoid sustainability impacts. For this approach, existing concepts for digitalization (RAMI4.0) and knowledge management (business intelligence) are combined. Moreover, the paper presents a qualitative example using the knowledge framework and considering the problem statement about the environmental effects of greenhouse gas (GHG) emissions. Other sustainability problem statements can be considered too, such as employees’ working conditions. • Current research trends and developments in digitalization, knowledge management, and business intelligence. • Knowledge framework representing data, information, and knowledge for sustainable production planning and controlling. • Qualitative example of knowledge-based decision making in sustainable production planning and controlling.

Structuring Circular Objectives and Design Strategies for the Circular Economy: A Multi-Hierarchical Theoretical Framework

Most frameworks for dealing with the complexity of designing for the circular economy have limitations in terms of correlating different domains of knowledge, correlating highly complex design strategies, and facilitating the process of design strategies’ discovery and development. This paper discusses how managers and designers can create products that can be circulated for several life cycles by considering five different circular objectives (i.e., maintenance/longevity, reuse, refurbishment, remanufacture and/or recycling). To achieve one or more of these objectives, multiple design strategies can be used at various phases of each product life cycle and throughout the product’s lifetime. A literature review is used in this article to evaluate how circular objectives and design strategies are classified in terms of relevance, product life cycle phases, and product life cycles. The three classifications are merged to create a novel conceptual framework, which is then tested through the use of four circular case studies to map out life cycles, circular objectives, and design strategies. The framework may help managers and designers better understand how their businesses and products interact along the supply chain, allowing them to establish more effective product lifetime plans.

Integrating Customer Order Decoupling Point with Operation Planning in Deteriorating Supply Chain: General Dynamic Model and Applications

Considering the real dilemma of deteriorating items, we explore how to find a balance between the conflicting achievements of enhancing flexibility and reducing costs. We propose a general dynamic model to penetrate customer orders by decoupling point with objective to minimize the cost. The closed forms of optimal solutions are obtained for companies to deal with the integrated problem of customer order decoupling point (CODP) decision and production–inventory plan simultaneously. Applications and numerical experiments are performed to illustrate practical insights for managers. The results show that the truth of zero-inventory policy is to avoid unnecessary inventory instead of absolutely no inventory. The CODP will shift forward with the increasing of customer demand rate and shift backward with the increasing of deterioration rate under the production smoothing policy. However, although it encounters the same changes of demand, the CODP moves with a smaller extent in high deterioration rate than in low. In addition, we find that during the growth phase of product life cycle, the increase of time-sensitive degree of demand is coupled with forward shifting of CODP; while during the decline phase, it is coupled with CODP backward shifting.

Exploring green product attributes and their effect on consumer behaviour: A systematic review

Despite the growing scholars' attention towards green products, extant literature has so far lacked a systematic effort to analyse green product attributes (along different phase of the product life cycle) and link them to consumer preferences/behaviour. Indeed, the green product (and related processes) design and the consumer behaviour perspectives have been mostly treated separately to date. However, understanding consumer behaviour towards products as characterized by different green attributes, that may be related to different phases of product life cycle, is key for green products' market success. For these reasons, this study aims at linking the design and the consumer behaviour aspects of green product development. Specifically, through a systematic review, this study analyses extant research to provide a comprehensive list of green product attributes organized following a product lifecycle management perspective and a discussion of the effect of different green product attributes on consumers' behaviour. Eighty-two articles were included in the review and analysed. We identified 73 individual green product attributes and categorized them into 18 attribute groups, which were associated with product life cycle management phases (production, use, and end-of-life). Our results show that, in the production lifecycle phase, there is high incidence of environmentally sustainable attributes, and they are mostly related to production efficiency. Consumers perceive less this type of attributes, probably because they are placed before consumption. In the use phase, environmentally sustainable attributes depend more on consumers' actions to realize their sustainable value and they focus on technologies to reduce consumption. Finally, end-of-life environmentally sustainable attributes are related to the after-consumption stage of products, and they depend more on external actors to realize their value. Findings from previous studies about the effect of product attributes (identified for each product lifecycle phase) on consumer behaviour (such as purchase intention or willingness to pay a premium price) are reported. Results show that, for many attributes, no study has addressed their effect on consumer behaviour and that attributes for which there is a greater amount of studies on consumer behaviour are those related to the production and use phase. A future research agenda is proposed to advance knowledge on the role of green product attributes and their effect on consumer behaviour.

Medicine shortages: Product life cycle phases and characteristics of medicines in short supply-A register study.

Introduction: Product life cycle refers to all phases of a product from development to active market phase and finally the phase in which products possibly exit the market. The product life cycle of medicines in short supply has not been studied in depth, although there is some indication of mature products and products with lower prices and profit margins being exposed to shortages more often. The aim of this study was to examine the product life cycle phases and characteristics of medicines in short supply as well as the features of medicine shortages in Finland from 2017 to 2019. Material and methods: Register data on medicine shortages of human medicinal products from 2017 to 2019 was combined with timely data on marketing authorizations and reimbursement status to gain data on product life cycle phases and characteristics (e.g., the age and the reimbursement status) of medicines in short supply and the features of medicine shortages. The data were analyzed in descriptive manner using appropriate statistical testing. Results: 3,526 shortages were reported during the 3-year study period and the number of shortages increased annually. The average duration of a shortage was 83 days and shortages affected 660 active pharmaceutical ingredients. Most often, shortages occurred with medicines affecting the nervous system, the cardiovascular system, and the genitourinary system. A majority of shortages (n = 2,689) was reported in the reimbursable medicines group, where shortages increased as the number of patients receiving reimbursements increased (p < 0.001). In the reimbursable medicines group, shortages most commonly involved medicines aged 15–19, 20–24, and 25–29, whereas with both reimbursable and non-reimbursable products the shortages most often occurred in medicines aged 50–54. The frequency of shortages differed between the groups (p < 0.001) when both age and reimbursement status were taken into account. Conclusion: Medicine shortages are common and affect commonly used medicines. Product life cycle phase has an effect on the frequency of shortages: Reimbursable medicines and medicines exposed to changes in life cycle are more likely to face a shortage. The impacts of product life cycle on the availability of medicines and medicine shortages should be studied in more detail.

Towards the Smart Circular Economy Paradigm: A Definition, Conceptualization, and Research Agenda

The digital age we live in offers companies many opportunities to jointly advance sustainability and competitiveness. New digital technologies can, in fact, support the incorporation of circular economy principles into businesses, enabling new business models and facilitating the redesign of products and value chains. Despite this considerable potential, the convergence between the circular economy and these technologies is still underinvestigated. By reviewing the literature, this paper aims to provide a definition and a conceptual framework, which systematize the smart circular economy paradigm as an industrial system that uses digital technologies during the product life-cycle phases to implement circular strategies and practices aimed at value creation. Following this conceptualization, the classical, underlying circular economy principle, ‘waste equals food’, is reshaped into an equation more fitting for the digital age—that is to say, ‘waste + data = resource’. Lastly, this paper provides promising research directions to further develop this field. To advance knowledge on the smart circular economy paradigm, researchers and practitioners are advised to: (i) develop research from exploratory and descriptive to confirmatory and prescriptive purposes, relying on a wide spectrum of research methodologies; (ii) move the focus from single organizations to the entire ecosystem and value chain of stakeholders; (iii) combine different enabling digital technologies to leverage their synergistic potential; and (iv) assess the environmental impact of digital technologies to prevent potential rebound effects.