Content area
Product lifecycle management (PLM) constitutes a strategic approach in business that encompasses a variety of practices aimed at facilitating the collaborative creation, organization, dissemination, and utilization of information pertinent to the definition of a product throughout its entire life cycle. This strategy seeks to integrate individuals, processes, information, and organizational systems effectively. The present article delineates the applications of PLM within the defense, automotive, and small to medium-sized enterprises (SMEs) sectors, while also presenting findings from a systematic literature review (SLR). The analysis identifies the current state of PLM applications within the specified sectors and evaluates their effectiveness. Furthermore, the integration of PLM with artificial intelligence and digital twins is explored, highlighting significant avenues for future research in this domain.
Introduction
In contemporary business environments, it is evident that organizations are operating within a highly competitive market characterized by significant economic fluctuations [1, 2]. Consequently, companies are compelled to consistently meet the needs of their customers while navigating a series of challenges presented by an increasingly demanding marketplace and the evolving expectations of consumers, which have resulted in a reduced product lifespan [3]. In light of this complex landscape, the growth and performance of a company cannot be attributed solely to economic factors; rather, the integration of both technological and organizational innovation is imperative. Indeed, numerous stakeholders regard innovation as a critical component for the development and sustainability of businesses [4]. Beyond technological advancements, contemporary organizations are also engaged in organizational innovations that introduce significant modifications and transformations, thereby establishing meaningful objectives that facilitate participation in the enhancement and development of their operations. These forms of innovation have proliferated in recent years and have given rise to new strategic methodologies for the collaborative management of product-related information throughout its lifecycle, exemplified by Product Lifecycle Management (PLM) [2].
PLM can be defined as a multifaceted approach that offers numerous benefits at both the technical and organizational levels. Presently, this approach facilitates the integration of various methods and techniques for managing product information, spanning from the initial conception of an idea to the conclusion of the product's life cycle [5, 6].
While large corporations are increasingly exploring PLM in response to environmental regulations and technological advancements, its adoption remains limited among small and medium-sized enterprises (SMEs). There exists a paucity of empirical research focused on the significance of PLM within SMEs, particularly regarding strategies to mitigate production time, costs, and risks [7, 8, 9–10]. This body of work is insufficient to facilitate the widespread implementation of PLM in the SME sector. Most existing studies on PLM have concentrated on industries such as defense [11], automotive [12], medical, and fashion. As an example, PLM software enables fashion enterprises to achieve substantial cost reductions over time. The integration of data and diverse functionalities inherent in PLM systems facilitates brands in optimizing their production processes, minimizing waste, and enhancing resource management. Such improvements invariably yield favorable effects on the financial resources allocated for the design and manufacturing of textile products [13]. Moreover, PLM provides a comprehensive framework for the collection, enhancement, and administration of all data and processes associated with medical products, encompassing research and development, quality assurance, production, commercialization, and marketing. Furthermore, PLM addresses the complexities inherent in manufacturing and drug development by enabling effective management of clinical trial inventories, thereby contributing to the formulation of innovative strategies for the management of pharmaceutical enterprises [14].
Furthermore, this research specifically targets the defense and automotive sectors, as they represent the most prevalent contexts for PLM application [15, 16]. The objective of this study is to deepen the understanding of PLM characteristics within the small business context through a systematic review of empirical literature. Firstly, this study contributes to the existing body of knowledge by elucidating the conditions under which small firms in Morocco are likely to adopt PLM. Secondly, it enhances the understanding of the relationship between PLM and performance outcomes at the firm level. Notably, the Moroccan SMEs suffer from lack of organization and the generation of waste while executing tasks by artisans. That’s why the introduction of PLM within the Moroccan context in necessary [17]. Based on a systematic literature review, this article raises and discusses the following research questions: (1) What are the main works that have enriched the literature by evoking the PLM strategy especially within defense and automotive sector? (2) What are the research points that can be raised in order to be able to use PLM within society Moroccan since the use of this technology is absent within it? (3) What are the problems that can be solved through the use of PLM within the Moroccan industry?
The structure of this article is organized as follows. Section 2 summarizes the main existing works in the literature as well as the analysis and study of the existence of PLM within certain sectors, namely defense and automotive. Section 3 describes the research methodology, and preliminary statistics of the searched literature and corpus are presented to reveal the characteristics of literature distribution. In Sect. 4, we will raise certain points for future research, namely the establishment of PLM within a sector of an original nature which is the Moroccan social and solidarity economy sector in order to be able to resolve the problems that the latter knows namely the waste of raw material, time and effort used. In Sect. 5, we conclude this work.
Theoretical background
PLM approach is recognized as a reference framework that is beneficial for organizations based on their specific requirements. This framework positions the organization at the core of observations, taking into account various constraints related to product quality, collaboration among the organization and its stakeholders, as well as the requisite expertise [18, 19].
Thomas et al. explore the semantic management of the product lifecycle by proposing a metadata repository that employs a minimalist computational architecture. This architecture provides an information management layer grounded in a kernel, facilitating the acquisition of product data from diverse computational sources [20]. Moreover, Sakao et al. offer support to manufacturers by proposing an innovative and practical solution that emphasizes the design of a product/service system (PSS), aimed at ensuring the profitable utilization and sustainability of resources [21]. Besides, Tchoffa et al. examine the dynamic nature of the Federated Interoperability Framework (FIF), detailing the progression from its inception to anticipated future developments, particularly concerning the PLM standards test bench, manufacturing virtualization, and cyber-physical systems (CPS) [22]. Additionally, Liu et al. highlight the application of blockchain technology to ensure secure data exchange throughout the product lifecycle. The authors propose a platform that facilitates the storage and exchange of information among all stakeholders involved [23]. Furthermore, Jiewu et al. conducted a survey to investigate the relationship between sustainability and blockchain technology, reviewing existing literature from two perspectives: manufacturing systems and PLM. Consequently, the authors identify a series of challenges and barriers that blockchain technology must address to ensure sustainability on both industrial and commercial scales [24]. Also, McKendry et al. identify a range of factors that impede the effective implementation of PLM, including scale, complexity, uncertainty, extended product lifespans, management maturity, and the challenges associated with prototyping engineering-to-order (ETO) products. Consequently, the authors conducted an initial study involving 27 semi-structured interviews with PLM practitioners engaged in ETO product development. They subsequently proposed a framework aimed at facilitating the implementation of PLM within high value-added engineering programs [25]. In contrast, Camba et al. concentrate on small and medium-sized enterprises (SMEs) and propose a methodology for selecting the most appropriate PLM system for these organizations. Their approach is structured into three stages: the specification of needs, the refinement of management requirements, and the selection of a supplier for system implementation [26]. Moreover, Bertoni et al. undertake a cartographic analysis complemented by a literature review to investigate the role of digital twins throughout the product lifecycle (PSS), examining various dimensions such as collaboration and research aspects [27]. Hence, Ebel et al. integrate smart service innovation with PLM, proposing a methodology grounded in models suggested by the authors. Their focus is on the barriers that obstruct the assessment of the potential of digital technologies, emphasizing the pursuit of new business opportunities through a solution-oriented approach during the design phase. This study is predicated on the hypothesis that the development of new innovative models should stem from the recombination of pre-existing models and frameworks [28]. Besides, Woitsh et al. concentrate on digital twinning, advocating for a model-based approach. They address the observed gap between product manufacturing and the utilization of products and services by proposing a methodology designed to bridge this gap and demonstrate the relationship between data integration throughout the product lifecycle and digital twinning. This methodology is articulated as a meta-model to describe the integration process during manufacturing. Additionally, the authors present a physical experience that highlights the challenges associated with digitalization and servitization, which refers to the transition from traditional product sales to comprehensive offerings that include services [29].
The aeronautics sector is expansive and continuously evolving. Consequently, technological tools such as PLM transcend mere software for the design, industrialization, and manufacturing of aircraft; they serve as catalysts for the introduction of numerous innovations within the field [30].
The aeronautics sector is characterized by intense competition and is subject to various constraints across legislative, economic, ecological, and security domains. Nevertheless, technological advancement is imperative, necessitating the continuous development of high-quality products that surpass their predecessors within increasingly shorter timeframes [11]. This paradigm shift has directed engineering efforts towards the comprehensive design of aeronautical program architectures and the enhancement of after-sales services.
Institutions within the defense sector encounter numerous challenges, including escalating investment costs during periods of budgetary fluctuations and stringent contractual regulations. Consequently, the establishment of an integrated digital environment that consolidates various weapons programs alongside methodologies related to supply chain management and quality initiatives has become essential. Experts in aerospace and defense are thus reforming traditional systems utilized for the creation, marketing, and evolution of existing products. PLM emerges as a critical tool for enhancing productivity and performance, particularly in aeronautics, as it fosters collaboration among global teams and seeks to improve operational efficiency through advanced digital supply chain methodologies.
Moreover, PLM influences decision-making processes by establishing a pragmatic design framework based on defined roles. The defense and aeronautics sectors are also marked by the necessity of handling confidential information; PLM facilitates the assurance of this confidentiality through the implementation of highly secure processes and products, thereby mitigating the risk of espionage [31, 32, 33, 34, 35–36].
The development of Engineer-to-Order (ETO) products presents numerous challenges, primarily stemming from the complexity inherent in the programs designed for this purpose, which involve multiple interconnected elements throughout their lifecycle. Sargut examined complex systems, characterizing their complexity as unpredictable due to the continuous changes in the operational environment. While these changes may differ across systems, they can be anticipated and analyzed using appropriate tools [37].
For instance, the complexity associated with the design and manufacturing of military vessels can be attributed to unpredictability, emergent behaviors during various lifecycle phases, and the intricacies of operational behavior. Consequently, these challenges give rise to significant issues concerning costs, timelines, and quality expectations. A multitude of actions must be undertaken to address the complexities encountered, such as modifications to supplier interface requirements. These challenges can also impact other design aspects, potentially disrupting product development.
PLM can be regarded as a specialized profession [38, 39], which holds significant relevance in the context of emerging business professions [40]. Consequently, life cycle managers are responsible for delivering projects within established timelines and budgets while ensuring high-quality outcomes. This capability is attributed to the development of a comprehensive set of knowledge, tools, and techniques that facilitate the organization and execution of tasks [41, 42].
The origins of project management can be traced back to the previous century, primarily due to advancements in the defense and aerospace sectors [43]. Specifically, the increasing necessity to oversee a growing number of megaprojects has been a driving force in this field [44, 45]. Thus, project management is recognized as a crucial management competency, particularly in knowledge-intensive organizations [43, 46].
It is important to highlight that the defense sector is characterized by the implementation of Performance Based Logistics (PBL). A review of the literature reveals a substantial body of research focused on PBL, particularly its theoretical foundations [47, 48–49], operational strategies [50], and aspects of supply management [51], as well as inventory management [52]. Additionally, studies have examined PBL contract design [53, 54, 55, 56–57] and the challenges associated with the implementation of such contracts [58], including the intermediate costs incurred during the design and execution phases [59, 60]. The literature has provided insights into the design, implementation, success factors, and obstacles related to PBL [39].
PBL specifically addresses after-sales support contracts for equipment within the defense sector [61]. In contrast, Performance Based Contracting (PBC) encompasses applications relevant to the manufacturing sector, impacting both public and private entities [62]. Consequently, PBL is recognized as a strategic outsourcing approach that incentivizes suppliers, both financially and temporally, to invest in the enhancement of weapon systems [63, 64]. Notably, PBL has been adopted by several countries, including the United Kingdom [65], Italy [66], South Korea [67], and Israel [68]. Consequently, various studies have contributed to the optimization of PBL systems, aiming to minimize customer wait times, enhance system preparedness [69], and reduce costs [70, 71]. Furthermore, it is noteworthy that a cohort of researchers has employed Problem-Based Learning (PBL) methodologies to investigate the application of Performance-Based Contracting (PBC) within the defense sector, specifically focusing on services that are not directly related to the support of weapon systems [72] and security services [73].
In the automotive industry, PLM software facilitates the integration of various processes, including product design, lifecycle planning, assembly, testing, and maintenance [74]. Effective lifecycle management is crucial for success in this sector, as it enables profitable production through the adoption of innovative methodologies. Consequently, the automotive industry is positioned as a leading global entity in design and manufacturing contract services. To ensure the rapid delivery of high-quality products, industry leaders must invest significantly in research and development [75].
Achieving product profitability and process efficiency necessitates robust vehicle lifecycle management. Furthermore, companies must cultivate sophisticated and well-defined strategies and decisions throughout the product lifecycle [76]. PLM enhances clarity and coherence for suppliers and automobile manufacturers, facilitating the development of innovative processes that enable effective data management from the inception of a need to the product's eventual dismantling. Digital engineering supports collaborative efforts in the development, manufacturing, and renovation of products marketed globally [77, 78].
It is important to recognize that configuration management serves as a critical lever within the automotive industry. This aspect is fundamental to innovation, as it encompasses a set of concepts grounded in digital tools tailored to industrial applications [79]. Four key concepts are identified in this context:
Identification: This concept aids in conceptualizing the structure of the product and its components.
Recording configuration states: This phase allows for the stabilization of the product structure at a specific point in time.
Change management: This process provides a comprehensive description of all developmental states of the product structure.
Compliance monitoring: This aspect ensures the documentation of the implementation of product and system requirements.
Within the automotive sector, information pertaining to the product is systematically collected, organized, and disseminated throughout the product lifecycle, ensuring accessibility for all project stakeholders [80]. This systematic approach guarantees the monitoring of defects and facilitates responses to customer complaints, thereby minimizing the time products spend in the field. Product data is sourced from engineering applications and specialized databases. Ultimately, PLM ensures the identification and resolution of significant issues impacting customer experience while maintaining oversight of the product in the field to detect and prevent potential incidents that could lead to product damage [81].
In recent decades, the automotive industry has experienced a significant increase in competitiveness. According to McKinsey and Company, the advent of digitalization and artificial intelligence has introduced greater complexity to the business models employed by automotive firms, thereby necessitating a novel approach to production that is underpinned by the implementation of PLM. Consequently, it is imperative for automotive companies to adapt their operational practices to maintain a competitive edge in the marketplace. PLM facilitates these necessary adaptations, thereby contributing to the success of firms within the sector [82].
However, the realization and execution of PLM initiatives within small and medium-sized enterprises (SMEs) presents considerable challenges [83]. Typically, the implementation of such frameworks has been predominantly aligned with larger corporations, which poses significant obstacles for SMEs seeking to adopt PLM [84]. Therefore, it is essential to provide support to practitioners, as highlighted by Mickael [85], who offer insights into distinguishing between document-oriented and relational data-oriented PLM applications. Furthermore, the introduction of innovative practices within SMEs may entail various risks; Forrogh et al. [86] proposed a model aimed at substantially mitigating these associated risks. Additionally, Antonio et al. [87] introduced a versatile platform designed to assist SMEs in optimizing their processes and addressing challenges stemming from limited resources and a lack of technological expertise. Moreover, Gokcen [88] proposed a framework for the implementation of lifecycle management for high value-added products tailored to order programs, while Victor et al. [89] conducted a methodological bibliometric analysis encompassing all studies related to design management in SMEs. Similarly, Olwethu et al. [90] noted that the adoption of data management throughout the product lifecycle in SMEs is influenced by a variety of factors.
Methodology
In recent years, the application of artificial intelligence (AI) tools has gained significant prominence due to their capacity to efficiently extract data, manipulate textual information, and derive insights from extensive datasets tasks that can be labor-intensive and repetitive for researchers conducting systematic literature reviews through manual methods [91, 92]. Nonetheless, AI systems are limited in their ability to make nuanced judgments, interpret complex findings, apply specialized knowledge, or evaluate meanings across diverse fields of study. Consequently, a hybrid approach that combines computer assistance with manual processes was employed to conduct this systematic literature review, which is recognized as one of the most effective research strategies for advancing knowledge within a specific academic domain [93, 94–95].
With a primary focus on breadth, we undertook scoping studies across various disciplines, including business, management, entrepreneurship, technology, information management, and social sciences, to evaluate how PLM has been addressed in previous research. As noted by Tranfield et al., scoping studies are utilized in systematic literature reviews to assess the relevance and volume of existing literature and to delineate the subject area or topic under investigation [96]. Our scoping studies facilitated an exploration of the available literature on our topic and the identification of key related concepts. These preliminary evaluations affirmed the significance of the phenomenon within the fields of international business, marketing, management, innovation management, information management, industrial engineering, and social sciences.
The systematic literature review (SLR) methodology consists of three distinct phases: the collection of literature, the selection of relevant literature, and the classification of the literature, followed by the execution of the review search [97, 98–99]. This study adheres to the SLR framework with the aim of fulfilling specific research objectives, as illustrated in Fig. 1.
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Fig. 1
Methodology followed for the realization of the research objectives
The data collection methodologies employed in this review adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines as outlined by Moher et al. [100, 101]. A flow chart illustrating the study selection process is presented in Fig. 2.
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Fig. 2
The selection procedure of the studies (PRISMA flow diagram)
Documents published from 2008 to 2024 are searched, with document types including journal articles, conference papers, white papers and standards, etc. The search terms are found in the title and keywords of the publications compromise “Product lifecycle management”, “PLM”, “automotive sector”, “defense sector”, “SMEs”, etc. Researchers use a set of academic databases and a set of search engines, namely Science Direct, Web of Science and Scopus. Likewise, the search indexes are grouped in Table 1. According to the relevance ranking, approximately 22,320 literary works were properly analyzed. After an initial analysis of the content of the sections namely: the title, the summary, the Introduction and the conclusion we considered it necessary to retain 99 articles relevant to the objectives of our research and were selected.
Table 1. Literature search index in academic databases
Search | Index details |
|---|---|
Data base | Scopus, Web of science and science direct |
Time Range | From 2008 to 2024 |
Search Term | Product Life Cycle Management definition and objective PLM definition and objective Product Life cycle Management and defense sector PLM and defense sector Product Life cycle Management and automotive sector PLM and automotive sector Product Life cycle Management in SMEs PLM in SMEs |
Term Location | ‘‘Title” or ‘‘Keywords’’ of papers |
Literature Type | Journal papers, Conference papers |
Notably, we find that the documents reviewed are of different types, 69% are articles, 13.8% are conference papers, 6.7% are book chapters, 6.1% are reviews, 1.6% are conference reviews, 1.2% are books, 0.5% are editorials, 0.4% are erratums, 0.3% are notes and 0.3% are short surveys the distribution of documents is mentioned in Table 2.
Table 2. Distribution of documents by subject area
The subject area of documents | Distribution of papers (%) |
|---|---|
Review | 6.1 |
Book chapter | 6.7 |
Conference paper | 13.8 |
Article | 69 |
book | 1.2 |
Note | 0.3 |
Erratum | 0.4 |
Editorial | 0.5 |
Short survey | 0.3 |
Conference review | 1.6 |
Others | 0.1 |
As we said before, the study presented in this article was conducted using tree different databases: Scopus, Web of Science, Science Direct. The generic search string was defined as: “Product lifecycle management and objective"OR"PLM and objective"and"Product lifecycle management and defense sector"OR “PLM and defense sector” AND"Product lifecycle management and automotive sector"OR “PLM and automotive sector” AND"Product lifecycle management and small and medium enterprise"or “PLM and small and medium enterprise”.
In addition, inclusion and exclusion criteria were defined in order to select which research studies should be included, or not, in the review.
The defined inclusion criteria are:
Studies from 2008 to 2024.
Studies in the English language;
Studies related to the search string defined in title, keywords and abstract;
Primary studies.
The exclusion criteria are:
The primary study is not labelled as a paper published in journal or conference proceedings;
Duplicated papers;
Secondary studies;
Non-English written papers;
Specific Domain papers;
The redundant papers of the same author.
It is important to note that the exclusion criteria for the selected articles encompass several key aspects. Firstly, duplicate publications are eliminated, which refers to articles that appear multiple times across one or more databases. Secondly, secondary studies are excluded; these are articles that do not explicitly focus on Product Lifecycle Management (PLM), but rather discuss advancements in sectors such as defense while only briefly mentioning PLM. Additionally, articles not written in English are excluded from consideration. Lastly, papers that pertain to specific domains or are unrelated to the research context of this study are also excluded. For instance, PLM may refer to concepts such as patents local module or peak load management systems, which fall outside the scope of this research.
A systematic literature review may exhibit various forms of bias, one of which is selection bias. This type of bias is characterized by systematic differences in baseline characteristics between the groups being compared in a study. In the context of randomized trials, selection bias can emerge from insufficient generation of a random allocation sequence or inadequate concealment of allocations prior to group assignment. Detection bias occurs when there are discrepancies in outcome assessment that stem from the knowledge of treatment allocation by unblinded outcome assessors. Performance bias is defined as a systematic difference in the treatment of groups or variations in participant behavior resulting from awareness of the assigned interventions. Attrition bias pertains to systematic differences in dropout rates between groups. Lastly, outcome reporting bias arises when published trials selectively report only a subset of the outcomes that were measured.
The data schema plan has been developed to systematically capture the most pertinent information from the studies, thereby enhancing the analytical process and addressing each research question effectively. The details of the data schema are presented in Table 3. For each study, the collected data included the following elements: title, authors, year of publication, type of publication, source of publication, database utilized, technology employed, standard formalization, application domain, and the location of the proposal evaluation.
Table 3. Data extraction schema
Field | Description |
|---|---|
Study | Identification number |
Title | The paper title given by the authors |
Authors | Authors of the study |
Year | Year of the publication |
Publication type | Event type where the paper was published |
Publication source | Name of the event where the paper was published |
Database | Scientific search engine where the paper was indexed |
Used technology | Name of the technology used to achieve interoperability |
Standard formalization or ad hoc approach | If the study employs a standard formalization, is based on a standard, or employs an ad hoc approach |
Domain of application | The industry that the proposal covers |
Implementation | Academia, industry or conceptual |
Conducting a literature review remains a valuable approach for synthesizing the findings of various studies. This research is grounded in the results obtained from databases such as Scopus, Web of Science, and Science Direct, with the aim of identifying the most pertinent peer-reviewed articles related to the subject matter under investigation. Four specific categories were considered in this selection process (see Fig. 1).
Firstly, the articles must be indexed in Science Direct, Scopus or Web of Science. Secondly, the selected articles should originate from distinct journals and conferences, published between 2008 and January 20, 2024, to avoid redundancy. Thirdly, the articles must incorporate one of the specified keywords such as"PLM"or"Product Lifecycle Management"within the title, abstract, or keywords section. Lastly, the articles must be relevant to the concept being examined and address one of the designated sectors.
Results and discussion
The originality of this review is found in its exploration of the studied concept and the imperative to enhance this technology through its integration with other technological advancements, specifically artificial intelligence and digital twins [102, 103–104]. Consequently, the existing literature suggests that most approaches to digital twins predominantly focus on the Bill of Lading (BoL), particularly during the production phase [105, 106]. It is also important to highlight that the technological methodologies concerning PLM within the aforementioned sectors, namely artificial intelligence and digital twins, remain largely theoretical, lacking empirical investigations into the integration of these technologies with PLM [107, 108, 109–110].
This SLR review set out to answer three research questions, which were introduced in Sect. 1 as follows: (1) what are the main works that have enriched the literature by evoking the PLM strategy especially within defense and automotive sector? (2) What are the research points that can be raised in order to be able to use PLM within society Moroccan since the use of this technology is absent within it? (3) What are the problems that can be solved through the use of PLM within the Moroccan industry?
This review has identified a total of 99 documents spanning various disciplines. Among these, 40 documents address PLM on a global scale, discussing its objectives and the imperative for its implementation within industries. Additionally, 21 documents concentrate on PLM in the defense sector, 20 documents examine PLM in the automotive sector, and 18 documents focus on PLM in small and medium-sized enterprises.
To answer the first question we recapitulate some ideas that can help industries facing challenges especially defense and automotive industries.
As PLM and Industry 4.0 advance within the realm of defense manufacturing, several critical challenges and prospective avenues for advancement emerge. A primary concern is the necessity of ensuring robust cybersecurity. The increasing interconnectivity of manufacturing systems and the sharing of data heighten the risk of cyberattacks. Given the pivotal role of defense manufacturing in national security, it is particularly vulnerable to such threats. Consequently, the implementation of stringent cybersecurity measures—including advanced encryption, secure communication channels, and real-time threat detection—is imperative to safeguard sensitive information and uphold the integrity of defense production processes.
Another significant challenge lies in the integration of new Industry 4.0 technologies with existing PLM frameworks. Numerous defense production facilities still rely on outdated hardware and software. Transitioning to smart, interconnected systems necessitates meticulous planning and considerable investment to mitigate potential disruptions. The development of methodologies that enable the seamless and gradual incorporation of new technologies into current infrastructures poses a formidable challenge. Strategies such as modular updates, the utilization of middleware to facilitate communication between legacy and modern systems, and comprehensive training programs to equip personnel with the skills to manage advanced technologies may be essential components of this integration process.
In the defense sector, PLM initiatives are focused on the introduction of more intelligent and autonomous manufacturing systems. The convergence of PLM with artificial intelligence (AI) and machine learning (ML) has the potential to yield production lines capable of self-optimization and real-time adaptation to fluctuations in manufacturing requirements and environmental conditions. These advanced systems can significantly enhance productivity and reduce downtime by anticipating maintenance needs, optimizing production schedules, and even making autonomous decisions.
However, the development of such systems will require substantial advancements in hardware and sensor technology, as well as improvements in AI and ML algorithms, alongside enhanced data collection and processing capabilities.
For the automotive sector, recent advancements in the economy and technology have rendered automobiles increasingly significant in contemporary society. However, the automotive industry currently faces substantial challenges. Firstly, stringent environmental regulations have led to increased complexity in automotive equipment and in-vehicle control software, necessitating enhanced integration and intelligence, as well as greater diversification of power systems. Concurrently, the lifespan of automobiles has diminished due to production demands, creating an urgent need to bolster system design capabilities and develop effective solutions. Moreover, as vehicle structures become more intricate, the likelihood of performance degradation and functional failures escalates, resulting in heightened costs associated with design, development, testing, operation, and maintenance. This underscores the necessity for more efficient health prediction and maintenance strategies within the automotive sector. Additionally, the rising number of vehicles contributes to traffic congestion, complicating road traffic conditions, which is an issue that warrants immediate attention. Finally, addressing the conflict between automotive emissions and environmental sustainability has prompted vigorous research into electric and new energy vehicles, with a particular focus on enhancing battery performance. The integration of PLM with Digital Twin (DT) technology may offer innovative solutions to these pressing challenges.
In addressing the second and third inquiries, we outline several research questions pertinent to small and medium-sized enterprises (SMEs) in Morocco. Additionally, we discuss the challenges that can be effectively addressed through the implementation of PLM strategies, particularly within the ceramics and leather industries.
Regarding small and medium-sized enterprises (SMEs), the literature has identified numerous studies that present findings indicating the availability of PLM software tailored for smaller organizations, which are user-friendly [111]. Therefore, the effective implementation of such software in SMEs is contingent upon the adaptation of PLM to the specific organizational structure. Thus, a thorough analysis of the company's structure is crucial to ensure the successful adoption of PLM and to address potential barriers to integration, such as resistance to change, inadequate communication and information sharing, insufficient active listening, and the tendency to implement changes too rapidly [112]. Furthermore, it is noteworthy that the literature has not addressed the social and solidarity economy sector, particularly in the context of Morocco, which is characterized by its originality and cultural and heritage diversity.
The research questions that may be explored in future studies can be presented as follows:
How can we integrate PLM into the social and solidarity economy sector in Morocco? What steps should we follow for this integration? What problems can PLM solve within the industry? What are the impacts of the integration of this type of approach on the sector at the organizational and technical level? What gains and benefits can be made by this introduction? Can we combine it with other technologies within this sector namely the blockchain technology?
In light of the aforementioned issues, we advocate for the implementation of PLM as a means to address a prevalent challenge across all sectors of the social and solidarity economy: the inefficiency associated with material waste, which ultimately results in the squandering of both effort and production time. The marble industry exemplifies a significant industrial sector characterized by high consumption rates of water and energy [113, 114–115]. Notably, the production processes involved in the cutting of marble blocks necessitate substantial water usage [116, 117]. Furthermore, approximately 50% of the material processed during production is converted into dust waste [118, 119], which not only contributes to environmental pollution but also results in energy inefficiencies. By integrating waste into recycling initiatives, it is possible to mitigate environmental degradation and promote the sustainable use of energy and natural resources in production [120, 121–122].
The production of ceramics is associated with the emission of considerable quantities of greenhouse gases, which exacerbate environmental pollution and contribute to the climate changes observed in recent decades. In response, various projects have been initiated to alleviate these detrimental environmental impacts, including the development of alternative green construction materials aimed at enhancing sustainable development [123, 124]. The manufacturing of ceramic products necessitates the use of cement, with each ton of cement produced resulting in the emission of approximately one ton of greenhouse gases, thereby constituting a significant portion of global greenhouse gas emissions [125]. According to data from the Italian association of manufacturers of machinery and equipment for the ceramic industry, global production of various ceramic categories reached 13.7 billion m2 in 2018 [126]. It is noteworthy that around one-third of construction materials are discarded during the production process, and this ceramic waste is notably durable and resistant to the environmental conditions experienced in recent decades.
The leather industry is characterized by unpleasant odors and the generation of substantial amounts of highly biodegradable organic waste [114]. This waste primarily arises from the processing of animal hides and the reliance on various chemicals, including dyes, salts, oils, biocides, enzymes, sulfates, and finishing solvents utilized in manufacturing processes [127]. According to Muthukkauppan and Parthiban, only a small fraction of these materials—approximately 20%—is retained in the production of leather, while the remainder is released as waste, often accompanying wastewater [128]. Furthermore, chromium utilized in industrial tanning processes is predominantly present in waste, with approximately 60% of it being identified in wastewater. This waste is primarily composed of Chromium VI (hexavalent chromium), which is highly toxic and poses a significant threat to natural resources [129]. Additionally, the wastewater discharged from tanneries is characterized by pronounced coloration and contains a mixture of particles, organic matter, heavy metals, and noxious odors, all of which can contribute to chronic respiratory illnesses [127]. Consequently, tannery wastewater has been classified as one of the most hazardous types of industrial wastewater [130].
Furthermore, the implementation of PLM within the artisanal sector is anticipated to yield beneficial outcomes by enhancing the structural organization of the sector, thereby mitigating the disorder often observed during the execution of tasks by artisans. Furthermore, PLM has the potential to be expanded to incorporate additional design tools within this sector. It is imperative that this implementation is accompanied by a strategic approach that facilitates the marketing of products, transitioning the social and solidarity economy from routine activities to innovative design practices.
Morocco possesses significant energy and expertise that can be effectively integrated into PLM initiatives. Additionally, the country boasts influential advantages, including the transparency of sectorial plans, robust technological infrastructures, and a framework for industrial property. However, the sector is confronted with challenges that may hinder the pace of progress, particularly a lack of a comprehensive vision for innovative approaches such as PLM. Therefore, it is crucial to reassess and enhance the value of innovation, striving to embed it within production and management processes. In light of the challenges it faces, Morocco must adhere to two fundamental imperatives: to innovate and to embrace new ideas, concepts, and technologies in order to penetrate new markets.
Conclusion
It is important to acknowledge that the choice of databases and search queries may result in a limitation of search outcomes, potentially leading to a superficial or biased representation of the subject matter. Currently, PLM emphasizes the implementation and integration of Digital Twin technology and artificial intelligence, particularly in conjunction with PLM systems [131, 132].
This review encompasses a total of 99 scholarly works pertaining to PLM within an industrial context, aiming to encapsulate the developmental aspects of PLM technology across the defense, automotive sectors, and small to medium-sized enterprises (SMEs). The establishment of software platform linkages is a primary objective of PLM integration within industries, facilitating effective data management and ensuring seamless communication among all project stakeholders, thereby enhancing decision-making processes [133, 134].
This research is accompanied by several limitations that warrant consideration within the framework of the study. Furthermore, it delineates prospective directions for future research. The foremost limitation is that the study primarily serves as a thorough literature review on PLM, while significantly lacking in practical examples of its application within organizational contexts. A secondary limitation is that the review predominantly emphasizes publications explicitly related to PLM, thereby overlooking literature on related concepts such as eco-innovation, sustainable management, and open innovation pertaining to green initiatives. Moreover, there is an exclusion of non English studies which can influence the results of this SLR.
Additionally, the study may be influenced by potential biases from both the authors and reviewers. Such biases could have led to the omission of pertinent articles due to the specific keywords utilized in the search process. This concern may also stem from the employment of inadequate keywords or alternative terminologies for the same concept. As a result, the selection, inclusion, categorization, and analysis of the articles were inevitably influenced by the subjective viewpoints of the authors and reviewers.
The implementation of PLM necessitates careful monitoring when adopted by an organization. The transition to PLM integration within production processes demands significant organizational and strategic changes, which can provide new opportunities for companies to market their products in innovative ways, ultimately enhancing profit margins. Furthermore, PLM serves as a conduit for collaborative innovation, offering a suite of tools for idea generation, data management, and the dissemination of essential information across various environments [135, 136].
Moreover, the social and solidarity economy sector in Morocco presents a domain that requires numerous improvements. Consequently, there is a pressing need to introduce PLM to optimize the utilization of raw materials, a topic that will be explored in our forthcoming research focused on the social economy sector in Morocco.
Author contributions
Mohammed Saad Aberkane wrote the main article and prepare the figures, Aberkane Otman validate the results. All of the authors reviewed the manuscript.
Funding
There was no external Funding for this research.
Data availability
No datasets were generated or analysed during the current study.
Declarations
Ethics approval and consent to participate
Not applicable.
Competing interests
The authors declare no competing interests.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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