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As a manufacturing power in the era of Industry 4.0, the Chinese traditional manufacturing industry urgently needs innovation and upgrading. In this process, the pressure on the traditional manufacturing industry is mainly financial shortages. The government can act as a Booster to add power to the upgrading by providing financial support. We build a three-tier game model consisting of Raw Material Suppliers, a Traditional Manufacturer, and an Original Equipment Manufacturer to explore the upgrading conditions and construct three settings: Agency, Consignment, and Design. We find that the government subsidy can serve as an effective way to ease enterprises' financial burden and improve the innovation level, which is more evident when the traditional manufacturer innovates. In addition, when the market competition and the government subsidy are both at a moderate level, the combined effect of the two factors is positive, and the condition is the best to upgrade. Encouragingly, the social welfare under Design will be the highest when the government subsidy is slightly great. Finally, excessive subsidy hinders upgrading and aggravates market competition, even if the traditional manufacturer enjoys exorbitant profits. HIGHLIGHTS The upgrading on the manufacturing industry in the era of Industry 4.0 The right of product design in supply chain models The cross-influence of the government subsidy and market competition on industrial upgrading is introduced The conditions to help upgrade the manufacturing industry are given in the era of Industry 4.0 [ABSTRACT FROM AUTHOR]

Freight transportation, including just-in-time (JIT) supplier networks, accounts for a substantial part of the global carbon dioxide (CO $ _2 $ 2 ) emissions. The JIT truck routing problem (TRP-JIT) presented in the recent literature consists of several suppliers serving a single original equipment manufacturer (OEM). A logistics provider organises the milk-run routes. The shipments are available after their release dates at the suppliers and should be delivered on their due dates at the OEM with minimal total earliness-tardiness penalties (first objective). Unlike previous research on the TRP-JIT, we focus on its environmental impact: (1) We include the weight-distance (second objective), depending on the truck's curb weight, the load, and the transportation distance. (2) We adapt a state-of-the-art large neighbourhood search (LNS) from the literature considering both objectives. (3) The LNS is embedded in bi-criterial frameworks, i.e. ε-constraint and weighted sum methods. Thereby, we estimate Pareto frontiers with at least 60 solutions in less than 25 min for instances with 99 shipments. From a managerial perspective, increasing the difference between the release and due dates for a better JIT performance may worsen the environmental impact. Lighter trucks can reduce the environmental costs without affecting the JIT performance, whereas a smaller fleet negatively affects both objectives. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) provides new opportunities to improve manufacturing lines' performance and in-plant logistic processes. The digital milk-run system represents the new frontier to optimize material handling strategies but is still not fully exploited to address material distribution depending on the time slots required by the manufacturing lines. Therefore, to fill this gap, this paper investigates the actual integration of the milk-run system with an IoT system. An analytical model for planning a dynamic routing strategy for tugger trains to deliver the materials to different workstations of a production line has been developed. The proposed model provides a materials distribution consistent with the time slot required by the manufacturing line, ensuring the minimisation of the total distance of the routes. An algorithm developed in Python is proposed to solve the NP-hard problem (nondeterministic polynomial time problem). The model has been applied to a real case of a worldwide automotive company to validate and prove its efficacy and efficiency. Indeed, compared to the current in-plant logistic strategy, (i) the inventory stock of each workstation was ensured, (ii) the average utilization rate of the tugger trains' fleet was improved, and (iii) the daily path was minimized. [ABSTRACT FROM AUTHOR]

Electric Vehicles (EVs) have a critical role in the future of sustainable transportation systems. Recently, improving the infrastructure for EVs has been a major focus of organizations around the world, such as local and federal governments, energy companies, and automotive original equipment manufacturers. In this article, we present a service network design framework to improve the infrastructure for EVs with quality of service constraints taken into consideration. We present a novel charging station location model with capacity allocation. The model maximizes the EV traffic flow captured and minimizes the average service time for drivers. The model formulation allows for assessing capacity and quality of service trade-offs, and operational insights are presented to reflect drivers' expectations. We demonstrate an application for the solution approach on a real road network and evaluate the performance based on both computational efficiency and solution quality. Our results highlight how charging times at stations affect the quality of service in the whole service system by quantifying the improvements in flow coverage while reducing waiting times. The value of faster chargers in increasing coverage and reducing the average waiting times is also highlighted in relation to a service provider's budget constraints. [ABSTRACT FROM AUTHOR]

This paper discusses logistics collaboration applied to a vehicle-manufacturing setting. We reach out to a larger segment of the supply chain by employing a novel unit of analysis, a logistics triad. The triad encompasses an Original Equipment Manufacturer, a Third-Party Logistics Service Provider, and first-tier suppliers. We use the framework known as Collaborative Transportation Management (CTM) to study collaborative transportation activities, focusing on the important relationship between logistics collaboration and logistics performance. Using a qualitative research orientation and a multi-case research strategy, we interviewed logistics practitioners in three countries to identify the enablers of CTM, the salient collaborative practices, and the performance outcomes. The study uncovers the extent to which CTM contributes to the operational and relational performance of the logistics triad. We provide empirical evidence of an ad hoc implementation of this notion. We propose avenues of intervention to preserve logistics collaboration and to enhance logistics performance. [ABSTRACT FROM AUTHOR]

The hydrogen internal combustion engine (H 2 -ICE) is proposed as a robust and viable solution to decarbonise the heavy-duty on- and off-road, as well as the light-duty automotive, sectors of the transportation markets and is therefore the subject of rapidly growing research interest. With the potential for engine performance improvement by controlling the internal mixture formation and avoiding combustion anomalies, hydrogen direct injection (H 2 DI) is a promising combustion mode. Furthermore, the H 2 -ICE poses an attractive proposition for original equipment manufacturers (OEMs) and their suppliers since the fundamental base engine design, components, and manufacturing processes are largely unchanged. Nevertheless, to deliver the highest thermal efficiency and zero-harm levels of tailpipe emissions, moderate adaptations are needed to the engine control, air path, fuel injection, and ignition systems. Therefore, in this article, critical design features, fuel-air mixing, combustion regimes, and exhaust after-treatment systems (EATS) for H 2 DI engines are carefully assessed. [Display omitted] • Key design aspects for achieving high efficiency and low emissions summarised. • Injection and intake ports are critical for good in-cylinder mixture formation. • Thermal management is required to mitigate abnormal combustion. • Advanced boosting system required to obtain high power density. [ABSTRACT FROM AUTHOR]

The automotive industry, known for its dynamism and innovation, relies on effectiveness of product and process requirements management. Effective collaboration with OEM (Original Equipment Manufacturers) is essential for success. The article analyses how product and process requirements evolve during different project phases, following the APQP (Advanced Product Quality Planning) approach, depending on OEM type. The study focuses on Tier 1 organizations, direct suppliers to the automotive industry, and their diverse approaches to product development. It underscores the need for Tier 1 organizations to maintain flexibility in their operations and to be prepared for changes in OEM demands. The study emphasizes the role of effective communication and coordination among all the levels of the supply chain to ensure the successful implementation of the APQP approach. [ABSTRACT FROM AUTHOR]

The third‐party remanufacturer (TPR) can cooperate with the original equipment manufacturer (OEM) and remanufactured products are sold by the OEM (i.e., the cooperation mode). The TPR can also sell remanufactured products individually to compete with the OEM's new products (i.e., the competition mode). Considering the issue of false information in remanufacturing supply chains and the TPR's limited capital, we build game models with blockchain to explore the TPR's optimal financing strategies under different co‐opetition mode selections. We find that a high blockchain usage prompts the TPR to finance from the OEM in the competition mode, while a low blockchain usage motivates the TPR to choose the cooperation mode and opt for a bank credit. Besides, we also find that the difference between the TPR's optimal profits of cooperation and competition modes increases with the interest rate. [ABSTRACT FROM AUTHOR]

In the context of the world economic downturn, consumers are showing a trend of brand weakening. In order to explore the product advantages of the source manufacturer, that is, the competitive supplier, we establish a game theory model to study the strategy choice of original equipment manufacturers (OEM), competitive suppliers (CS), and noncompetitive suppliers (NS) based on consumer heterogeneity. By dividing consumers into quality consumers and ordinary consumers and considering horizontal competition (between suppliers) and vertical competition (between OEM and suppliers), it is found that the products of the source manufacturers are becoming more and more popular with consumers. Contrary to the traditional view, we find that under the trend of brand weakening, the products of the source manufacturers should be positioned above the price range acceptable to consumers, and the OEM products of the brand owners should be appropriately reduced. The interesting question is whether CS will discontinue the supply of OEM components once it has its own branded products. Further, we analyze that CS terminating the component sales business is an untrustworthy threat to OEM. Finally, we find that there will be a "win–win" zone between OEM and competing suppliers, and the "win–win" region will decrease as the manufacturing cost of the competing supplier increases and increase as the manufacturing cost of the noncompeting supplier increases. [ABSTRACT FROM AUTHOR]

As the number of electronic control units (ECUs) in vehicles continues to grow, exchanging physical components between original equipment manufacturers (OEMs) and ECU suppliers presents logistical challenges, impeding the pace of development and leading to accumulation of costs. In this work, we introduce a conceptual framework that enables remote testing of geographically dispersed ECUs over the Internet. Pertinent to the Internet of Things (IoT) sphere, where interconnection of distributed components is hampered by the inherent challenges of latency, we propose a hybrid synchronous methodology that combines asynchronous test management with time synchronization mechanisms to mitigate the delay impact within the distributed environment. Additionally, we discuss challenges and prospects associated with this approach. [ABSTRACT FROM AUTHOR]

In order to improve the profitability and customer service management of original equipment manufacturers (OEMs) in a market where full-service (FS) and on-call service (OS) co-exist, this article extends the optimising modelling for pricing FS repair contracts with the effects of dynamic learning and forgetting. Along with considering autonomous learning in maintenance practice, this study also analyses how induced learning and forgetting process in a workplace put impact on the pricing optimising model of FS contracts in the portfolio of FS and OS. A numerical analysis based on real data from a medical industry proves that the enhanced FS pricing model discussed here has two main advantages: (1) It could prominently improve repair efficiency, and (2) It help OEMs gain better profits compared to the original FS model and the sole OS maintenance. Sensitivity analysis shows that if internal failure rate increases, the optimised FS price rises gradually until reaching the maximum value, and profitability to the OEM increases overall; if frequency of induced learning goes up, the optimal FS price rises after a short-term downward trend, with a stable profitability to the OEM. [ABSTRACT FROM AUTHOR]

We have developed three distinct decision models to examine the influence of consumer's carbon footprint sensitivity level and government subsidies on the green technology innovation level of an original equipment manufacturer (OEM), as well as pricing decisions for both the OEM and a third-party remanufacturer (TPR). Our study provides valuable insights for businesses to determine the appropriate green technology innovation level and manage the adverse effects of carbon footprint. The results show that the OEM will set the green technology innovation level according to the consumer's carbon footprint sensitivity level and the remanufacturing emission reduction coefficient. Only when there is government subsidy and the carbon footprint sensitivity level exceeds a certain threshold, does the profit of OEM increase with a rise in carbon footprint sensitivity level. Otherwise, the carbon footprint only harms the OEM's profit. While the consumer's carbon footprint sensitivity level can help reduce the detrimental environmental impact of products, it can also diminish consumer surplus and social welfare. However, government subsidies have the potential to mitigate the adverse effect, making the consumer's carbon footprint sensitivity level an incentive to increase consumer surplus and social welfare. [ABSTRACT FROM AUTHOR]

This study investigates an original equipment manufacturer's (OEM's) outsourcing choice between a competing manufacturer (CP) and a non‐competing manufacturer (NP). We develop a benchmark self‐produce strategy and two outsourcing strategies to differentiate two manufacturing service providers, and examine the optimal strategy alongside an analysis of the respective incentives (e.g., a lump‐sum payment) from the two service providers. The optimal strategy depends on the difference in production efficiency, degree of product substitution, and joint effect of the transfer payments. The transfer payments contribute to a greater range of Pareto improvements, increasing the possibility of outsourcing cooperation while highlighting the role of competition intensity on the model and outsourcing cooperation partner. Effect analysis shows that in the absence of transfer payment, the optimal strategy is beneficial to social welfare. With transfer payment, the optimal strategy is changed and the firms will be more profitable, but at the expense of customers' surplus, which may result in worse social welfare. An extended analysis of mixed strategies, in which the OEM produces part of the products and outsources the rest to CP/NP, shows that while the mixed‐CP strategy can be an optimal choice, the mixed‐NP strategy will degenerate to either self‐produce or complete outsourcing to NP under certain conditions. [ABSTRACT FROM AUTHOR]

Introduction: Refurbished medical devices are previously owned equipment that undergo a process of restoration to ensure they meet quality standards and function effectively. The utilization of refurbished medical devices, coupled with the integration of software, poses intricate challenges in terms of regulatory compliance, risk management, and patient safety. Areas covered: This article explores the regulatory frameworks governing refurbished medical devices in the United States (US), the European Union (EU), Malaysia, and Ghana. Included information from a range of primary and secondary sources. Additionally, it aims to identify and analyze the risks associated with refurbished medical devices, with a specific focus on the implications of software integration, and recommend practical solutions for mitigating these risks. Expert opinion: The landscape of refurbished medical devices presents challenges in terms of regulatory compliance, risk management, and patient safety. Addressing these challenges requires careful consideration and strategies to ensure that refurbished devices meet stringent quality standards. By focusing on these areas, policymakers and healthcare professionals can enhance the safe utilization of refurbished medical devices, thereby improving access to quality healthcare, particularly in underserved regions. [ABSTRACT FROM AUTHOR]

This paper develops a game‐theoretic model that examines the entry decisions of two competing platform owners with differentiated research and development (R&D) efficiency and the response strategy of an original equipment manufacturer (OEM) in selecting which platform to cooperate with. The OEM and platform owners compete on quality and price in the face of consumers with heterogeneous preferences across the dimensions of the device and platform. We analyze the interaction between the entry decisions of platform owners and the OEM's response strategy within two cooperation models. In the charging model, we find that in the absence of entry, the OEM prefers the high‐efficiency platform. When only one platform owner enters, the OEM prefers the low‐efficiency platform. If the differentiated R&D efficiency and the device differentiation cost are large, both platform owners will choose to enter and the OEM will cooperate with the low‐efficiency platform. In the bundling model, when only one platform owner enters, only at a large cost of device differentiation will the OEM cooperate with the platform that enters the market to weaken market competition. In particular, when only the high‐efficiency platform enters, it is interesting that there exists a large cost of device differentiation that makes the high‐efficiency platform more favorable in the case when the OEM cooperates with the low‐efficiency platform. Our study provides practical insights into platform entry and OEM response. [ABSTRACT FROM AUTHOR]

Increased consumer environmental awareness prompts an original equipment manufacturer (OEM) to work with a green contract manufacturer (CM), where the latter can encroach on the existing market and compete with its OEM by introducing his own-label products. We consider four supply chain scenarios (i.e., NE, ED, EA, and ER) based on the encroachment modes of green CM (i.e., no-encroachment, direct selling, agent selling, and reselling), and explore channel configuration strategies from various perspectives. First, for economic benefit, the CM always encroaches, and entry cost, product substitutability, and agency fee are critical to online channel configuration. The OEM is more reluctant to CM encroachment when two products' greenness is different. Based on the fact that the agency fee is generally not greater than 0.2, the platform acts as a reseller in most cases. Second, for environmental benefit, both Scenarios ED and EA are likely to be dominant strategies when product greenness is different; otherwise, Scenario ED is always dominant. Finally, consumer surplus can be improved in all encroachment scenarios and consumers prefer Scenario ED in most cases. [ABSTRACT FROM AUTHOR]

Original Equipment Manufacturers (OEMs) have sought new supply chain paradigms that allowed them to focus on core activities, i.e. overall product design and commercialisation. This pursuit led to partnerships with a new generation of tier-1 strategic suppliers acting as integrators. Integrators are not only responsible for system supply, but also for system design. However, critical integrators were not able to live up to their new roles, which led to costly delays in development and production. These failures highlight the ineptitude of current risk management practices employed by OEMs. To support OEMs in implementing a more differentiated and suitable approach to the use of integrators, this paper proposes a mathematical programming model for Supply Chain Design (SCD). Instead of looking at the introduction of integrators as a dichotomous decision, the model suggests the optimal number of integrators, i.e. systems, and individual part suppliers. We propose new measures for integration risk, which build upon current risk assessment practices. Robust optimisation is used to study the effect of uncertainty over baseline risk values. All approaches were tested using both randomly generated instances and real data from a large European OEM in the aerospace industry. [ABSTRACT FROM AUTHOR]

To formulate multi-tier supply chain management strategies with global impact, understanding the roles of various supply chain partners in disseminating sustainability along the supply chain is crucial. We analyze the influence of different supply chain positions on sustainability and financial outcomes of Turkish manufacturing companies listed in İstanbul Stock Exchange (BIST). We propose a sustainability measure, and rank firms according to their sustainability practices in relation to their financial outcomes using data envelopment analysis (DEA). We estimate Seemingly Unrelated Regression (SUR) equations to control for the common financial shocks that can affect sustainability and financial outcomes simultaneously. Our analysis reveals that first-tier and sub-supplier (second-tier and lower-tiers) firms' financial performance is substantially better compared to Original Equipment Manufacturer (OEM) firms while their sustainability outcomes stay behind. We find that this latter effect is more profound for first-tier firms. Although the supplier firms generally comply with the OEM's product standards, our results show that they are not aligned with the OEM in terms of the environmental and social impact of their operations. Given the crucial role of first-tier suppliers in sustainability dissemination along the supply chain, policies should be formulated in this industry amid these characteristics of the sustainability dissemination. [ABSTRACT FROM AUTHOR]

Despite stringent regulatory scrutiny and increased cybersecurity spending, data breaches and cyberattacks have persisted, resulting in dire socioeconomic consequences. Particularly affected is the automotive industry, where original equipment manufacturers (OEMs) have implemented effective strategies against cyberattacks. Limiting the vulnerability of connected and autonomous vehicles to cyberattacks requires an expanded suite of strategies over and above technological safeguards. This study, guided by the National Institute of Standards and Technology cybersecurity framework, aimed to answer two questions: First, how do leaders of automotive OEMs describe and interpret the use of cybersecurity frameworks to prevent cyberattacks? Second, how does the perceived impact of potential cyberattacks influence the cybersecurity framework used by automotive OEM leaders? Using purposeful sampling, 20 automotive OEM leaders in the cybersecurity field responded to questionnaires and interviews to reveal three insights: (a) The automotive OEMs must reinforce bundled risk management frameworks because attackers will continue to exploit human vulnerabilities to gain access to secured systems, and this calls for reducing human vulnerabilities by understanding employee behaviors; (b) The leaders have to embrace open-threat intelligence through information sharing. Instructive for policy-making is the continued advocacy for threat intelligence-sharing platforms that are transparent and timely; (c) Uniquely insightful is leveraging blockchain technology to manage and securely track CAVs and their components enhances the automotive OEMs' ability to maintain cyber-defensible CAV assets. [ABSTRACT FROM AUTHOR]

The development of digital technology, such as data mining and analysis techniques, has enabled e-commerce platforms to use the data generated in their ecosystems and forecast the online demand more accurately. By sharing the forecast information, platforms help their partners reduce the demand uncertainty. To examine the effects of the shared information, this study considers a two-echelon supply chain consisting of one original equipment manufacturer (OEM), one brand store, and one platform, and investigates the relations between the forecast information and firms' channel strategies. Our analysis reveals some interesting implications. First, the platform's forecast information encourages the OEM to develop online business unless the brand store adopts the dual-channel strategy and the platform sets the revenue commission as zero, while it always increases the brand store's willingness to adopt the dual-channel strategy. Moreover, the OEM's online business hinders the platform to share the information if consumers' acceptance for the brand in online channel is low. Interestingly, the brand store's dual-channel strategy hinders the platform to share the information if consumers' acceptance for the brand in online channel is high. Further, we find that when the brand store adopts the dual-channel strategy, the OEM's online business always decreases the benefit of the forecast information for the brand store. However, when the OEM develops online business, the brand store's dual-channel strategy sometimes increases the benefit of the forecast information for the OEM. In addition, we also conduct some numerical experiments to examine the impacts of the platform commission rate on these firms' benefits from the information and find that the higher commission rate can increase the OEM's benefit under certain conditions. Our study aims to provide managerial insights for the OEM, brand store, and platform to capture the value of forecast information. [ABSTRACT FROM AUTHOR]

The targets of energy conservation, decarbonization, and industry reinvigoration have significantly influenced the design of China's new energy vehicle (NEV) industrial policies and nationwide electrification. As a monumental policy framework for energy transition in transportation sector, the NEV industry development plan plays an influential role in promoting cleantech diffusion and enhancing NEV competitiveness. This study employs an event study method to investigate the stock market reaction to the NEV plan shocks. The NEV plan announced in 2020 receives a markedly positive stock price effect of 3.72% in the 6-day event window. Heterogeneity tests on subsamples indicate that state-backed entities exhibit a similar effect to the total sample, while the automotive manufacturing class and original equipment manufacturers see a significantly higher market value gain of 6.56% and 13.34%, respectively. However, battery manufacturers, as one of the key participants in the NEV value chain, experience an insignificant stock price effect. This study documents the financial consequences of clean energy policies specific to the emission-intensive automotive manufacturing sector, highlights the effectiveness of government-to-investor signalling in a cleantech diffusion context, and reveals the implications to other economies seeking to deploy clean transport and enhance environmental sustainability. The national NEV industry development plan aiming at the energy transition of the transportation sector can incur outperformance of NEV stocks in the financial market. Different stock market performances between NEV plans manifest investor preference for market-oriented industry policies. The long-term policy framework for green industry transition can send positive signals to investors, guide capital reallocation, and direct investment flows into key financial assets. The implications from the Chinese market offer valuable insights for other countries in formulating concrete industry planning, transition agendas, and binding targets for climate change mitigation. [ABSTRACT FROM AUTHOR]

The objective of this study was to assess the biofidelity of the Global Human Body Models Consortium (GHBMC) 50th male (M50-O) v6.0 seated in an upright (25-degree recline) all-belts-to-seat (ABTS) in a 56 km/h rear-facing frontal impact. The experimental boundary conditions from the post-mortem human subjects (PMHS) tests were replicated in the computational finite element (FE) environment. The performance of the rigidized FE ABTS model obtained from the original equipment manufacturer was validated via simulations using a Hybrid III FE model and comparison with experiments. Biofidelity of the GHBMC M50-O was evaluated using the most updated NHTSA Biofidelity Ranking System (BRS) method, where a biofidelity score under 2 indicates that the GHBMC response varies from the mean PMHS response by less than two standard deviations, suggesting good biofidelity. The GHBMC M50-O received an occupant response score and a seat loading score of 1.71 and 1.44, respectively. Head (BRS = 0.93) and pelvis (BRS = 1.29) resultant accelerations, and T-spine (avg. BRS = 1.55) and pelvis (BRS = 1.66) y-angular velocities were similar to the PMHS. The T-spine resultant accelerations (avg. BRS = 1.93) and head (BRS = 2.82), T1 (BRS = 2.10) and pelvis (BRS = 2.10) Z-displacements were underestimated in the GHBMC. Peak chest deflection in the anterior-posterior deflection in the GHBMC matched with the PMHS mean, however, the relative upward motion of abdominal contents and subsequent chest expansion were not observed in the GHBMC. Updates to the GHBMC M50-O towards improved thorax kinematics and mobility of abdominal organs should be considered to replicate PMHS characteristics more closely. [ABSTRACT FROM AUTHOR]

This study examines the optimal authorization strategy for an original equipment manufacturer (OEM), the optimal distribution channel choice for a platform, and their interactions. We developed four models based on the OEM's two strategy choices — authorization and non-authorization strategies, and the platform having two distribution channels for refurbished products: reselling and agency selling channels. Our results indicate that the authorization strategy is optimal for the OEM when consumer's preference for refurbished products is not sufficiently high. Unlike conventional research, an increase in the production cost of a new product leads to different choices for the OEM. Specifically, the OEM prefers a non-authorization strategy in the reselling channel and an authorization strategy in the agency selling channel. Moreover, under the OEM's authorization strategy, the platform always adopts a reselling channel for refurbished products. However, under the OEM's non-authorization strategy, the platform's choice is determined by the commission fee and the production cost of the new product. [ABSTRACT FROM AUTHOR]

Currently, many utility‐scale wind turbine generator original equipment manufacturers are dependent on imported rare earth permanent magnets, which are susceptible to market risks from cost instability. To lower the production costs of these generators and stay competitive in the market, several small wind manufacturers are pursuing continuous improvements to both generator design and manufacturing. However, traditional design and manufacturing methods have yielded marginal improvements in wind power performance. This work presents novel methods to redesign a baseline 15‐kW wind turbine generator with reduced rare‐earth permanent magnets by leveraging cutting‐edge three‐dimensional (3D) printed polymer‐bonded permanent magnets and steel. Symmetric, asymmetric, and multimaterial‐magnet parametrization methods are introduced for shape optimization. We extend the symmetric and asymmetric methods to the back iron in the stator to further investigate the impact and opportunities for performance improvements with lesser active materials. We employ a design‐of‐experiments approach with parametric computer‐aided design for shape generation and evaluate different designs by magneto‐thermal modeling and finite‐element analysis. We use adaptive sampling technique to identify better performing designs with lesser magnet mass, higher efficiency, and lower cogging torque when compared with the baseline generator. Asymmetric pole designs resulted in a magnet mass in the range of 4.77–5.37 kg, which was 27%–35% lighter than the baseline generator, suggesting that a new design freedom exists that can be enabled by advanced manufacturing, such as 3D printing. Shaping the back iron in the stator resulted in material savings in electrical steel of up to 14.62 kg, which was 20% lighter than the baseline stator. We conducted a structural analysis to evaluate an optimized asymmetric rotor design from the point of view of mechanical integrity and air‐gap stiffness. The magnetically optimal shape profile was shown as having a positive impact on the radial stiffness, and an optimal solution was discovered to reduce the structural mass by nearly 30 kg, which was 29% lighter than the baseline. [ABSTRACT FROM AUTHOR]

This study focuses on the optimal pricing and product refurbishing decisions of an original equipment manufacturer (OEM) and a retailer in a supply chain. The OEM sells the new product through a retailer, which serves as a reseller or selling agency, and then chooses whether to provide the refurbished product to consumers. By constructing four models, we obtain the following results. First, we show that the OEM and the retailer always prefer to sell a refurbished product as a monopoly. Second, competing refurbishments leads to a prisoner's dilemma in which both parties suffer greater losses compared to the no refurbishment scenario. This implies that competing refurbishments, except for product cannibalization, hinder the refurbishing industry. Finally, with different refurbishers, the OEM has different preferences for a new product's selling format. However, when the retailer serves as the sole refurbisher, the OEM always prefers agency mode. [ABSTRACT FROM AUTHOR]

In recent years, the development of a circular economy of plastic products in the automotive industry has been pursued by original equipment manufacturers (OEMs) not only due to strategic premises by the European Commission but also due to an increasing demand by customers. To achieve a circular economy, high-quality recyclates are needed. However, in the current situation, there is a discrepancy between the low-quality recyclate that is available on the market and the high-quality recyclate that is demanded by manufacturers. To increase the quality of recyclate on the market, a standardized process to reward a 'design-for-recycling' approach at the product development stage is needed. This paper proposes an allocation method that takes into account material compositions and common recycling processes and incentivizes the preservation of high-quality grades of recyclate based on grade purity. [ABSTRACT FROM AUTHOR]

The rapid development of B2B has brought about fierce competition among suppliers, and how to gain customer attention and improve performance has become a common concern in academia and industry. This study examined the drivers and mechanisms of B2B performance from an enterprise capability perspective. We collected transaction and enterprise data from 325 suppliers on Alibaba 1688 platform and constructed a structural equation model (SEM). Results showed that supplier service capability, logistics capability, and production capacity all positively impacted B2B performance through the mediating role of customer attention. In addition, we found that service and logistics capabilities are more critical for attracting customer attention for Original Equipment Manufacturer (OEM) suppliers than for non-OEM suppliers. The findings contribute to understanding B2B commerce and provide constructive directions for B2B suppliers to improve their performance. [ABSTRACT FROM AUTHOR]

The number and rate of wildlife strikes continue to increase worldwide. More than 30 years of wildlife strike data indicate that approximately 92% of wildlife strikes for commercial aircraft occur at or below 3500 ft above ground level. Since urban air mobility (UAM) operations are envisioned to carry cargo and passengers up to an altitude of 4000 ft above ground level, UAM operations will face increased exposure to wildlife strike risks throughout their operations. Moreover, the comparatively small size of UAM aircraft, proposed cruising speeds of up to 170 kt, and quieter electric engines are expected to reduce opportunities for threat perception and evasive maneuvers by aircraft operators and wildlife. This paper presents how well-established wildlife strike prevention measures can be adapted to meet the needs of UAMoperations and how, with new technology, original equipment manufacturers (OEMs), regulatory agencies, aircraft operators, communities, airspace managers, and vertiport operators can work together to enhance safety. [ABSTRACT FROM AUTHOR]

Engineering projects for complex technical systems such as automobiles demand extensive requirement specifications and corresponding hierarchy levels in system architectures. Especially when considering emergent phenomena, such as total weight or aerodynamics, a closely networked collaboration of discipline‐specific and cross‐disciplinary roles is required. Further, in large organizations with a group structure, resulting functional and non‐functional contents need to be managed by distinct Systems Engineering roles. For example, the role "property manager" takes care of achieving overarching product properties, such as weight or aerodynamics, which cannot be directly fixed, but result from many specifications. This paper proposes new Systems Engineering roles and their application in a German Original Equipment Manufacturer (OEM). For validation, the roles have already been applied in everyday engineering projects at the OEM. The concept proved to be indispensable and transferable to other Systems Engineering projects. [ABSTRACT FROM AUTHOR]

Purpose: In this paper, we investigate the coevolution of the supply network and procurement strategies in the context of semiconductors and electronics for the automotive industry over 3 decades. We aim to explain how procurement strategy interrelates with changes in supply network structure and what the implications of a hub-centric structure network structure are for procurement in supply. Design/methodology/approach: We collected in-depth primary and secondary data that stretched back to 1996 from a leading automotive European original equipment manufacturer (OEM) and its network. Using social network analysis (SNA), we identified OEMs' procurement focus and mapped the evolution of the supply network, the links in the network, and the environmental forces impacting the strategies and the network. Findings: Our findings describe the supply network for semiconductor and electronic components to the automotive industry. The findings suggest that a focus on cost can lead to a Tier 1-centric network structure with many tiers that can fail to assure supply or capture innovation when the external environment is marked by high uncertainty. In such situations, increasing complexity by creating more links in the network can improve transparency and contribute to supply assurance and innovation. Practical implications: The findings indicate that managers should consider the role of the supply network in selecting their strategy to attain objectives of cost, innovation, and supply assurance. Originality/value: This paper presents empirical-based insights into the automotive semiconductor and electronic component supply chain (SC), the unexpected implications of hub-centric supply networks, and the use of SNA in the SC in context. [ABSTRACT FROM AUTHOR]

The supply chain consisting of an original equipment manufacturer (OEM) and a downstream retailer encounters vertical competition along with two‐sided competition from a third party remanufacturer (3PR). The two‐sided competition refers to competition in both recycling and sales. We investigate the recycling investments by the OEM and retailer in diverse vertical structures. Our findings indicate that cooperative investment is optimal when either the OEM or retailer is the Stackelberg leader, but neither party is willing to invest in recycling when they are in vertical Nash. The experiments reveal that the OEM, acting as the Stackelberg leader, and implementing the cooperative investment strategy, yields better economic and environmental benefits. [ABSTRACT FROM AUTHOR]

This study investigates the competitive issues of the newsvendor problem with product substitution under the carbon cap-and-trade system. Building on existing research, this paper introduces the carbon cap-and-trade system under uncertain market demand and considers that the original equipment manufacturer (OEM) can choose to procure raw materials from the contract manufacturer (CM), with both final products being substitutable. Furthermore, we explore the different substitution relationships between OEM and CM products under both pure competitive and co-opetitive modes. For this problem, decision models are developed for various scenarios, and optimal solutions satisfying given conditions are provided. We find that in one-way substitution, under pure competition, an increase in the OEM's (or CM's) green investment and substitution rate only leads to an increase in OEM's (or CM's) yields, while an increase in the OEM's (or CM's) green investment does not necessarily reduce CM's (or OEM's) yields. In the co-opetitive mode, an increase in the substitution rate and green investments of both manufacturers may lead to an increase in the yields of both manufacturers. Furthermore, an increase in carbon trading prices does not necessarily inhibit the manufacturer's yields. Moreover, we find that under the same competition mode, under certain conditions, two-way substitution between OEM and CM can bring better profits to both manufacturers and the entire supply chain. When the two modes are in the same substitution scenario, and the CM cannot substitute for the OEM, the optimal decisions and total supply chain profits of the two modes are equal. Finally, through numerical analysis, we find that neither mode is necessarily optimal when CM can substitute for OEM. Additionally, it is observed that when the same mode is in different substitution scenarios, total supply chain profits may be enhanced in the presence of product substitution. [ABSTRACT FROM AUTHOR]

The article offers information on optimizing supplier management by directly sourcing materials to ensure high-quality, cost-effective production. Topics discussed include supplier selection processes; categorization and risk assessment; and also mentions about the importance of ongoing monitoring and evaluation to maintain product quality and regulatory compliance.

This research investigates growth inhibitors for smart services driven by condition‐based maintenance (CBM). Despite the fast rise of Industry 4.0 technologies, such as smart sensoring, internet of things, and machine learning (ML), smart services have failed to keep pace. Combined, these technologies enable CBM to achieve the lean goal of high reliability and low waste for industrial equipment. Equipment located at customers throughout the world can be monitored and maintained by manufacturers and service providers, but so far industry uptake has been slow. The contributions of this study are twofold. First, it uncovers industry settings that impede the use of equipment failure data needed to train ML algorithms to predict failures and use these predictions to trigger maintenance. These empirical settings, drawn from four global machine equipment manufacturers, include either under‐ or over‐maintenance (i.e., either too much or too little periodic maintenance). Second, formal analysis of a system dynamics model based on these empirical settings reveals a sweet spot of industry settings in which such inhibitors are absent. Companies that fall outside this sweet spot need to follow specific transition paths to reach it. This research discusses these paths, from both a research and practice perspective. Highlights: Condition‐based maintenance (CBM)‐driven smart services have become technically much more feasible and affordable through the fast rise of Industry 4.0 technologies, such as smart sensoring, internet of things, and machine learning (ML), and yet such smart services have failed to keep pace with this rise.A key CBM‐specific complication for service growth is that, in order to reach high‐quality performance of such smart services, the ML‐algorithms that drive them need significant numbers of equipment failures to learn from.Such failure data may be hard to obtain for OEMs, either because certain components fail to often (and hence are replaced, making the failure data obsolete) or too rarely (making the time needed to collect failure data very long).Also, customers may be very much reliability focused (leading to much preventive maintenance and so few failures) or not sufficiently reliability focused (leading to much unmonitored corrective maintenance and low interest in advanced services such as CBM).The sweet spot for CBM smart services therefore lies somewhere in the middle, with both a fair amount of component failures and fairly strongly reliability‐oriented customers. [ABSTRACT FROM AUTHOR]

Background: Increased maritime trade has led to a surge in drayage operations, causing congestion and environmental issues in port areas. Truck Appointment Systems (TASs) are commonly used to manage truck arrival rates, yet transparency and equity in slot allocation remain problematic, fostering distrust between Licensed Motor Carriers (LMCs) and Marine Terminal Operators (MTOs). Methods: This study proposes a polycentric approach to improve truck scheduling and ensure that those impacted by decisions are involved in the decision-making process. A single-round auction mechanism focused on optimizing the truck hauling process through a pricing policy that promotes sincere bidding is introduced. The proposed approach employs an optimization strategy to achieve equitable coordination in truck synchronization through means of adaptable capacity management. Results: Numerical experiments assessing scenarios of noncollaborative behavior against partial collaboration between MTOs and LMCs demonstrate the effectiveness of the proposed approach in enhancing user satisfaction and terminal conditions for a case study focused on a medium-sized terminal. Collaboration between trucking companies is shown to increase utility per monetary unit spent on slot acquisition. Conclusions: The polycentric strategy offers a solution to TAS limitations by ensuring stakeholder participation with respect to flexibility and transparency by ensuring that those impacted by decisions are involved in the decision-making process. [ABSTRACT FROM AUTHOR]

This paper considers an outsourced supply chain comprising a contract manufacturer (CM), an original equipment manufacturer (OEM) and an online platform. In addition to providing contract manufacturing services to the OEM, the CM enters the market using the customer‐to‐manufacturer (C2M) strategy. Two baseline models and four encroachment models with different selling modes are modeled to explore the interaction among CM encroachment, selling modes and the C2M strategy. We find that the CM will always encroach if brand substitution is sufficiently high. However, the CM will still encroach despite brand substitution being low if the platform charges the OEM a high commission rate in Scenario PR. The results also show that the CM may increase or decrease the wholesale price charged to the OEM according to his dependence on the OEM channel and direct channel. Finally, we find that after CM encroachment, the OEM is worse off, while the platform may be better or worse off. The profits of the CM, OEM, and platform decrease if customers are more concerned about production flexibility. Our work provides guidance for CM encroachment from the perspective of channel choice and product strategy and offers managerial insights into C2M practice. [ABSTRACT FROM AUTHOR]

This research aims to aid original equipment manufacturers (OEMs) to model, analyze, evaluate, and benchmark potential design and manufacturing suppliers based on respective product engineering teams' efficiencies. The product engineering efficiency in this study is modeled in terms of product engineering-related attributes such as commercial lead time, number of parts, number of green features, number of end products developed, and so forth. Essentially, these parameters capture more complex interactions than simple traditional supplier selection criteria such as cost, quality, delivery, and flexibility. Due to the presence of information uncertainty in terms of bounds related to the suppliers' related parameters, a number of data envelopment analysis (DEA) efficiency measurement models have been deployed. The proposed decision support system is novel because it models both the self-assessment type and cross-efficiency type using DEA such that maximum discrimination can be achieved amongst suppliers in the presence of interval data. The study is demonstrated for ten different sheet-metal cabin suppliers. Comparison with some well-known, relevant methods is also carried out to illustrate the validity of the proposed method. The research can specifically help supply chain managers to align the evaluation of potential suppliers with their firm's commercial considerations in the presence of information uncertainty. [ABSTRACT FROM AUTHOR]

Early cost estimation is a decisive value driver in the product development process in manufacturing industries. Machine learning offers new intelligent methods to support traditional cost calculation processes. While traditional research on intelligent cost estimation focuses on machine learning regression or classification models, we propose a new approach based on interlocking deep learning methods. In this paper we investigate the applicability of deep learning techniques, focusing on image recognition and deep learning regression as well as autoencoding to estimate product costs of circuit boards to be purchased. We create and evaluate deep learning models using real-world data from an original equipment manufacturer (OEM). Our findings suggest that deep learning models can streamline cost calculation and estimation processes while deep learning object recognition-based cost estimation outperforms autoencoding techniques. This research is designed to be transferable to other cost estimation projects. [ABSTRACT FROM AUTHOR]

For weight reduction, multi-material designs comprising metal and fiber-reinforced plastic (FRP) components in vehicle body structures have been increasingly used. However, the commonly used resistance spot welding (RSW) technology for car body assembly cannot be employed to join sheet metal and FRPs, limiting the use of FRPs. To solve this problem, a novel resistance insert spot welding (RISW) technique was developed in this work for RSW of steel parts and FRP structure parts made by injection molding. Small inserts were developed by using finite element method and experiments that may be welded to different micro-alloyed and dual-phase sheet steels using the projection welding method. The usual flange width of original equipment manufacturers could be kept unchanged. Using the developed insert and welding parameters, the maximum temperature in the FRPs surrounding the inserts was limited to 255 °C, minimizing the damage to polyamide 6 (PA6) material (with 40 wt% glass fiber). A weldability range between 2.5 and 7 kA could be achieved. The joining strength of RISW between a micro-alloyed HC340 steel in 0.75 mm and 1.5 mm thickness and a 2.5 mm/3.0 mm PA6-GF40 material is 20 to 80% higher than self-piercing riveting (SPR). For high-speed loading, RISW strength increases by 39 to 56% further. Finally, RISW was successfully applied to an FRP–steel roof-frame sub-assembly that consists of 19 simultaneously integrated inserts, achieving 10% weight reduction. [ABSTRACT FROM AUTHOR]

The production and personal use of passenger vehicles contribute significantly to greenhouse gas (GHG) emissions, making personal transport a major contributor. In response to increasing pressure from regulators and consumers to lower emissions, original equipment manufacturers (OEMs) have introduced alternative powertrains, such as battery electric vehicles (BEVs). To assess the economic and environmental feasibility of BEVs, OEMs conduct various life cycle assessment (LCA) approaches as part of their internal management practices. However, the public presentation of their results is often ambiguous and of unverifiable quality. This study conducts a review of sustainability impact reporting using the GREET model, which is based on the total vehicle life cycle. The paper provides a summary of the input data requirements for validating emissions from both the fuel and vehicle cycles as part of the proposed model. The availability of the model components was tested against actual public corporate environmental, social and governance reporting disclosures of the largest global automotive OEMs, indicating a deficit in the public presentation of essential sustainability information. The implications of the research suggest that LCA models could benefit sustainability accounting by incorporating proper tagging during accounting practices and taking advantage of digital accounting and reporting practices such as the extensible business reporting language (XBRL). By further developing the model, sustainability reporting can benefit from its structure and workflow, thus ensuring improved information validity for stakeholders. [ABSTRACT FROM AUTHOR]

• Identification of the most influencing factor (Mn) for the sludge yield in Mg-Al alloys. • Intermetallic size in the sludge determined primarily by the holding temperature as well as the Al and Mn contents. • Establishment of sludge factors for Mg alloys with multivariate linear regression analyses; and. • Sludge factor equations making the sludge yield and intermetallic size in Mg-Al alloys predictable, which can avoid sludge buildup in holding crucibles, hard spots in cast components, reduced fluidity of liquid metal to flow into a die during casting. Intermetallic formation in sludge during magnesium (Mg) melting, holding and high pressure die casting practices is a very important issue. But, very often it is overlooked by academia, original equipment manufacturers (OEM), metal ingot producers and even die casters. The aim of this study was to minimize the intermetallic formation in Mg sludge via the optimization of the chemistry and process parameters. The Al 8 Mn 5 intermetallic particles were identified by the microstructure analysis based on the Al and Mn ratio. The design of experiment (DOE) technique, Taguchi method, was employed to minimize the intermetallic formation in the sludge of Mg alloys with various chemical compositions of Al, Mn, Fe, and different process parameters, holding temperature and holding time. The sludge yield (SY) and intermetallic size (IS) was selected as two responses. The optimum combination of the levels in terms of minimizing the intermetallic formation were 9 wt.% Al, 0.15 wt.%Mn, 0.001 wt.% (10 ppm) Fe, 690 °C for the holding temperature and holding at 30 mins for the holding time, respectively. The best combination for smallest intermetallic size were 9 wt.% Al, 0.15 wt.%Mn, 0.001 wt.% (10 ppm) Fe, 630 °C for the holding temperature and holding at 60 mins for the holding time, respectively. Three groups of sludge factors, Chemical Sludge (CSF), Physical Sludge (PSF) and Comprehensive Sludge Factors (and CPSF) were established for prediction of sludge yields and intermetallic sizes in Al-containing Mg alloys. The CPSF with five independent variables including both chemical elements and process parameters gave high accuracy in prediction, as the prediction of the PSF with only the two processing parameters of the melt holding temperature and time showed a relatively large deviation from the experimental data. The Chemical Sludge Factor was primarily designed for small ingot producers and die casters with a limited melting and holding capacity, of which process parameters could be fixed easily. The Physical Sludge Factor could be used for mass production with a single type of Mg alloy, in which the chemistry fluctuation might be negligible. In large Mg casting suppliers with multiple melting and holding furnaces and a number of Mg alloys in production, the Comprehensive Sludge Factor should be implemented to diminish the sludge formation. [ABSTRACT FROM AUTHOR]