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Circular economy denotes future sustainability that allows optimum utilization of resources. In the present era of technology, plenty of innovations are happening across the world, and digital manufacturing is one of such innovations. However, there are several barriers which are impeding adoption of digital manufacturing in circular economy environment. The study explores the barriers of digital manufacturing initiatives in a circular economy and develops a methodological model to prioritize the identified challenges for automotive parts manufacturing industry.

Seven categories of challenges namely process, human resources, financial, collaboration, technological, security and leadership challenges were identified from literature and further validated with subsequent discussions with experts from the industry. The study is conducted in two phases, where in the first phase, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique is used to define the priority and importance of seven categories of challenges. In second phase, the barriers are ranked using a Fuzzy Performance Important Index (FPII), taking into account contextual factors associated with the challenges and linked barriers, to determine the extent to which they impede the adoption of digital manufacturing in the sample automotive parts manufacturing company.

The “risk of data security and information privacy in connection with use of external data and protecting customer data” appeared as the most significant barrier to digital manufacturing in circular economy. Furthermore, technological challenges emerged as the most significant category of challenges followed by financial challenges in adoption of digital manufacturing in circular economy.

Identification of the identified barriers and understanding the interrelationships will lead to easier adoption of digital manufacturing in circular economy.

Despite all the potential benefits of implementing Industry 4.0 technologies in manufacturing industries, the adoption thereof is still in nascent phase with significant challenges yet to be overcome to accelerate the pace of adoption. Hence, this study explores the barriers preventing companies from adopting and benefiting from digital manufacturing initiatives and further develops a methodological model.

In 2016, the ISO/TS 16949 quality management standard for the automotive industry evolved to IATF 16949. The update brought new requirements that need to be analyzed before being implemented in organizations. Therefore, the purpose of this article is to propose guidelines to assist organizations in the automotive sector in the implementation of the elements added in the update to the IATF 16949 standard.

To fulfill this objective, the identification and analysis of the elements added in the evolution from ISO/TS 16949 to IATF 16949 was carried out, and four case studies were conducted in Brazilian automotive companies.

The main elements added to IATF 16949 with the update of the standard are the use of process failure mode effects analysis (PFMEA) for risk analysis; the development of a communication channel for employees to report cases of misconduct and non-conformities; procedures for controlling repaired/reworked products and temporary changes; and the inclusion of autonomous maintenance for the full implementation of total productive maintenance (TPM).

The main practical implication/contribution of the research is the proposed guidelines, which can support managers and automotive companies that want to implement, or will go through, the IATF certification process. The article's originality lies in the combination of a theoretical framework and case study analyses to develop the guidelines.

This paper aims to enable the analysts of reliability and safety systems to evaluate the risk and prioritize failure modes ideally to prefer measures for reducing the risk of undesired events.

To address the constraints considered in the conventional failure mode and effects analysis (FMEA) method for criticality assessment, the authors propose a new hybrid model combining different multi-criteria decision-making (MCDM) methods. The analytical hierarchy process (AHP) is used to construct a criticality matrix and calculate the weights of different criteria based on five criticalities: personnel, equipment, time, cost and quality. In addition, a preference ranking organization method for enrichment evaluation (PROMETHEE) method is used to improve the prioritization of the failure modes. A comparative work in which the robust data envelopment analysis (RDEA)-FMEA approach was used to evaluate the validity and effectiveness of the suggested approach and simplify the comparative analysis.

This work aims to highlight the real case study of the automotive parts industry. Using this analysis enables assessing the risk efficiently and gives an alternative ranking to that acquired by the traditional FMEA method. The obtained findings offer that combining of two multi-criteria decision approaches and integrating their outcomes allow for instilling confidence in decision-makers concerning the risk assessment and the ranking of the different failure modes.

This research gives encouraging outcomes concerning the risk assessment and failure modes ranking in order to reduce the frequency of occurrence and gravity of the undesired events by handling different forms of uncertainty and divergent judgments of experts.

The purpose of this paper is to propose and empirically investigate the concept of networking capability (NC) for the management of supplier relationships and their dynamics in order to leverage product innovations. NC in the context of supplier relationships is conceptualized based on dynamic capabilities aimed at relationship initiation, relationship development, and relationship ending. Furthermore, the study tests the interaction of NC with relationship proclivity as an organizational feature, and analyzes latent classes of NC affecting product innovation.

This study brings together prior research on company routines related to inter-firm networking, the dynamic capability approach to strategy, and literature on inter-firm innovation. The study utilizes multiple informant survey data gathered from 156 firms operating in the automotive parts industry in Iran. Data are analyzed with partial least square structural equation modeling, as well as latent class analysis using finite mixture modeling (FIMIX-PLS).

This research provides evidence for the positive influence of NC with respect to supplier relationships on firm product innovation, as well as overall firm performance. Relationship proclivity is shown to amplify this effect. At the same time, the research illustrates that NC may be applied in different combinations in the context of supplier relationship portfolio management. Two mechanisms are tentatively identified: firms using “static optimization” focus mainly on supplier relationship development capabilities, while those using “dynamic optimization” utilize supplier relationship initiation and ending capabilities.

This research focuses on one setting (i.e. the automotive parts industry in Iran). Further studies need to broaden these findings to other industries and countries, specifically those which show a different cultural make-up from Iran. Furthermore, this research indicates the existence of two distinct mechanisms as to how different aspects of NC impact product innovation. While it is reasonable to identify these mechanisms as networking “strategies,” this study does not clarify whether this represents intended strategies by firms or relates to emerging capability patterns.

The study contributes to managerial knowledge by illustrating the need for a dynamic approach with regard to networking-related routines in supplier relationships in the context of product innovation. This study suggests that managers should devote equal attention to strengthening existing supplier relationships as well as to initiating new supplier relationships (e.g. screening for promising partners and signaling firm’s relationship value to attract new counterparts) and managing non-performing supplier relationships (e.g. by developing routines to exit from those supplier relationships).

The paper contributes to a better understanding of dynamic approaches to networking with suppliers and their impact on product innovation from the perspective of the focal firm. It furthermore provides a fine-grained understanding of different latent classes of firms in terms of how they utilize networking capabilities.

The ability of a manufacturing system to respond to customer demand in a timely fashion is widely accepted as a source of competitive advantage. While quick response concepts at system level have been widely discussed in a range of industry sectors, such as textile, electronics and fast moving consumer goods, few studies so far have specifically investigated the responsiveness of the component supply chain. This exploratory study hence aims to reconcile the considerable ambiguity that exists around the concept of supplier responsiveness, supported by an empirical investigation into the automotive parts industry.

The study analyses the responsiveness of first‐tier automotive suppliers in Europe. The research is based on a multi‐method approach comprising of a survey, coupled with in‐depth processing mapping and complimenting interviews of production control staff at a subset of the surveyed companies.

The findings suggest that supplier responsiveness is constrained by both endogenous factors originating from within their own manufacturing operations, as well as exogenous factors related to both their respective up‐stream and downstream tiers. Furthermore, the study highlights how first‐tier suppliers are “squeezed” between demanding vehicle manufacturers on the one hand, and an unresponsive raw material supply base on the other, constraining their overall ability to respond to changing market requirements.

The conclusions derived from this research are bound by the sample these are drawn from, and additional large‐scale analyses are suggested as further research.

While the concept of “responsiveness” has been widely discussed in the supply chain literature, this debate has largely remained in the realms of qualitative description. Few studies have empirically addressed the issue of supply chain responsiveness, and if so, often focused on a subset of factors (e.g. schedule variations) only. In this paper, an holistic approach to responsiveness is adopted that aims at identifying the key variables that impact on supply chain responsiveness, as well as providing quantitative evidence to support these claims.

The paper presents a benchmarking analysis that investigates the efficiency gap in relation to spot welding robots in automotive body shops at foreign and domestic companies in North America. The main purpose of this paper is to determine body shop efficiency improvement opportunities for the domestic companies or the Big Three, therefore reducing the competitive gap and improving business performance.

The following paper is an extension of an earlier dissertation study conducted by EL-Khalil that focused on improving body shop overall efficiency. The Harbour Report was utilized to determine the best in class facilities that must be visited for benchmarking purposes. The data and information presented were obtained from the facilities visited through observations and interviews. The research utilized the corresponding facilities' labs in order to perform measurements and inspect product welding efficiency. The data obtained were a result of a two-year benchmarking study.

The inspection results of spot welds applied on the door flange do not justify the utilization of additional spot welding arm designs and/or robots for the domestic companies. The data presented provide a good opportunity for improving business performance at the body shop Big Three facilities. In order to reduce the current competitive gap, decrease cost, and improve utilization, the Big Three must adopt new strategies (i.e. communization of specific vehicles parts).

The benchmarking study was limited to the aperture area. Researchers are encouraged to test the propositions further on different types of vehicles and different areas of the vehicle body.

Based on the actual findings, this paper presents a case that impacts the improvements of the body shop overall performance in relation to reducing the number of spot welding arm and robot designs at the automotive industry in North America.

The presented gap analysis on body shop spot welding efficiency for automotive companies in North America was not conducted previously. Therefore, the data can be utilized as a benchmark target to drive improvements at the domestic automotive body shops.

This research aims to examine the influences of preceding implementation phases on succeeding phases of business continuity management (BCM) comprising leadership, strategy, planning, application and maintenance.

Data were gathered from 216 automotive parts manufacturers in Thailand. Descriptive statistics were employed to measure the maturity level of BCM implementation components. Path analysis of structural equation modeling was used to test hypotheses.

The study's findings found that the intensity of BCM elements decreased following the implementation phases. Leadership and strategy had the highest mean score, while maintenance had the lowest. Preceding phases had significant positive effects on succeeding phases. The direct impact of leadership on maintenance was much weaker than its indirect impact through strategy, planning and application.

This is one of the first examples of empirical research to investigate the sequential links between preceding and succeeding BCM implementation components. Strategic BCM elements and systematic implementation can improve and sustain BCM in the automotive parts industry in Thailand.

The purpose of this study is to evaluate two supply chain resilience key elements of vulnerability and capability in the automotive industry.

We propose a fuzzy approach for statistical hypothesis testing and analyze two research hypotheses by synthesizing the results of a questionnaire given to 44 companies in the Iranian automotive industry.

The results indicate that the automotive industry in Iran should: (1) resist five elements of vulnerability, i.e. “external pressures,” “sensitivity,” “connectivity,” “supplier/customer disruptions,” and “resource limits,” and (2) embrace nine elements of capability, i.e. “flexibility in order fulfillment,” “capacity,” “efficiency,” “visibility,” “adaptability,” “recovery,” “dispersion,” “organization,” “market position” and “security” to achieve greater resiliency elasticity in the supply chain.

This is the first study on the supply chain resilience vulnerabilities and capabilities in the Iranian automotive industry.

The purpose of this research is to examine the impact of the Toyota Way (TW), TW pillars (i.e. continuous improvement, and respect for people), and TW elements (i.e. challenge, kaizen, genchi-genbutsu, respect, and teamwork) on agile manufacturing (AM) and AM elements (i.e. responsiveness, capability, speed and flexibility).

Data were collected from 216 automotive parts manufacturers. Multiple and linear regressions were used to test the hypotheses.

The study found that overall TW and both pillars have significant effects on overall AM and all AM elements, except for the influence of continuous improvement on speed and flexibility. No individual TW element can improve every AM element. TW and AM are not mutually exclusive. To improve AM, managers should apply TW as a set of integrated technical and personnel elements rather than as isolated elements.

This study is one of the first to hierarchically explore the effects of socio-technical TW, TW's individual pillars and elements on overall AM and each AM element in the automotive parts industry. Findings from this research can be used to develop a socio-technical lean system to be integrated with AM more effectively leading to successful leagile manufacturing.

This study aims to design a reliable multi-level, multi-product and multi-period location-inventory-routing three-echelon supply chain network, which considers disruption risks and uncertainty in the inventory system.

A robust optimization approach is used to deal with the effects of uncertainty, and a mixed-integer nonlinear programming multi-objective model is proposed. The first objective function seeks to minimize inventory costs, such as ordering costs, holding costs and carrying costs. It also helps to choose one of the two modes of bearing the expenses of shortage or using the excess capacity to produce at the expense of each. The second objective function seeks to minimize the risk of disruption in distribution centers and suppliers, thereby increasing supply chain reliability. As the proposed model is an non-deterministic polynomial-time-hard model, the Lagrangian relaxation algorithm is used to solve it.

The proposed model is applied to a real supply chain in the aftermarket automotive service industry. The results of the model and the current status of the company under study are compared, and suggestions are made to improve the supply chain performance. Using the proposed model, companies are expected to manage the risk of supply chain disruptions and pay the lowest possible costs in the event of a shortage. They can also use reverse logistics to minimize environmental damage and use recycled goods.

In this paper, the problem definition is based on a real case; it is about the deficiencies in the after-sale services in the automobile industry. It considers the disruption risk at the first level of the supply chain, selects the supplier considering the parameters of price and disruption risk and examines surplus capacity over distributors’ nominal capacity.