SC Network Research Articles

Assessment of awareness levels towards additive manufacturing best practices in transforming traditional manufacturing: A case study in Ethiopian context

The main objective of this study is to assess the awarness levels of acadamic staffs and industry experts towards the best practices of additive manufacturing (AM) in transforming traditional manufacturing (TM) in local context. The study used closed ended questionnaires with 1-5 liker scales to collect secondary data from the respondents. The collected data were analyzed using descriptive statistics (frequency and percentage) by using SPSS v20 software. The findings of this paper identified ten (10) AM best practice benefit factors (Resource consumption benefit factor, Waste management benefit factor, Pollution control benefit factor Material utilization benefit factors, Design optimization benefit factor, Manufacturing flexibility best practice factors, SC flexibility benefit factors, SC network improvement benefit factor, Cost reduction benefit factors, Ability of changing customer demand benefit factors) in transforming traditional manufacturing in local context. Among the eight AM best practices both academic staffs and industry experts have common awareness level on five factors. In addition, the findings of the study showed that 49% of academic staffs and 37% of industry experts have good awarness levels towards the identified AM best practices in transfornig traditional manufacturing. Based on the findings of this study conceptual framework was developed for future research work to quantitatively investigate the effects of AM best practices on traditional manufacturing performmance.

Research on Metallurgical Saw Blade Surface Defect Detection Algorithm Based on SC-YOLOv5

Under the background of intelligent manufacturing, in order to solve the complex problems of manual detection of metallurgical saw blade defects in enterprises, such as real-time detection, false detection, and the detection model being too large to deploy, a study on a metallurgical saw blade surface defect detection algorithm based on SC-YOLOv5 is proposed. Firstly, the SC network is built by integrating coordinate attention (CA) into the Shufflenet-V2 network, and the backbone network of YOLOv5 is replaced by the SC network to improve detection accuracy. Then, the SIOU loss function is used in the YOLOv5 prediction layer to solve the angle problem between the prediction frame and the real frame. Finally, in order to ensure both accuracy and speed, lightweight convolution (GSConv) is used to replace the ordinary convolution module. The experimental results show that the mAP@0.5 of the improved YOLOv5 model is 88.5%, and the parameter is 31.1M. Compared with the original YOLOv5 model, the calculation amount is reduced by 56.36%, and the map value is increased by 0.021. In addition, the overall performance of the improved SC-YOLOv5 model is better than that of the SSD and YOLOv3 target detection models. This method not only ensures the high detection rate of the model, but also significantly reduces the complexity of the model and the amount of parameter calculation. It meets the needs of deploying mobile terminals and provides an effective reference direction for applications in enterprises.

The impact of green human resource management on green pharmaceutical supply chain management practices

Today's competition is among supply chains rather than enterprises as independent actors. Additionally, the success of the actors within the SC network, through the improvement of the global performance, depends on how well they handle the growing environmental problems. For this reason, much attention is given to the greening concept. This paper aims to investigate the Green Human Resource Management (GHRM) impact on Green Supply chain Management (GSCM) in a strategic sector, namely the pharmaceutical sector. Our interest to deal with this issue was aroused by the fact that there are no studies exploring the causality relationships in the pharmaceutical sector in Saudi Arabia. Based on deductive methodology, a questionnaire has been developed. A research sample included 109 pharmaceutical companies operating in KSA. The results highlight a significant impact of GHRM on GSCM practices. In other words, training and performance appraisal, recruitment, and eco-behavior-based rewards influence GSCM practices positively. Based on the results, the study provides new theoretical insights and practical suggestions.

SUPPLY CHAIN PERFORMANCE EVALUATION MODELS: A LITERATURE REVIEW

Our structured literature review reveals the current state-of-the-art supply chain performance evaluation models (SCPEMs) from the last 21 years of research. Seventy related papers from the 2000 to 2021 time period were found to contribute by using ISI and SCOPUS databases. This paper has classified SCPEMs in terms of focus area and the perspective considered (financial and non-financial). With the analysis, these models’ applicability in today’s business environment pinpointed the most usable models and their current shortcomings. Findings disclose current SCPEMs limitations and misalignments with the emerging disruptive technologies observed in today’s supply chains. Given the findings, this study has highlighted the lack of overall supply chain performance evaluation and the failure to underline the underperforming decision criteria in the SC network. Therefore, to tackle these gaps, the authors have suggested visibility, leagility, collaboration, digitalization, sustainability, and integration as SCM characteristics to be considered in the future when developing a novel SCPEM. Finally, this study can be used as guidance for future studies.

Modeling the supply chain finance (SCF) barriers of Indian SMEs using BWM framework

PurposeThe presence of barriers in the supply chain finance (SCF) of small and medium enterprises (SMEs) cripples the productivity and efficiency of SMEs and makes it challenging to execute strategies. SCF barriers can be internal and external which tend to impede the desired performance and profitability of the SMEs. Therefore, the purpose of this paper is to discern the possible SCF barriers and analyze the criticality of the barriers to understand how they impact on the SMEs market of India.Design/methodology/approachThis study proposes a novel hybrid approach called best worst method (BWM) to evaluate the discerned barriers. BWM technique is espoused to appraise the SCF barriers, so that the decision-makers can rationally comprehend the reason behind dominance of one barrier over other. Although such an assessment may possibly vary for different industries, that is why proposed approach is generic in nature and can be applied in real-world cases. The robustness of the suggested model is also assessed through sensitivity analysis.FindingsSCF barriers are identified through extensive literature review and inputs from the industry. The results derived through BWM approach concludes that the “Financial Barriers” are censorious and foremost inhibitors for SMEs to flourish, therefore, require special attention by the top management. Likewise, “Supply and Suppliers Barriers” are ranked second, conversely, “Market and Policy Related Barriers” are found least critical in nature in SMEs of India.Research limitations/implicationsThis work is specific to SCF barriers and other barriers have not been touched upon. The study is based on expert panel opinion for seeking information which is restricted to Indian context, as the members of the expert panel belong to same geography.Practical implicationsThis research could aid decision-makers and strategists to comprehend the deep-rooted initiatives to achieve a comprehensive implication of SCF across SC network. By assessing SCF barriers, this study helps SMEs to understand their shortfalls and in answering the pertinent question of how to gain excellence in this intensely competitive market.Originality/valueSMEs are considered as engines of economic development worldwide. India too is striving for increasing the growth and development of SMEs in every aspect, to gain operational excellence, to make profits or employment generation but presence of SCF barriers makes it difficult to achieve this in Indian SMEs. Therefore, it is imperative to analyze the criticality of the SCF barriers to understand how they impact on SMEs market of India. The paper illustrates the modeling of SCF barriers among SMEs using BWM approach, exhibiting how comprehending barriers can improvise productivity and efficiency of the SCs in SMEs.

The effect of supply chain quality management on supply chain performance: the indirect roles of supply chain agility and innovation

PurposeThe current study seeks to investigate how supply chain quality management (SCQM) and supply chain agility (SCA) and innovation (SCI) have an impact on supply chain performance (SCP) and how SCQM affects SCP through the mediating role of SCA and SCI capabilities.Design/methodology/approachIn line with the research objective, a quantitative model was applied, and a multi-item survey questionnaire was developed to collect primary data. A random sample of 284 manufacturing firms belonging to different industries was used. The measurement model was assessed for validity and reliability, and satisfactory levels of these tests were demonstrated. Research hypotheses were examined using structural equation modeling (SEM).FindingsThe results of the current study have significant implications in regard to the further improvement of SCP through SCQM. The study also found that SCQM plays a key role across the entire SC network in facilitating and developing SCA and SCI capabilities. The remarkable findings of the current study revealed the indirect effect of SCQM on SCP through SCA and SCI. These results broaden the work of previous studies which identified the positive effects of SCQM on performance by providing meaningful insights into SCQM's role in promoting SCA and SCI capabilities, which, in turn, further improves SCP.Originality/valueThis study addresses a gap in the literature concerning the effect of SCQM on SCP. In addition, it is the first study, to the best of the researchers' knowledge, to explore the role of two major SC capabilities, namely, SCA and SCI on the SCQM–SCP relationship. Moreover, the present study addresses a questionable issue in the literature regarding practices that conceptualize SCQM. Several studies confuse SCQM practices with internal quality management (QM) practices. This study defines SCQM as consisting of collaborative QM practices with external SC members and proposes five related practices for measuring SCQM.

The Information System Management and Its Infrastructure for Supply Chain Management as Antecedents of Financial Performance

A model is presented in this paper to provide understanding of the supply chain integration and supply chain information practices' impact on the manufacturing industries. The supply chain information practices play a crucial role in sharing information between the members of SC network. Thus, it is important to develop a comprehensive understanding of the differences and similarities among ISI and information management. It will allow firms to systematically evaluate and carefully choose the information strategy. The empirical findings of this research offer essential and interesting insights about what role SCI, supply chain information and Supply chain ISI play in determining Malaysia's financial performance. The theoretical gaps addressed in this study are of significant importance, since a little empirical evidence is available regarding system infrastructure and supply chain information management's effectiveness. This research provides further paths of exploring system infrastructure and information management, thereby defining the manufacturing industries' next step in SCM struggle i.e. modifying total integrated SC principle in other manufacturing firms. The Resource-based theory discovered organizational resources as an essential organizational success ingredient. Therefore, in order to recognize its potential value, internal resources, for instance, information system and management must be fully utilized.

Mutational analysis of >14,000 NGS tests from community oncology practices: The Sarah Cannon molecular landscape.

26 Background: Utilization of NGS-based testing for patients in community oncology settings continues to grow. A comprehensive analysis of the molecular landscape of > 14,000 patients with commercial tissue-based and plasma-based NGS (tbNGS and pbNGS) testing from Sarah Cannon’s (SC) network of community oncologists between 2012 and 2018 was performed. These data aid clinical trial design/feasibility and identify rare and actionable mutations in the community oncology setting. Methods: Medical Oncologists in the SC network ordered NGS-based molecular profiling for their patients as standard of care. Data from multiple commercial vendors starting in 2012 were harmonized and analyzed. Results: On average, tbNGS (n = 8938) and pbNGS (n = 5419) tests revealed 14 and 4 mutations/sample, respectively. The top 10 mutated genes from both tbNGS and pbNGS - tests are in the table. The most predominant mutation-types detected were SNVs in both tbNGS and pbNGS tests, and gene amplifications were detected in ~40% of tbNGS and ~22% of pbNGS tests. MET amplifications (range: 2 - 40 copies (pbNGS) and 6 - 82 copies (tbNGS)) and ERBB2 amplifications (range: 2.1 - 90.2 copies (pbNGS) and 4 - 293 copies (tbNGS)) were detected in 1.6% (MET-tbNGS) and 4.6% (MET-pbNGS) and 4.2% (ERBB2-tbNGS) and 2.69% (ERBB2-pbNGS) of patients, respectively, and informed clinical trial enrollment. Of the fusions detected, 28 NTRK rearrangements were detected (NTRK1 – 16, NTRK2 – 5, NTRK3 – 7) by tissue-based testing and 3 (NTRK1) fusions were detected by plasma-based tests. Conclusions: These data describe the mutational landscape of NGS tests ordered within community oncology practices. SC’s data infrastructure links NGS-based testing data and clinical data to support real world evidence research, and highlights the need for healthcare IT systems to marry clinical and genomic data for clinical decision support and clinical research. [Table: see text]

Enhanced Rheological Properties of PLLA with a Purpose-Designed PDLA-b-PEG-b-PDLA Triblock Copolymer and the Application in the Film Blowing Process to Acquire Biodegradable PLLA Films.

The inadequate rheological properties limit the film blowing process of biodegradable polylactic acid (PLA), thus hindering its potential application in environmentally friendly packaging films and mulch films. Herein, biodegradable polyethylene glycol (PEG) and d-lactide were used to synthesize three kinds of poly-d-lactic acid (PDLA)-b-PEG-b-PDLA (DPD) triblock copolymers, and their effects on stereocomplex (sc) structure formation and rheological properties of the composites were studied. The results showed that the poly l-lactic acid (PLLA)/DPD4k sample introduced the highest sc content, storage modulus, and complex viscosity value compared with PLLA/DPD2k and PLLA/DPD10k at the same loading condition, indicating that the PEG4k chains can better accelerate the formation of a sc network between DPD4k and the PLLA matrix. The introduction of 10 wt % DPD4k also resulted in about 38 times longer relaxation time and a strain-hardening behavior during the steady biaxial extension of PLLA. At last, the continuous film blowing process was successfully conducted in the PLLA/DPD4k composites, which acquired a stable blow-up ratio of 3.07. On the basis of the above results, the soft chain-grafted PDLA copolymer may provide a novel method for film blowing of biodegradable PLA.

Mutational analysis of >14,000 solid tumor NGS tests from community oncology practices: The Sarah Cannon molecular landscape.

e18065 Background: Utilization of NGS-based testing for patients in community oncology settings continues to grow. A comprehensive analysis of the molecular landscape of > 14,000 patients with commercial tissue-based and plasma-based NGS (tbNGS and pbNGS) testing from Sarah Cannon’s (SC) network of community oncologists between 2012 and 2018 was performed. These data aid clinical trial design/feasibility and identify rare and actionable mutations in the community oncology setting. Methods: Medical Oncologists in the SC network ordered NGS-based molecular profiling for their patients as standard of care. Data from multiple commercial vendors starting in 2012 were harmonized and analyzed. Results: On average, tbNGS (n = 8938) and pbNGS (n = 5419) tests revealed 14 and 4 mutations/sample, respectively. The top 10 mutated genes from both tbNGS and pbNGS - tests are in the table. The most predominant mutation-types detected were SNVs in both tbNGS and pbNGS tests, and gene amplifications were detected in ~40% of tbNGS and ~22% of pbNGS tests. MET amplifications (range: 2 - 40 copies (pbNGS) and 6 - 82 copies (tbNGS)) and ERBB2 amplifications (range: 2.1 - 90.2 copies (pbNGS) and 4 - 293 copies (tbNGS)) were detected in 1.6% (MET-tbNGS) and 4.6% (MET-pbNGS) and 4.2% (ERBB2-tbNGS) and 2.69% (ERBB2-pbNGS) of patients, respectively, and informed clinical trial enrollment. Of the fusions detected, 28 NTRK rearrangements were detected (NTRK1 – 16, NTRK2 – 5, NTRK3 – 7) by tissue-based testing and 3 (NTRK1) fusions were detected by plasma-based tests. Conclusions: These data describe the mutational landscape of NGS tests ordered within community oncology practices. SC’s data infrastructure links NGS-based testing data and clinical data to support real world evidence research, and highlights the need for healthcare IT systems to marry clinical and genomic data for clinical decision support and clinical research. [Table: see text]

Cardiogenic shock is a rare disease: the dedicated network

Cardiogenic shock (CS) is a rare disease that needs a rapid and multiparameter diagnosis and a timely, aggressive and multidisciplinary goal-oriented treatment. Recently published epidemiological studies and registries underline how SC represents an infrequent clinical entity still burdened by high mortality rates, substantially unchanged over the years. Currently, only few patients with CS are treated with circulatory assistance in dedicated centers. Some consensus documents and expert recommendations emphasize the importance of early diagnosis of CS, immediate pharmacological support, and treatment of precipitating causes, and stress the need for hospitalization in high-volume intensive care centers. The aim of this review is to show the instructions for the creation of a SC network, emphasizing the necessary elements, in agreement with available resources and existing health regulations for giving the same care opportunities to all the patients.

Solid-State NMR Spectroscopy Proves the Presence of Penta-coordinated Sc Sites in MIL-100(Sc).

Advanced solid-state NMR methods and first-principles calculations demonstrate for the first time the formation of penta-coordinated scandium sites. These coordinatively unsaturated sites were shown during the thermal activation of scandium-based metal-organic frameworks (MOFs). A 45 Sc NMR experiment allows their specific observation in activated Sc3 BTB2 (H3 BTB=1,3,5-tris(4-carboxyphenyl)benzene) and MIL-100(Sc) MOFs. The assignment of the ScO5 groups is supported by the DFT calculations of NMR parameters. The presence of ScO5 Lewis acid sites in MIL-100(Sc) explains furthermore its catalytic activity. The first NMR experiment to probe 13 C-45 Sc distances is also introduced. This advanced solid-state NMR pulse sequence allows the demonstration of the shrinkage of the MIL-100(Sc) network when the activation temperature is raised.

A priority-based modified encoding–decoding procedure for the design of a bi-objective SC network using meta-heuristic algorithms

This paper aims at a bi-objective optimization of the multi-periodic multi-product supply chain network design (SCND) problem under uncertainty consisting of manufacturing centers, distribution centers, and customer nodes. The problem is considered as a two-stage transportation model while there are several candidate transportation options for each plant. The supposed uncertainty is related to the services of the warehouses and affects the decision making of the SCND that are critical issues. So, the goal is to make the best decisions to maximize the minimum average percentages of products dispatched for each customer in each period while minimizing the sum of strategic, tactical and operational costs. Since the proposed model is of constrained bi-objective mixed-integer nonlinear programming type, we apply a linear programming metric and goal attainment methods to turn the problem into a single-objective model. Each of two methods is separately embedded in simulated annealing, a genetic algorithm, and an imperialist competition algorithm to solve this bi-objective model by MATLAB™ software. Furthermore, we extend a priority-based encoding–decoding method that leads to feasible solutions. The performance of the proposed algorithms is examined on a set of problem instances. Then, some numerical results are provided to demonstrate the algorithm's effectiveness and efficiency further. For this purpose, we propose Duncan's multi-range test and TOPSIS methods.

Delayed convergence between brain network structure and function in rolandic epilepsy.

Introduction: Rolandic epilepsy (RE) manifests during a critical phase of brain development, and has been associated with language impairments. Concordant abnormalities in structural and functional connectivity (SC and FC) have been described before. As SC and FC are under mutual influence, the current study investigates abnormalities in the SC-FC synergy in RE.Methods: Twenty-two children with RE (age, mean ± SD: 11.3 ± 2.0 y) and 22 healthy controls (age 10.5 ± 1.6 y) underwent structural, diffusion weighted, and resting-state functional magnetic resonance imaging (MRI) at 3T. The probabilistic anatomical landmarks atlas was used to parcellate the (sub)cortical gray matter. Constrained spherical deconvolution tractography and correlation of time series were used to assess SC and FC, respectively. The SC-FC correlation was assessed as a function of age for the non-zero structural connections over a range of sparsity values (0.01–0.75). A modularity analysis was performed on the mean SC network of the controls to localize potential global effects to subnetworks. SC and FC were also assessed separately using graph analysis.Results: The SC-FC correlation was significantly reduced in children with RE compared to healthy controls, especially for the youngest participants. This effect was most pronounced in a left and a right centro-temporal network, as well as in a medial parietal network. Graph analysis revealed no prominent abnormalities in SC or FC network organization.Conclusion: Since SC and FC converge during normal maturation, our finding of reduced SC-FC correlation illustrates impaired synergy between brain structure and function. More specifically, since this effect was most pronounced in the youngest participants, RE may represent a developmental disorder of delayed brain network maturation. The observed effects seem especially attributable to medial parietal connections, which forms an intermediate between bilateral centro-temporal modules of epileptiform activity, and bear relevance for language function.

Leveraging the supply chain flexibility of third party logistics – Hybrid knowledge-based system approach

Nowadays, intensified globalization and consequent competitive pressures have reemphasized the importance of third party logistics (3PL) in managing logistics processes as well as customer and supplier relationships within the supply chain management (SCM). However, 3PL providers and their upstream and downstream parties within the whole chain have usually interacted as disconnected entities in the logistics performance management process. Despite the increased interest in using and improving logistics information systems, the number of researchers investigating the design and implementation of this process in close detail is still very small. This paper proposes an intelligent performance measurement system (K-LPMS) for measuring the performance of 3PL providers and their upstream and downstream supply chain partners. With the help of K-LPMS, 3PL providers are capable to fulfil different customer's supply chain service requirement through accessing the capability of each SC partners and reconfigure SC network. This paper describes the structure of K-LPMS and its features. The results of testing and applying the tool in companies are presented. This paper concludes by discussing the implications of this research for managers, and identifying directions for future research.

Switched network analysis based on final value theorem of Laplace transform

This paper proposes a new method of analysis in the modified nodal analysis of the switched network. In the proposed method, the limit of the switching resistance r for 1/∞ or ∞ is replaced by the limit of the variable “s” of Laplace transform for s 0. Then by applying the final value theorem of the Laplace transform, the solution of the network equation immediately after switching is derived as the limit for t ∞ of the virtual state equation. By this transformation based on the final value theorem of the Laplace transform, the limiting operation of the switching resistance can be transformed into the iterative calculation of the product of the nonsingular matrix, which does not depend on the switching resistance, and a vector. In this new method, the coefficient matrix of the backward Euler method in the numerical integration of the virtual state equation is always nonsingular. This makes it possible to designate the next switching pattern without a particular algorithm, even in the singular problem where the network equation becomes singular for a certain switching pattern. When the state before the switching is the actual solution, as in the SC network, this method can derive the discontinuous solution which jumps from one state to the next state. Since the coefficient matrix of the backward Euler method is always nonsingular, the inverse matrix lemma can be applied to the calculation of the inverse matrix, which can be executed by lowering the order of the matrix from the given matrix to the actual order of the switched pattern.

Elements of four‐port matrix theory as required for sc network analysis

AbstractFour‐port matrix theory is the foundation for various useful methods of analysing switched‐capacitor networks. Thus, for example, signal‐flow graph techniques, the link‐two‐port concept, and nodal computer analysis methods are based on either the four‐port transmission or admittance matrix. In the derivation of these analysis techniques transmission, reverse‐transmission, and transfer matrices are often used, but the relationship between them has not yet been clearly formulated for four‐port networks. In this paper an attempt at formulation and clarification is made. Furthermore, it is shown that, once the considerable simplifications due to the presence of opamps are taken into account, a simple and elegant method of hand analysis for basic SC circuits using a combination of transmission and transfer matrix parameters results.

Direct analysis of stray-insensitive switched-capacitor networks using signal flow graphs

A method for the direct closed-form analysis of switched-capacitor networks using signal-flow graph (SFG) techniques is presented. Although the networks must conform to certain constraints, these include the constraints required for insensitivity to stray capacitance. The method of analysis is noteworthy for its simplicity of use, because it permits the signal-flow graph of a switched capacitor network to be drawn directly by inspection. Arbitrary network functions can then be obtained using signal-flow graph theory. An additional advantage of the method is due to the insight afforded into the functioning of a network by its signal-flow graph. The reverse procedure of synthesizing an SC network by deriving the signal-flow graph corresponding to a given transfer function, and then transforming the SFG into a physical network, is thereby also simplified.

A scaling Pauper's algorithm for SC network analysis

A general approach is presented as regards the frequency-domain analysis of SC networks. At first the scaling property of SC network is discussed. From the scaling property it is pointed out that the SC network can be modeled by an analogue circuit consisting of amplifiers, resistors and capacitors with real constant element values using scaling transformation and bilinear transformation (Pauper's algorithm). Thus the SC network frequency response and sensitivity can be calculated by calling available standard analogue circuit analysis program. The proposed algorithm has the advantage of small computing time in comparison with existing methods.

Analysis of wave switched‐capacitor filters

AbstractFor a special class of switched‐capacitor filters, the wave SC filters, a very efficient analysis method will be given. It is based on a block partitioning technique, i.e. the whole wave SC network is divided into small subnetworks. Only small matrices have to be processed which saves computation time, so that even large wave SC filters can be analysed very fast and with high accuracy. It will also be shown that the methods can be extended for the analysis of other SC networks. Some numerical examples of different wave SC structures will be given.