Electronic Supply Research Articles

Aligning Performance Measurement Systems across the Supply Chain: Evidence from Electronic Components Suppliers

ABSTRACTSuccessful interorganizational governance requires practices that reduce information asymmetry between supply chain partners and foster collaborative activities. We study one potential practice—suppliers aligning their performance measurement systems with their largest customer’s performance priorities. Using survey data collected from face-to-face interviews with executives from over 1,000 electronic components suppliers, we find that suppliers with greater customer-supplier information asymmetry and higher partner interdependence have performance measurement systems that align more with their largest customer’s performance priorities. These results are particularly apparent when the exchange involves complex components and when the largest customer represents a greater proportion of supplier sales, suggesting that performance measurement system alignment is of greater value in such situations. We conclude that the performance priorities of large customers play a role in shaping suppliers’ management control systems.

Online Energy Management Strategy of the Flexible Smart Traction Power Supply System

The flexible smart traction power supply system (FSTPSS) is a fully electronic traction power supply system (TPSS), which integrates ac-dc–ac traction substations, distributed generation, and hybrid energy storage system (HESS). Compared with the traditional TPSS, the power supply of FSTPSS becomes more diverse, but the randomness of power flow becomes greater. A suitable energy management strategy is needed for FSTPSS to control the power flow of the system. At present, the day-ahead energy management strategy (DAEMS) has been proposed to make an optimal plan for the whole-day operation of FSTPSS, but this energy management strategy does not consider the impact of real-time fluctuation caused by nondeterministic loads or sources on the reliable execution of DAEMS. To solve this problem, this article proposes an online energy management strategy (OEMS) based on long short-term memory (LSTM) network and deep deterministic policy gradient (DDPG) algorithm to counteract the effects of these real-time fluctuations. The proposed OEMS has the advantages of small tracking error, model-free control, and continuous action control. To verify these advantages, a series of comparative simulations is carried out, and the simulation results verify the advantages of the proposed OEMS.

Doing Well by Doing Right

Abstract Richard Locke, Ben Armstrong, Samantha Schaab-Rozbicki, and Geordie Young speculate that COVID-related challenges might lead firms to shift their assumptions about workers in ways that open up new political-economic possibilities, with benefits for workers in safety, compensation, and voice. I am skeptical about the idea of such COVID-induced learning. Drawing on an analysis of the costs of high turnover in the electronics supply chain, however, I argue that more generous assumptions about workers appear to have operational benefits. Understanding those operational benefits might lead firms to be less resistant to demands from workers for the kinds of jobs that Locke and his coauthors celebrate.

Surface Density of Cobalt Single Atoms Manipulating Hydroxyl Radical Generation Via Dual Pathways: Electrons Supply and Active sites

AbstractPhotocatalytic generation of •OH from O3 is an intriguing avenue for aqueous organics degradation due to the high utilization of photogenerated electrons, but ambiguous information about charge transfer and surface‐active sites hinders the optimization of photocatalysts. In this work, a series of cobalt single‐atom catalysts (SACs) anchored on graphitic carbon nitride to improve •OH generation from O3 via electron reduction and catalytic activation dual pathway is synthesized. Various characterization and density functional theory calculations reveal that cobalt single atoms can introduce trap states for holes, which improve the light‐harvesting ability and accelerate the transfer of electrons and holes. Meanwhile, Co single atoms can also act as active sites to accelerate ozone decomposition and produce •OH directly. Particularly, the influence of different surface densities of Co single atoms on photogenerated electron supply and surface reaction is disclosed. A higher density of Co provided more active sites for O3 catalytic activation, but the narrowed distance between oxidation and reduction centers reduces the supply of available electrons by worsening the charge recombination. This work offers an atomic‐level correlation of the isolated metal density and photocatalytic properties, and can scientifically guide the design of high‐performance photocatalysts for organic synthesis and water purification.

Enhanced nutrient removal of agricultural waste-pyrite bioretention system for stormwater pollution treatment

Pyrite as filler applied to bioretention cells has the potential for simultaneous nitrogen and phosphorus removal, but its low electron supply rate cannot adapt to the demand for nitrogen and phosphorus removal under high rainfall intensity and continuous rainfall conditions. In this study, novel pyrite-based bioretention cells with agricultural waste amendment (corn cobs, rice husks, wood chips) were developed, and the pollution removal of each cell was evaluated under simulated complex rainfall conditions. The bioretention cell amended with woodchips achieved significantly higher efficiency and stability for dissolved nutrient removal compared with the pyrite bioretention cell. Its average removal efficiency of nitrate nitrogen, total nitrogen, and phosphate phosphorus was 69.39%, 45.60%, and 60.01% higher than that of the control group. The average chemical oxygen demand (COD) and total iron (TFe) concentrations in the effluent were slightly higher than those from the pyrite bioretention cell but were significantly lower than those from the corn cob and the rice husk-pyrite bioretention cell. Microbiological analysis revealed that the addition of woodchips significantly increased the relative abundance of Thiobacillus (the main functional genus of autotrophic denitrification) and Thauera (the main functional genus of heterotrophic denitrification) in the bioretention cell to 25.17% and 3.06%. The results indicated that woodchips promoted the proliferation of both heterotrophic and autotrophic microorganisms, therefore enhancing the nitrogen removal efficiency of mixotrophic denitrification.

An enterprise network model for understanding and disrupting illicit counterfeit electronic part supply chains

This article analyses several promising policies in the electronic parts industry for disrupting the flow of counterfeit electronic parts. A socio-technical electronic part supply-chain network model has been developed to facilitate policy analysis. The model is used to understand the technical and social dynamics associated with the insertion of counterfeit electronic components into critical systems (e.g., aerospace, transportation, defense, and infrastructure) and to analyze the impact of various anti-counterfeiting policies and practices. This network model is used to assess the effectiveness of mandatory original component manufacturer buyback programs and the debarment of distributors found to provide counterfeit components. In this agent-based model, each participant in the supply chain is modeled as an independent entity governed by its own motivations and constraints. The entities in the model include the original component manufacturers, distributors, system integrators, operators, and counterfeiters. Each of these entities has dynamic behaviors and connections to the other agents. Since time is an integral factor (lead times and inventory levels can be drivers behind the appearance of counterfeits), the simulation is dynamic. The model allows the prediction of the risk of counterfeits making it into an operator’s system and the length of time between relevant supply-chain events/disruptions and the appearance of counterfeits.

Optimizing the Use of Behavioral Locking for High-Level Synthesis

The globalization of the electronics supply chain requires effective methods to thwart reverse engineering and IP theft. Logic locking is a promising solution, but there are many open concerns. First, even when applied at a higher level of abstraction, locking may result in significant overhead without improving the security metric. Second, optimizing a security metric is application-dependent and designers must evaluate and compare alternative solutions. We propose a meta-framework to optimize the use of behavioral locking during the high-level synthesis (HLS) of IP cores. Our method operates on chip's specification (before HLS) and it is compatible with all HLS tools, complementing industrial EDA flows. Our meta-framework supports different strategies to explore the design space and to select points to be locked automatically. We evaluated our method on the optimization of differential entropy, achieving better results than random or topological locking: 1) we always identify a valid solution that optimizes the security metric, while topological and random locking can generate unfeasible solutions; 2) we minimize the number of bits used for locking up to more than 90% (requiring smaller tamper-proof memories); 3) we make better use of hardware resources since we obtain similar overheads but with higher security metric.

Direct electrochemical detection of extracellular nitric oxide in Arabidopsis protoplast based on cytochrome P450 55B1 biosensor

Cytochrome P450 55B1(CYP55B1) from Chlamydomonas reinhardtii reduces nitric oxide (NO) to dinitrogen oxide (N2O) with the electron supply from NAD(P)H in vivo. Here a novel nitric oxide biosensor was developed by immobilized CYP55B1 on the surface of pyrolytic graphite electrode (PGE) by cross-linking with glutaraldehyde (GA) and bovine serum albumin (BSA). The direct electrochemistry of CYP55B1 was realized with the redox peak potential of −0.355 V and −0.385 V and the catalytic reduction peak of NO by CYP55B1 is at −0.85 V at the scan rate of 0.5 V S−1 in pH 7.0 phosphate buffer. The apparent coverage (Γ = 1.43 × 10−11 mol cm−2), the electron transfer rate constant (ks = 17.39 s−1) and apparent affinity to NO (Kmapp = 11.64 nM) of CYP55B1 in GA/BSA film were obtained. The catalytic mechanism of CYP55B1 towards NO with NADH was examined by the biosensor. The linear range of NO detection was investigated by differential pulse voltammetry with the results of 5–50 nM and the detection limit of 0.5 nM (S/N = 3). The selectivity and stability of the electrochemical biosensor were investigated. Furthermore, the CYP55B1electrochemical biosensor was applied to monitor NO release from Arabidopsis protoplasts with the average content of 0.848 fmol per cell under anaerobic condition.

Dual-optimization strategy engineered Ti-based metal-organic framework with Fe active sites for highly-selective CO2 photoreduction to formic acid

Increasing CO2 conversion efficiency over metal-organic framework (MOF) based photocatalysts is of great significance to promote the carbon capture and utilization. In this work, a dual-benefit design strategy is deployed in the synthesis of a new two-dimensional Fe/Ti-BPDC MOF photocatalyst with atomically dispersed Fe sites. This catalyst demonstrated an excellent catalytic performance in the visible-light-driven CO2 conversion to HCOOH, achieving a high yield of 703.9 μmol g-1 h-1 at a selectivity greater than 99.7%. This is attributed to the ‘dual-optimization’ achieved by this catalyst to sustain the supply of photogenerated electrons and to effectively activate CO2. Specifically, the Fe/Ti-BPDC catalyst provides a high proportion of effective photogenerated electrons for the CO2 photocatalysis process via a unique electron transfer mechanism. Meanwhile, the strong O/Fe affinity between CO2 and atomically dispersed Fe active sites not only enables a fast CO2 activation, but also dictates the intermediate reaction pathways towards high HCOOH selectivity.

Cu nanoclusters activating ultrafine Fe3N nanoparticles via the Mott-Schottky effect for rechargeable zinc-air batteries

The rational design and synthesis of cost-effective bifunctional oxygen electrocatalysts is crucial for the large-scale commercial applications of rechargeable zinc-air batteries. In this work, the CuNCs/Fe3N-NPCF catalyst was constructed by anchoring the metallic Cu/Fe3N ensembles with different sizes onto N-doped porous carbon nanosheets. The Mott-Schottky heterostructure formed by Fe3N nanoparticles and its surrounding Cu clusters enabled spontaneous electron transfer, which speeded up the electron supply from active sites to various oxygen intermediates. The electrophilic region on Cu side and the nucleophilic region on Fe3N side improved the adsorption of O2 and OH-, respectively. The CuNCs/Fe3N-NPCF exhibited onset potential of 0.98 V and low Tafel slope of 59.30 mV dec−1 in ORR, and overpotential of 282 mV at 10 mA cm−2 current density in OER. The CuNCs/Fe3N-NPCF-based zinc-air battery displayed the excellent catalytic activity and durability. These findings provided the guides in developing the efficient and stable Mott-Schottky bifunctional oxygen electrocatalysts.

The low power diesel-generator unit with electronically controlled fuel injection

BACKGROUND: Diesel engines, used in generator units, primarily operate in variable loading conditions. Therefore, their technical and economic performance generally deteriorate when the load decreases. It arises from the diesel engine fuel system feature, where pressure and quantity of the fuel, injected into a cylinder, reduces with the load decreasing. As a result, the injection becomes sluggish, the quality of mixing process and combustion becomes worse.
 AIMS: Improvement of effective indicators of the diesel-generator units with electronically controlled fuel injection.
 METHODS: Adjustment of operation modes of the diesel engine of the electrical power unit carried out with use of electronically controlled Denso solenoid, connected to the high-pressure fuel pump via an adapter.
 RESULTS: Results of the motor testing of the low power diesel-generator unit with electronically controlled fuel feed system are described in the article. The oscillograph charts of valve displacement and solenoid magnet winding current, presented in the article, confirm its operation efficiency. Sharp decrease in boost current at the stage of valve lift can be explained by onset of back EMF. Stable solenoid operation at diesel operation velocity of 30003100 min-1 is achieved by means of boost impulse supply to its winding. The boost impulse is supplied from a voltage upconverter and generated by discharge of preliminary charged booster capacitor.
 CONCLUSIONS: Separated fuel feed adjustment in each high-pressure pump section made possible to reduce intersectional fuel feed irregularity to zero. Significant fuel consumption reduction was revealed with the motor testing of the low power diesel-generator unit with electronically controlled fuel feed system (the reduction reaches 10% on low loading operation modes). As mentioned by authors, transition to electronic control of operation modes of diesel engines of autonomous electrical power units does not require major engine design change only to dismantle a mechanical controller and to set an adapter with electronically controlled bypass valve at a section of the high-pressure fuel pump. Electronic control unit supplies current to the valve. For autonomous electrical power units, transition to this control method can be done in typical repair workshop conditions, and an update of one unit (e.g. the KIPOR KDE19AE3) costs 13 950 rubles. By doing so, one electrical power unit may save up to 1191 liters of fuel and more than 63.96 thousands rubles at a cost of 53.7 rubles per liter.

Nanocomposite Electrode of Titanium Dioxide Nanoribbons and Multiwalled Carbon Nanotubes for Energy Storage.

TiO2 is one of the most investigated materials due to its abundance, lack of toxicity, high faradaic capacitance, and high chemical and physical stability; however, its potential use in energy storage devices is constrained by its high internal resistance and weak van der Waals interaction between the particles. Carbon nanotubes are especially well suited for solving these issues due to their strong mechanical strength, superior electrical conductivity, high electron mobilities, excellent chemical and thermal stability, and enormous specific nanoporous surface. The hydrothermal approach was followed by chemical vapor deposition to produce a network composite of titanium dioxide nanoribbons (TNRs) and multi-walled carbon nanotubes (MWCNTs). The nanocomposite was characterized using a variety of methods. One phase of TiO2-B nanoribbons has porous pits on its surface, and MWCNTs are grown in these pits to produce a network-like structure in the nanocomposite. With a two-electrode supercapacitor configuration, the TNR/CNT gave a gravimetric capacitance of 33.33 F g-1, which was enhanced to 68.18 F g-1 in a redox-active electrolyte containing hydroquinone (HQ). Additionally, the areal capacitance per footprint was increased from 80 mF cm-2 in H2SO4 to 163.63 mF cm-2 in H2SO4/HQ. The TNR/CNT supercapacitor has superior cyclic stability than the previously reported TiO2-based electrodes, with 97.5% capacitance retention after 5000 cycles. Based on these results, it looks like the TNR/CNT supercapacitor could provide portable electronic power supplies with new ways to work in the future.

Denitrification in Microbial Fuel Cells Using Granular Activated Carbon as an Effective Biocathode

Nitrate (NO3−-N) and nitrites (NO2−-N) are common pollutants in various water bodies causing serious threats not only to aquatic, but also to animals and human beings. In this study, we developed a strategy for efficiently reducing nitrates in microbial fuel cells (MFCs) powered by a granular activated carbon (GAC)-biocathode. GAC was developed by acclimatizing and enriching denitrifying bacteria under a redox potential (0.3 V) generated from MFCs. Thus, using the formed GAC-biocathode we continued to study their effect on denitrification with different cathode materials and circulation speeds in MFCs. The GAC-biocathode with its excellent capacitive property can actively reduce nitrate for over thirty days irrespective of the cathode material used. The stirring speed of GAC in the cathode showed a steady growth in potential generation from 0.25 V to 0.33 V. A rapid lag phase was observed when a new carbon cathode was used with enriched GAC. While a slow lag phase was seen when a stainless-steel cathode was replaced. These observations showed that effective storage and supply of electrons to the GAC plays a crucial role in the reduction process in MFCs. Electrochemical analysis of the GAC properties studied using electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV), and zeta potential showed distinct properties with different abiotic and biocathode conditions. We found that the enrichment of electrotrophic bacteria on GAC facilitates the direct electron transfer in the cathode chamber for reducing NO3−-N in MFCs as observed by scanning electron microscopy.

Effect of Supplier Relationship Management on the Relationship between Electronic Data Interchange Integration and Supply Chain Performance in Sugar Manufacturing Firms in Kenya

Globally and in Kenya to be specific, there has been a challenge on cost of manufacturing. Manufacturing cost has been rising for; a status report from the Sugar Directorate indicates that wholesale price of sugar in February 2017 was at average Sh 5, 352 per 50 kg, compared with Sh 4, 432 in the same period last year. In Kenya, sugar cane production decreased from 6.7 million tons in 2013 to 6.5 million tons in 2014 as reported in Economic Survey of 2014. Moreover, despite reporting increased cane delivery in 2015, supply chain in sugar firms remained dismal indicating inefficient firm processes and overall poor performance due to high cost of production. Its argued that supply chain(SC)s may use Electronic data interchange integration(EDII) to mitigate on cost and improve firm performance.SRM is management of all interactions with suppliers, while SCP performance means responsiveness, timeliness and reliability However; studies have not addressed this adequately. The purpose of this study was to determine the effect of supplier relationship management on the relationship between electronic data interchange integration and supply chain performance among sugar firms in western Kenya, the study established effect of electronic data interchange integration on supply chain performance; effect of supplier relationship management on supply chain performance; and effect of supplier relationship management on the relationship between electronic data interchange integration and supply chain performance. This study was anchored on resource based, transaction cost analysis, and social exchange theories. Correlation research design was used. Target population was 300 supply chain employees from 10 sugar manufacturing firms in western Kenya. A sample of 169 was drawn using cluster, purposive and simple random sampling. 10% of the sample was used to pre-test the questionnaire. Questionnaire and interview guides were used to collect primary data. Secondary data was obtained from Company’s’ records. The study concluded that EDI, SRM have significant effects on SCP and that SRM has moderating effect on the relationship between EDI and SCP. The study recommends that adopted EDII in SCP should be implemented consistently for improved performance and because SRM has a significant relationship between EDII and SCP it should been enhanced for increased performance. Findings may provide useful information for policy formulation for faster decision making in enhancing increased customer service level in the sugar firms and availability of research literature for further research

Simulation Model for Passive Harmonic Filters Using Matlab/Simulink: A Case Study

Electrical grid power quality is a global issue. The grid must supply electricity at sinusoidal voltages and currents without frequency or amplitude fluctuations. Harmonics from non-linear loads change the stable reference point voltage waveform and cause other problems. Harmonic reduction is essential for grid health. Electrical and electronic equipment users, manufacturers, and suppliers all contribute. This article presents a case analysis of the plastic processing industry, which has historically struggled with a difficulty related to the fifth harmonic. Unwanted harmonics are reduced by using a single-tuned passive filter, a double-tuned passive filter, and a second-order damped filter. The total harmonic distortion is almost identical, but the second-order damped filter provides the best harmonic mitigation, meeting the requirements of the IEE 519-1992 Standard.

A novel separate chance-constrained programming model to design a sustainable medical ventilator supply chain network during the Covid-19 pandemic

<p style='text-indent:20px;'>Providing new models or designing sustainable networks in recent studies represents a growing trend. However, there is still a gap in the simultaneous modeling of the three dimensions of sustainability in the electronic medical device supply chain (SC). In this paper, a novel hybrid chance-constrained programming and cost function model is presented for a green and sustainable closed-loop medical ventilator SC network design. To bring the problem closer to reality, a wide range of parameters including all cost parameters, demands, the upper bound of the released <inline-formula><tex-math id="M1">\begin{document}$ co_2 $\end{document}</tex-math></inline-formula>, and the minimum percentage of the units of product to be disposed and collected from a customer and to be dismantled and shipped from DCs are modeled as uncertain along with the normal probability distribution. The problem was first formulated into the framework of a bi-objective stochastic mixed-integer linear programming (MILP) model; then, it was reformulated into a tri-objective deterministic mixed-integer nonlinear programming (MINLP) one. In order to model the environmental sustainability dimension, in addition to handling the total greenhouse gas emissions, the total waste products were also controlled. The efficiency and applicability of the proposed model were tested in an Iranian medical ventilator production and distribution network. For sensitivity analyses, the effect of some critical parameters on the values of the objective functions was carefully examined. Finally, valuable managerial insights into the challenges of companies during the COVID-19 pandemic were presented. Numerical results showed that with the increase in the number of customers in the COVID-19 crisis, social responsibility could improve cost mean by up to 8%.</p>

The role of information technology in food business performance: The mediator of electronic green supply chain management

The role of information technology in food business performance: The mediator of electronic green supply chain management

A new model to design the suppliers portfolio in newsvendor problem based on product reliability

<p style='text-indent:20px;'>Suppliers' selection problem has always been daunting challenges in the Newsvendor problem. Furthermore, since the failures in the supplier's products cause irreparable damage to the retailer, it is necessary to consider the reliability of products in ordering suppliers' products. This paper develops the Newsvendor model by considering the impactful criteria in supplier selection and product reliability so that the total cost of the chain is minimized in a multi-product and multi-period model with multiple suppliers. While multiple criteria decision making (MCDM) accounts for multiple criteria and their tradeoffs, its application in Newsvendor model is not considered. This paper applies the Bayesian best worst method (BWM), as one of the MCDM methods, for ranking criteria and the fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) for prioritizing the suppliers. Then, the obtained weights are plugged into the model as the inputs of the designed model. A case study with real data in the electronic supply chain is considered. To validate the results obtained by the proposed method, genetic algorithm (GA) and particle swarm optimization (PSO) are leveraged to solve the proposed model. Finally, the efficiency of the designed model is verified through a case study.</p>

A vendor-managed inventory model based on optimal retailers selection and reliability of supply chain

<p style='text-indent:20px;'>One of the most common and successful approaches for the integrated supply chain management (SCM) is the vendor-managed inventory (VMI). In VMI, a vendor takes control of the inventory decisions for retailers. To establish a long-run relationship between the vendor and the retailer, it is necessary to consider two impactful factors: the vendors and retailers' reliability, and the optimal selection of retailers. For this purpose, the redundancy allocation problem (RAP), as an effective technique for increasing the reliability of vendors, is used in this paper. Also, the reliability of retailers as well as the reliability of the relationship between retailers and vendors are considered. In the retailer selection, process decisions on impactful criteria are simultaneously considered. For the retailers' selection, one analysis hierarchical process (AHP) is performed for each vendor, and the weights of retailers are obtained. Then, the obtained weights are plugged into the model as the inputs of the designed model. Since the developed model is a non-differentiable, non-convex, and mixed-integer function, genetic algorithm (GA) and particle swarm optimization (PSO) are leveraged to solve the formulated model. Finally, the efficiency of the presented method is verified through a case study with data collected from the electronic supply chain.</p>

Analysis of the enablers of supply chain digitalisation in the electronics industry: an interpretive structural modelling approach

Supply chain digitalisation has great advantages. In spite of a large number of studies, there is a lack of literature to identify and address the key enablers to be considered for supply chain digitalisation. In this study, 13 key enablers for integration of supply chain through digitalisation in an electronic supply chain in Indian context are identified and shortlisted in consultation with the experts from industry and academia. Interpretive structural modelling has been used for understanding of the hierarchical and contextual influences among the identified key enablers for supply chain digitalisation. Results of the model indicate that prior to taking a decision on supply chain digitalisation, companies have to identify the key enablers and its impact on digitalisation process. Policy decision-makers could use the results of this study to identify the key enablers and their interrelationship for taking effective decision for supply chain digitalisation process.