U. Umer, M. K. Mohammed, M. Abidi, H. Alkhalefah, H. Kishawy
In this study the effects of reinforcement particle size and cutting parameters on machining performance variables like cutting force, maximum tool-chip interface temperature and surface roughness of the machined surface have been investigated while machining Aluminum based metal matrix composites (MMCs). MMC bars with silicon carbide reinforcement having 10 % volume fraction and particle sizes of 5 μm, 10 μm and 15 μm are machined with polycrystalline diamond (PCD) inserts. Experiments are performed using central composite design (CCD) having four parameters with three levels. Response surfaces for each performance variables are generated using polynomial models. Single variable and interaction effects have been investigated using principal component analysis and 3D response charts. Multi-response optimization has been performed to minimize surface roughness and maximum tool-chip interface temperature using non-dominated sorting genetic algorithm II (NSGA-II). In addition, constraints have been applied to the optimization search to filter design points with high cutting forces and low material removal rate. Most of the optimal solutions are found to be with moderate cutting speeds, low feed rate and low depth of cuts.
{"title":"Machinability analysis and multi-response optimization using NGSA-II algorithm for particle reinforced aluminum based metal matrix composites","authors":"U. Umer, M. K. Mohammed, M. Abidi, H. Alkhalefah, H. Kishawy","doi":"10.14743/apem2022.2.431","DOIUrl":"https://doi.org/10.14743/apem2022.2.431","url":null,"abstract":"In this study the effects of reinforcement particle size and cutting parameters on machining performance variables like cutting force, maximum tool-chip interface temperature and surface roughness of the machined surface have been investigated while machining Aluminum based metal matrix composites (MMCs). MMC bars with silicon carbide reinforcement having 10 % volume fraction and particle sizes of 5 μm, 10 μm and 15 μm are machined with polycrystalline diamond (PCD) inserts. Experiments are performed using central composite design (CCD) having four parameters with three levels. Response surfaces for each performance variables are generated using polynomial models. Single variable and interaction effects have been investigated using principal component analysis and 3D response charts. Multi-response optimization has been performed to minimize surface roughness and maximum tool-chip interface temperature using non-dominated sorting genetic algorithm II (NSGA-II). In addition, constraints have been applied to the optimization search to filter design points with high cutting forces and low material removal rate. Most of the optimal solutions are found to be with moderate cutting speeds, low feed rate and low depth of cuts.","PeriodicalId":445710,"journal":{"name":"Advances in Production Engineering & Management","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121938943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
L. Yang, B. Yang, G.W. Yang, S. Xiao, T. Zhu, F. Wang
Currently, ΔF-N curves are often used to predict the fatigue lives of spot-welded joints, but the method for obtaining these ΔF-N curves is time-consuming, laborious, and non-universal. Tensile-shear fatigue tests were performed to obtain the fatigue lives and the corresponding normalized S-N curves of spot-welded joints. Subsequently, the force acting at the spot-welded joints was obtained by extracting the force and moment of the beam element in the shell-element-based finite element model, and the equivalent structural stress at the spot-welded joint was obtained based on the equiva-lent structural stress method. Finally, the S-N curves of the spot-welded joints were fitted using the least-squares method. A comparison of the S-N curves of the spot-welded joints with those of different materials revealed that the material type had a significant influence on the S-N curve. To avoid this influence, a method for predicting the S-N curve of the spot-welded joints was proposed based on the relationship between the ratio of the ten-sile strength and that of the fatigue limit of each material. This research provides guidance for predicting the fatigue life of spot-welded joints in engineering applications.
{"title":"A method for prediction of S-N curve of spot-welded joints based on numerical simulation","authors":"L. Yang, B. Yang, G.W. Yang, S. Xiao, T. Zhu, F. Wang","doi":"10.14743/apem2022.2.426","DOIUrl":"https://doi.org/10.14743/apem2022.2.426","url":null,"abstract":"Currently, ΔF-N curves are often used to predict the fatigue lives of spot-welded joints, but the method for obtaining these ΔF-N curves is time-consuming, laborious, and non-universal. Tensile-shear fatigue tests were performed to obtain the fatigue lives and the corresponding normalized S-N curves of spot-welded joints. Subsequently, the force acting at the spot-welded joints was obtained by extracting the force and moment of the beam element in the shell-element-based finite element model, and the equivalent structural stress at the spot-welded joint was obtained based on the equiva-lent structural stress method. Finally, the S-N curves of the spot-welded joints were fitted using the least-squares method. A comparison of the S-N curves of the spot-welded joints with those of different materials revealed that the material type had a significant influence on the S-N curve. To avoid this influence, a method for predicting the S-N curve of the spot-welded joints was proposed based on the relationship between the ratio of the ten-sile strength and that of the fatigue limit of each material. This research provides guidance for predicting the fatigue life of spot-welded joints in engineering applications.","PeriodicalId":445710,"journal":{"name":"Advances in Production Engineering & Management","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127324254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The study of eccentricity minimization in cylindrical products helps to reduce the mechanical vibrations and wear of related mechanical parts such as bearings, columns and gears which positively affects in maintenance costs savings and increasing production quality reliability. The main purpose of this paper is to investigate the effect of the eccentricity between the billet material and the die parts on the quality of the final product in the direct extrusion process. The input parameters to produce a cylindrical product shape are optimized in MINITAB based on Taguchi method and ANOVA. The selected material of the billet is the aluminium alloy AA2024, and the die material is Steel H13. The inputs parameters are the temperature, the die angle, the ram speed, and the presumed eccentricity. The finite element model of the process is simulated in DFORM-3D for providing the extrusion information such as the pressure, the effective stress and strain, the final product eccentricity, and the roundness error. The study is carried out on two cases of the presumed eccentricity in addition to a case of zero eccentricity. The single and multi-response optimizations are executed to obtain the optimum parameters for the minimum product eccentricity and roundness error.
{"title":"Modelling and simulation of hot direct extrusion process for optimal product characteristics: Single and multi-response optimization approach","authors":"F. Elplacy, M. Samuel, R. Mostafa","doi":"10.14743/apem2022.1.419","DOIUrl":"https://doi.org/10.14743/apem2022.1.419","url":null,"abstract":"The study of eccentricity minimization in cylindrical products helps to reduce the mechanical vibrations and wear of related mechanical parts such as bearings, columns and gears which positively affects in maintenance costs savings and increasing production quality reliability. The main purpose of this paper is to investigate the effect of the eccentricity between the billet material and the die parts on the quality of the final product in the direct extrusion process. The input parameters to produce a cylindrical product shape are optimized in MINITAB based on Taguchi method and ANOVA. The selected material of the billet is the aluminium alloy AA2024, and the die material is Steel H13. The inputs parameters are the temperature, the die angle, the ram speed, and the presumed eccentricity. The finite element model of the process is simulated in DFORM-3D for providing the extrusion information such as the pressure, the effective stress and strain, the final product eccentricity, and the roundness error. The study is carried out on two cases of the presumed eccentricity in addition to a case of zero eccentricity. The single and multi-response optimizations are executed to obtain the optimum parameters for the minimum product eccentricity and roundness error.","PeriodicalId":445710,"journal":{"name":"Advances in Production Engineering & Management","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123917007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The vehicle routing problem with split deliveries and pickups is a hot research topic in recent years, where a customer can be served multiple times with split deliveries and pickups. The objective is to minimize the travel distance, use the fewest number of vehicles and increase the load rate, which will further reduce the carbon emissions that damage the environment. In this paper, we use a two-stage construction heuristic approach to solve this problem. First, partitioning algorithms based on the multi-restart-iterative sweep algorithm are adopted to partition the customer domain into sub-domains according to the vehicle capacity, and to determine the split points and the corresponding values. Second, a modified Clarke-Wright savings algorithm is used to check the possibility of each point in each route based on the load of each point and the vehicle load limitation. The three case studies with 12 instances per each from the reconstructed Solomon benchmark datasets were conducted to evaluate the effectiveness and feasibility of the proposed approaches-Unsplit, Both-Split and Enhanced-Both-Split. The comparison among these approaches reveals that the splits reduce the total travel cost and vehicles used, and increase the average loading rate considerably, especially when customers have larger demand values. Our computation results proves that the vehicle routing problem with split deliveries and pickups is highly beneficial for transportation and logistics enterprises.
{"title":"A two-stage construction heuristic approach for vehicle routing problem with split deliveries and pickups: Case studies and performance comparison","authors":"C. Jin, L. Lu, J. Min","doi":"10.14743/apem2022.1.425","DOIUrl":"https://doi.org/10.14743/apem2022.1.425","url":null,"abstract":"The vehicle routing problem with split deliveries and pickups is a hot research topic in recent years, where a customer can be served multiple times with split deliveries and pickups. The objective is to minimize the travel distance, use the fewest number of vehicles and increase the load rate, which will further reduce the carbon emissions that damage the environment. In this paper, we use a two-stage construction heuristic approach to solve this problem. First, partitioning algorithms based on the multi-restart-iterative sweep algorithm are adopted to partition the customer domain into sub-domains according to the vehicle capacity, and to determine the split points and the corresponding values. Second, a modified Clarke-Wright savings algorithm is used to check the possibility of each point in each route based on the load of each point and the vehicle load limitation. The three case studies with 12 instances per each from the reconstructed Solomon benchmark datasets were conducted to evaluate the effectiveness and feasibility of the proposed approaches-Unsplit, Both-Split and Enhanced-Both-Split. The comparison among these approaches reveals that the splits reduce the total travel cost and vehicles used, and increase the average loading rate considerably, especially when customers have larger demand values. Our computation results proves that the vehicle routing problem with split deliveries and pickups is highly beneficial for transportation and logistics enterprises.","PeriodicalId":445710,"journal":{"name":"Advances in Production Engineering & Management","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133665125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper proposes and applies two different methodologies for modelling the roughness parameters in hard turning. The first method is based on the kinematical-geometrical copying of the cutting tool geometry onto the machined surface including a feedback loop through the parameter of statistic equality of sampling lengths in surface roughness measurements (SE). The other method employs the Design of Experiments (DOE) principles expressing the roughness parameters as first order nonlinear function of the input variables: cutting speed v, feed f, depth of cut ap, and tool nose radius rε. The research includes the Ra and Rz roughness parameters which are commonly modelled throughout the research works, and additionally develops models for the Rp, Rv and Rmr(c) roughness parameters which are more challenging to model compared to Ra and Rz as they depend more on the shape of the roughness profile and position of its mean line. Both methodologies for all roughness parameters were verified using a CNC lathe and special rings made of steel EN C55 with hardness of 53±1 HRC. Considering that the roughness profile is just a part of the total geometric deviations of the processed surfaces, and it is obtained from the total profile using software filtration, the research also considers the Wa parameter (waviness profile), as well as the deviations from the circularity (out-off-roundness) of the processed rings as indicators for the stability of the machining process.
{"title":"Modelling of multiple surface roughness parameters during hard turning: A comparative study between the kinematical-geometrical copying approach and the design of experiments method (DOE)","authors":"M. Tomov, V. Gečevska, E. Vasileska","doi":"10.14743/apem2022.1.422","DOIUrl":"https://doi.org/10.14743/apem2022.1.422","url":null,"abstract":"This paper proposes and applies two different methodologies for modelling the roughness parameters in hard turning. The first method is based on the kinematical-geometrical copying of the cutting tool geometry onto the machined surface including a feedback loop through the parameter of statistic equality of sampling lengths in surface roughness measurements (SE). The other method employs the Design of Experiments (DOE) principles expressing the roughness parameters as first order nonlinear function of the input variables: cutting speed v, feed f, depth of cut ap, and tool nose radius rε. The research includes the Ra and Rz roughness parameters which are commonly modelled throughout the research works, and additionally develops models for the Rp, Rv and Rmr(c) roughness parameters which are more challenging to model compared to Ra and Rz as they depend more on the shape of the roughness profile and position of its mean line. Both methodologies for all roughness parameters were verified using a CNC lathe and special rings made of steel EN C55 with hardness of 53±1 HRC. Considering that the roughness profile is just a part of the total geometric deviations of the processed surfaces, and it is obtained from the total profile using software filtration, the research also considers the Wa parameter (waviness profile), as well as the deviations from the circularity (out-off-roundness) of the processed rings as indicators for the stability of the machining process.","PeriodicalId":445710,"journal":{"name":"Advances in Production Engineering & Management","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116737498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The aim of this paper is to investigate scheduling problems in manufacturing. After a brief introduction to the modelling approach to the scheduling problem, the study focuses on the optimization approach to the scheduling problem. Firstly, the different optimization approaches are categorised and their respective advantages and disadvantages are shown. This is followed by a detailed analysis of the characteristics and applicability of each of the commonly used optimization approaches. Finally, a case study is presented. A mathematical model is developed with the objective of minimising the maximum completion time for a mixed flow shop scheduling problem, and a genetic algorithm is used to solve the problem. The validity of the model is verified through the case study, which can provide a reasonable scheduling solution for actual manufacturing. This provides a reference for the selection and use of methods for solving scheduling problems in practical production.
{"title":"Optimization approaches for solving production scheduling problem: A brief overview and a case study for hybrid flow shop using genetic algorithms","authors":"W. Xu, H.Y. Sun, A.L. Awaga, Y. Yan, Y. Cui","doi":"10.14743/apem2022.1.420","DOIUrl":"https://doi.org/10.14743/apem2022.1.420","url":null,"abstract":"The aim of this paper is to investigate scheduling problems in manufacturing. After a brief introduction to the modelling approach to the scheduling problem, the study focuses on the optimization approach to the scheduling problem. Firstly, the different optimization approaches are categorised and their respective advantages and disadvantages are shown. This is followed by a detailed analysis of the characteristics and applicability of each of the commonly used optimization approaches. Finally, a case study is presented. A mathematical model is developed with the objective of minimising the maximum completion time for a mixed flow shop scheduling problem, and a genetic algorithm is used to solve the problem. The validity of the model is verified through the case study, which can provide a reasonable scheduling solution for actual manufacturing. This provides a reference for the selection and use of methods for solving scheduling problems in practical production.","PeriodicalId":445710,"journal":{"name":"Advances in Production Engineering & Management","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132019583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Today's world revolves around technology, which has a total impact not only on human life but also on manufacturing companies. Many companies have embraced artificial intelligence (AI) in the form of powerful computers, applications, or software that can screen job applicants, alert when a machine is about to break down, and read legal contracts. However, the rapid expansion of AI and its use in legal settings, such as contract performance, in a company is a major challenge on the judicial side. This article, thus, establishes an evolutionary game model of whether manufacturing suppliers are performing contracts or not when the court chooses to use artificial intelligence (AI) technology. Considering the complexity of choosing manufacturers' AI strategy, the method constructs a simulation analysis model of manufacturers' contract enforcement behaviour with the participation of several subjects. We can simulate the influence of the factors selected on the strategy chosen by both parties (manufacturers and court) by changing the different influence factors and studying the evolutionary law of different court guidance and regulation strategies on the production behaviour of green products. The results show that the choice of the court and manufacturers to use the AI technology strategy or not is based on the rate of error reduction, through the computational implementation of multi-subject modelling.
{"title":"The influence of artificial intelligence technology judicial decision reasoning on contract performance in manufacturing supply chain: A simulation analysis using Evolutionary Game approach","authors":"G. Zhao, H. Shi, J.F. Wang","doi":"10.14743/apem2022.1.424","DOIUrl":"https://doi.org/10.14743/apem2022.1.424","url":null,"abstract":"Today's world revolves around technology, which has a total impact not only on human life but also on manufacturing companies. Many companies have embraced artificial intelligence (AI) in the form of powerful computers, applications, or software that can screen job applicants, alert when a machine is about to break down, and read legal contracts. However, the rapid expansion of AI and its use in legal settings, such as contract performance, in a company is a major challenge on the judicial side. This article, thus, establishes an evolutionary game model of whether manufacturing suppliers are performing contracts or not when the court chooses to use artificial intelligence (AI) technology. Considering the complexity of choosing manufacturers' AI strategy, the method constructs a simulation analysis model of manufacturers' contract enforcement behaviour with the participation of several subjects. We can simulate the influence of the factors selected on the strategy chosen by both parties (manufacturers and court) by changing the different influence factors and studying the evolutionary law of different court guidance and regulation strategies on the production behaviour of green products. The results show that the choice of the court and manufacturers to use the AI technology strategy or not is based on the rate of error reduction, through the computational implementation of multi-subject modelling.","PeriodicalId":445710,"journal":{"name":"Advances in Production Engineering & Management","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126907136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The paper presents the numerical simulation of quenching cylindrical steel sample immersed in three different quenchants: water, 5 % aquatensid solution, and isorapid oil. The quenching process starts from the initial temperature of the cylinder at 850 °C and moves through the air until it reaches the quenching bath. The quenchant is held at constant temperature of 40 °C. The cylinder is made of carefully selected steel which does not change its structure during quenching and heating. Cylindrical samples were manufactured in three different dimensions (R, H), (mm): (12.5 × 100), (25 × 150) and (37.5 × 225), so that four measuring points were installed in each sample. Each measuring point consists of thermocouple installed beneath the cylinder surface, capable of measuring the temperature every half second. Based on the experiment, the numerical simulation is recognized as transient and nonlinear two-dimensional heat conduction problem consisting of the two main tasks: direct heat transfer problem (DHTP) and inverse heat transfer problem (IHTP). The paper proposes a new multi-objective optimization approach for the estimation of heat transfer coefficients during the numerical simulation of quenching cylindrical steel sample. The proposed approach gained better results and less convergence time compared to the results from the literature. The paper includes methods, algorithms and the source code for the calculation of the temperature fields in time and heat transfer coefficient estimation of the IHTP. The simulation software has been implemented in C# programming language and can be found at http://github.com/bhrnjica/quenching_simulation.
{"title":"A new multi-objective optimization approach for process parameters optimization during numerical simulation of quenching steel parts","authors":"B. Hrnjica, Š. Behrem","doi":"10.14743/apem2022.1.418","DOIUrl":"https://doi.org/10.14743/apem2022.1.418","url":null,"abstract":"The paper presents the numerical simulation of quenching cylindrical steel sample immersed in three different quenchants: water, 5 % aquatensid solution, and isorapid oil. The quenching process starts from the initial temperature of the cylinder at 850 °C and moves through the air until it reaches the quenching bath. The quenchant is held at constant temperature of 40 °C. The cylinder is made of carefully selected steel which does not change its structure during quenching and heating. Cylindrical samples were manufactured in three different dimensions (R, H), (mm): (12.5 × 100), (25 × 150) and (37.5 × 225), so that four measuring points were installed in each sample. Each measuring point consists of thermocouple installed beneath the cylinder surface, capable of measuring the temperature every half second. Based on the experiment, the numerical simulation is recognized as transient and nonlinear two-dimensional heat conduction problem consisting of the two main tasks: direct heat transfer problem (DHTP) and inverse heat transfer problem (IHTP). The paper proposes a new multi-objective optimization approach for the estimation of heat transfer coefficients during the numerical simulation of quenching cylindrical steel sample. The proposed approach gained better results and less convergence time compared to the results from the literature. The paper includes methods, algorithms and the source code for the calculation of the temperature fields in time and heat transfer coefficient estimation of the IHTP. The simulation software has been implemented in C# programming language and can be found at http://github.com/bhrnjica/quenching_simulation.","PeriodicalId":445710,"journal":{"name":"Advances in Production Engineering & Management","volume":"370 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133225794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This research investigates the impact of external environment, cognitive factors, and behavioral dimensions in the context of implementing supply chain agility. It applies social cognitive theory to establish a link between various environments including business uncertainty and supply chain disruption risk, cognitive factors such as supply chain agility self-efficacy, trust, and supply chain cooperation, coordination, and communication attitude, and actions such as implementing supply chain agility as well as behavior to explain the decision-making process in implementation. Based on the survey data collected from 254 supply and purchasing managers in the Korean manufacturing industry, AMOS software with structural equation method was used for data analysis Our results support the concept that business uncertainty reduces self-efficacy in supply chain agility although both business uncertainty and supply chain disruption risk boosted trust in the supply chain as well as buyers’ positive attitude toward supply chain cooperation, coordination, and communication. The concept of supply chain agility, self-efficacy, trust, and supply chain cooperation, coordination, and communication attitude have a positive impact on firm performance. Supply chain agility, self-efficacy, and trust in suppliers positively affects implementation of supply chain agility as well as firms’ financial, operational, and supply chain performance. This research provides meaningful insights for considering external environments and cognitive factors while making decisions in implementing supply chain agility.
{"title":"The role of agility in responding to uncertainty: A cognitive perspective","authors":"M. Kim, S. Chai","doi":"10.14743/apem2022.1.421","DOIUrl":"https://doi.org/10.14743/apem2022.1.421","url":null,"abstract":"This research investigates the impact of external environment, cognitive factors, and behavioral dimensions in the context of implementing supply chain agility. It applies social cognitive theory to establish a link between various environments including business uncertainty and supply chain disruption risk, cognitive factors such as supply chain agility self-efficacy, trust, and supply chain cooperation, coordination, and communication attitude, and actions such as implementing supply chain agility as well as behavior to explain the decision-making process in implementation. Based on the survey data collected from 254 supply and purchasing managers in the Korean manufacturing industry, AMOS software with structural equation method was used for data analysis Our results support the concept that business uncertainty reduces self-efficacy in supply chain agility although both business uncertainty and supply chain disruption risk boosted trust in the supply chain as well as buyers’ positive attitude toward supply chain cooperation, coordination, and communication. The concept of supply chain agility, self-efficacy, trust, and supply chain cooperation, coordination, and communication attitude have a positive impact on firm performance. Supply chain agility, self-efficacy, and trust in suppliers positively affects implementation of supply chain agility as well as firms’ financial, operational, and supply chain performance. This research provides meaningful insights for considering external environments and cognitive factors while making decisions in implementing supply chain agility.","PeriodicalId":445710,"journal":{"name":"Advances in Production Engineering & Management","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128500900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. Rudolf, Ž. Jelen, M. Zadravec, P. Majerič, Z. Jović, M. Vuksanović, I. Stanković, L. Matija, A. Dragicevic, N. Miso Thompson, A. Horvat, D. Koruga
Three types of gold nanoparticles (AuNPs) were synthesised with a custom-made Ultrasonic Spray Pyrolysis (USP) device, from aqueous solutions of gold (III) chloride (AuCl3) and gold (III) acetate (AuC6H12O6), with an initial concentration of Au 0.5 g/L. AuNPs were collected in suspensions of deionised (D.I.) water with the stabilisers polyvinylpyrrolidone (PVP) or polyethylene glycol (PEG), followed by the process of freeze drying the AuNPs to be useful as a new additive for the cream. The standard cream base was used as a matrix for preparation of three types of cream with AuNPs in the same concentration ratios. The third AuNPs cream was prepared with a patented hydroxylated fullerene water complex (3HFWC-W) matrix. To examine the effect of AuNPs as additive in creams, a six-week study of test creams was conducted on 33 volunteers with no dermatological diseases. During the study three main parameters of the skin where measured: Collagen quality, skin moisturisation and the epidermis-dermis function. The results of the study found improvements of collagen quality between 18-24 %, achieved due to the use of AuNPs in standard creams, while the cream with the combination of 3HFWC-W and AuNPs gave significantly higher improvements with a value of 45.7 %. It was also discovered that hydration of the skin (stratum cornum) increased by 6.4-9.6 % in standard creams with AuNPs, and 73.7 % in the 3HFWC/AuNPs` cream. Similar results were measured by the epidermis-dermis function, where 24-28 % improvement for standard creams with AuNPs was identified, and 38.4 % for the cream 3HFWC-W/AuNPs.
{"title":"A gold nanoparticles and hydroxylated fullerene water complex as a new product for cosmetics","authors":"R. Rudolf, Ž. Jelen, M. Zadravec, P. Majerič, Z. Jović, M. Vuksanović, I. Stanković, L. Matija, A. Dragicevic, N. Miso Thompson, A. Horvat, D. Koruga","doi":"10.14743/apem2022.1.423","DOIUrl":"https://doi.org/10.14743/apem2022.1.423","url":null,"abstract":"Three types of gold nanoparticles (AuNPs) were synthesised with a custom-made Ultrasonic Spray Pyrolysis (USP) device, from aqueous solutions of gold (III) chloride (AuCl3) and gold (III) acetate (AuC6H12O6), with an initial concentration of Au 0.5 g/L. AuNPs were collected in suspensions of deionised (D.I.) water with the stabilisers polyvinylpyrrolidone (PVP) or polyethylene glycol (PEG), followed by the process of freeze drying the AuNPs to be useful as a new additive for the cream. The standard cream base was used as a matrix for preparation of three types of cream with AuNPs in the same concentration ratios. The third AuNPs cream was prepared with a patented hydroxylated fullerene water complex (3HFWC-W) matrix. To examine the effect of AuNPs as additive in creams, a six-week study of test creams was conducted on 33 volunteers with no dermatological diseases. During the study three main parameters of the skin where measured: Collagen quality, skin moisturisation and the epidermis-dermis function. The results of the study found improvements of collagen quality between 18-24 %, achieved due to the use of AuNPs in standard creams, while the cream with the combination of 3HFWC-W and AuNPs gave significantly higher improvements with a value of 45.7 %. It was also discovered that hydration of the skin (stratum cornum) increased by 6.4-9.6 % in standard creams with AuNPs, and 73.7 % in the 3HFWC/AuNPs` cream. Similar results were measured by the epidermis-dermis function, where 24-28 % improvement for standard creams with AuNPs was identified, and 38.4 % for the cream 3HFWC-W/AuNPs.","PeriodicalId":445710,"journal":{"name":"Advances in Production Engineering & Management","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129578258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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