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26 pages, 2144 KiB

Open AccessArticle

Support of Advanced Technologies in Supply Chain Processes and Sustainability Impact

by Susana Garrido Azevedo, Carina M. O. Pimentel, Anabela C. Alves and João C. O. Matias

Appl. Sci. 2021, 11(7), 3026; https://doi.org/10.3390/app11073026 - 29 Mar 2021

Cited by 10 | Viewed by 5624

Abstract

This paper aims to present a study of the type of advanced technologies used across manufacturing supply chains in supporting the main processes of the supply chain operations reference model (SCOR). It also intends to identify a set of sustainable performance indicators (environmental, [...] Read more.

This paper aims to present a study of the type of advanced technologies used across manufacturing supply chains in supporting the main processes of the supply chain operations reference model (SCOR). It also intends to identify a set of sustainable performance indicators (environmental, economic, and social) suitable to evaluate a supply chain 4.0 (SC4.0). To attain this objective, based on the literature review, a conceptual model is proposed. The multiple case study is used with a cross-case comparison to identify the type of advanced technologies more commonly used in SC4.0, and the performance indicators more suitable for assessing a SC4.0 sustainability performance. A sample of ten case studies was considered with companies belonging to different manufacturing SCs, from different countries, and belonging to different echelons. Main findings revealed that the level of adoption of advanced technologies in the Supply Chain SCOR processes varies amongst the case studies. Some technologies are quite commonly used among the several SCOR processes and companies while others are seldom applied. Some indicators were also identified that are regarded as very or extremely suitable to evaluate the sustainability performance of a SC4.0. The main contribution of this research to the body of knowledge is the empirical insights on the SC4.0 field and on Supply Chain Sustainability performance measurement. The results provide guidelines for the selection of advanced technologies to support SC processes and for the design of sustainable SC4.0 performance measurement systems. Full article

(This article belongs to the Special Issue Industrial Engineering and Management: Current Issues and Trends)

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17 pages, 2157 KiB

Open AccessArticle

Comparing Semantic Differential Methods in Affective Engineering Processes: A Case Study on Vehicle Instrument Panels

by Gee Won Shin, Sunghwan Park, Yong Min Kim, Yushin Lee and Myung Hwan Yun

Appl. Sci. 2020, 10(14), 4751; https://doi.org/10.3390/app10144751 - 10 Jul 2020

Cited by 5 | Viewed by 2913

Abstract

When developing a user-oriented product, it is crucial to consider users’ affective needs. Various semantic differential (SD) methods have been used to identify affect regarding materials, and this is the most important property in products. This study aims to determine which of the [...] Read more.

When developing a user-oriented product, it is crucial to consider users’ affective needs. Various semantic differential (SD) methods have been used to identify affect regarding materials, and this is the most important property in products. This study aims to determine which of the three conventional SD methods (absolute evaluation 1 [AE 1], absolute evaluation 2 [AE 2], or relative evaluation [RE]) is most effective for affective evaluation. Affective evaluation was performed for vehicle instrument panels by each of these three SD methods. Two quantitative analysis methods (correlation analysis and repeated-measures ANOVA) were used to examine the performance (sample distinguishability) of each evaluation method, and it was found that both AE 2 and RE produced better results than AE 1. The correlation coefficients and p-values in correlation analysis were slightly better for RE than for AE 2. In conclusion, an affective evaluation produced better results when pairwise samples (especially one sample pair) were presented, indicating that maintaining distinct samples is very important. The clearer the difference in comparison targets is, the more accurate the evaluation results. Full article

(This article belongs to the Special Issue Industrial Engineering and Management: Current Issues and Trends)

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19 pages, 1590 KiB

Open AccessArticle

A Study on Identification of Development Status of MASS Technologies and Directions of Improvement

by Chong-Ju Chae, Mingyu Kim and Hyung-Ju Kim

Appl. Sci. 2020, 10(13), 4564; https://doi.org/10.3390/app10134564 - 30 Jun 2020

Cited by 44 | Viewed by 5265

Abstract

The introduction of the maritime autonomous surface ship (MASS) to the maritime industry will open up a new era and bring about a new paradigm shift in terms of cost efficiency, maritime accidents, and human resources. Various studies are currently being conducted to [...] Read more.

The introduction of the maritime autonomous surface ship (MASS) to the maritime industry will open up a new era and bring about a new paradigm shift in terms of cost efficiency, maritime accidents, and human resources. Various studies are currently being conducted to realize the MASS. Understanding the scope and direction of these studies will be of great help for future MASS research. In this study, the current development status of technologies for autonomous ships is identified, and considerations and directions of improvement are suggested for six major research fields that cover all technological issues of MASS. Firstly, the results of the regulatory scoping exercise (RSE) on the International Maritime Organization (IMO) conventions to accept MASSs are identified; in particular, human elements are identified as vital issues to be considered for the design and operation of MASSs. Secondly, various studies on the decision-making system are identified, and the future direction is suggested. Thirdly, in terms of ship design and propulsion system, design changes for autonomous cargo ships are investigated, with their potential impacts to be considered. Fourthly, the communication system will need to be robust and supported by multiple systems to minimize potential risk with third-party infrastructures, and suitable protection of systems, networks, and data will be required as an integral part of the safety system for cybersecurity. Fifthly, issues of maintenance and repair are identified, with a maintenance strategy to be considered. Lastly, hazard analysis of the autonomous ship is explored, and system-theoretic process analysis (STPA) and the functional resonance analysis method (FRAM) are identified as the most representative new methods that can be used for hazard analysis of autonomous ships. Full article

(This article belongs to the Special Issue Industrial Engineering and Management: Current Issues and Trends)

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24 pages, 2007 KiB

Open AccessArticle

A Social Life Cycle Assessment Framework for Additive Manufacturing Products

by Bardia Naghshineh, Francisco Lourenço, Radu Godina, Celeste Jacinto and Helena Carvalho

Appl. Sci. 2020, 10(13), 4459; https://doi.org/10.3390/app10134459 - 28 Jun 2020

Cited by 22 | Viewed by 4139

Abstract

Additive Manufacturing (AM) is viewed as a disruptive technology with the potential to replace many manufacturing processes. With its rapid proliferation in recent years, it is crucial to understand how to measure this technology’s social impacts. There are many studies available in the [...] Read more.

Additive Manufacturing (AM) is viewed as a disruptive technology with the potential to replace many manufacturing processes. With its rapid proliferation in recent years, it is crucial to understand how to measure this technology’s social impacts. There are many studies available in the existing literature regarding the economic and environmental impacts of AM technology. However, research regarding the social impacts of this technology is still scarce. To this end, this research has developed a framework based on Social Life Cycle Assessment (SLCA) methodology to measure AM products’ social impacts throughout their life cycle stages. The proposed framework includes an underlying mathematical model that was developed to allow for the aggregation of indicator scores. Additionally, cut-off scores were determined to differentiate between positive and negative social impacts. This framework can be applied to case studies, which provides a final score that quantifies the social impacts of an AM product throughout all its life cycle stages. It also provides scores for each stakeholder category and life cycle stage, which facilitates the identification of hotspots that require attention from organizations. Full article

(This article belongs to the Special Issue Industrial Engineering and Management: Current Issues and Trends)

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17 pages, 513 KiB

Open AccessArticle

Earnings Drivers of Slovak Manufacturers: Efficiency Assessment of Innovation Management

by Pavol Durana, Anna Zauskova, Ladislav Vagner and Silvia Zadnanova

Appl. Sci. 2020, 10(12), 4251; https://doi.org/10.3390/app10124251 - 21 Jun 2020

Cited by 25 | Viewed by 2978

Abstract

In innovation management, it is crucial to know the incentives or factors that, in many cases, provide the fundamental drivers of earnings, competitive advantage and the sustainable growth of businesses while also measuring their effectiveness. The study deals with the evaluation of the [...] Read more.

In innovation management, it is crucial to know the incentives or factors that, in many cases, provide the fundamental drivers of earnings, competitive advantage and the sustainable growth of businesses while also measuring their effectiveness. The study deals with the evaluation of the efficiency of investments in innovations utilizing constant returns to scale models of small- and medium-sized industrial enterprises in Slovakia. It is industrial production that includes enterprises that are the creators of new products, the appliers of the latest knowledge of science, and the creators of innovations. The main objective of the study is to evaluate the effectiveness of invested finances in the innovation of small- and medium-sized production enterprises in Slovakia, as it is a very demanding and neglected role in management. The method to assess the efficacy that was used is called Data Envelopment Analysis. CCR-I also CCR-O models were run, where it was essential to determine the inputs and outputs. The indicators R&D expenditures and employee training costs were selected based on a detailed analysis of articles with similar issues. The final sample contained 132 manufacturing enterprises within industrial production that were classified according to the official Slovak categorization because of their relevance. We assessed the effectiveness of food producers, beverage manufacturers, textile and clothing manufacturers, manufacturers of rubber plastic products, metal manufacturers, PC, electronic and optical equipment manufacturers, machine and equipment manufacturers, and furniture manufacturers to identify the enterprises that own earnings drivers caused by innovation. It was detected that the most efficient units in the industrial production are the rubber plastic products manufacturers. The least effective units were found in beverage and furniture manufacturers. Full article

(This article belongs to the Special Issue Industrial Engineering and Management: Current Issues and Trends)

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14 pages, 3311 KiB

Open AccessCommunication

Eight Weeks Later—The Unprecedented Rise of 3D Printing during the COVID-19 Pandemic—A Case Study, Lessons Learned, and Implications on the Future of Global Decentralized Manufacturing

by Tobias Mueller, Ahmed Elkaseer, Amal Charles, Janin Fauth, Dominik Rabsch, Amon Scholz, Clarissa Marquardt, Katja Nau and Steffen G. Scholz

Appl. Sci. 2020, 10(12), 4135; https://doi.org/10.3390/app10124135 - 16 Jun 2020

Cited by 24 | Viewed by 5142

Abstract

The eruption of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (corona virus disease, COVID-19) in Wuhan, China, and its global spread has led to an exponentially growing number of infected patients, currently exceeding over 6.6 million and over 390,000 deaths as of [...] Read more.

The eruption of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (corona virus disease, COVID-19) in Wuhan, China, and its global spread has led to an exponentially growing number of infected patients, currently exceeding over 6.6 million and over 390,000 deaths as of the 5th of June 2020. In this pandemic situation, health systems have been put under stress, and the demand for personal protective equipment (PPE) exceeded the delivery capabilities of suppliers. To address this issue, 3D printing was identified as a possible solution to quickly produce PPE items such as face shields, mask straps, masks, valves, and ear savers. Around the world, companies, universities, research institutions, and private individuals/hobbyists stepped into the void, using their 3D printers to support hospitals, doctors, nursing homes, and even refugee camps by providing them with PPE. In Germany, the makervsvirus movement took up the challenge and connected thousands of end users, makers, companies, and logistic providers for the production and supply of face shields, protective masks, and ear savers. The Karlsruhe Institute of Technology (KIT) also joined the makervsvirus movement and used its facilities to print headbands for face shield assemblies and ear savers. Within this paper, the challenges and lessons learned from the quick ramp up of a research laboratory to a production site for medium-sized batches of PPE, the limitations in material supply, selection criteria for suitable models, quality measures, and future prospects are reported and conclusions drawn. Full article

(This article belongs to the Special Issue Industrial Engineering and Management: Current Issues and Trends)

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14 pages, 1147 KiB

Open AccessArticle

Fuzzy Supplier Selection Method Based on Smaller-The-Better Quality Characteristic

by Chun-Min Yu, Kuen-Suan Chen, Kuei-Kuei Lai and Chang-Hsien Hsu

Appl. Sci. 2020, 10(10), 3635; https://doi.org/10.3390/app10103635 - 24 May 2020

Cited by 22 | Viewed by 2793

Abstract

Many important parts of tool machines all have the important smaller-the-better (STB) quality characteristics. The important STB quality characteristics will impact on the quality of the end-product. At the same time, supplier quality influences the quality and functionality of the end-product, so suppliers [...] Read more.

Many important parts of tool machines all have the important smaller-the-better (STB) quality characteristics. The important STB quality characteristics will impact on the quality of the end-product. At the same time, supplier quality influences the quality and functionality of the end-product, so suppliers must be selected with caution. The six sigma quality index for the STB quality characteristics can directly reflect process quality levels. Besides, this index possesses a mathematical relationship with process yield. Nevertheless, the point estimation will cause the risk of misjudgment, due to sampling errors. As a result, this study applies the confidence interval of the index to a two-tailed fuzzy testing method, in order to select appropriate suppliers. Now that this method is on the basis of the confidence interval, the possibility of misjudgment caused by sampling errors will be reduced, while the precision of the selection will be enhanced. The method can help companies increase product quality, as well as the competitiveness of the industry chain as a whole. Finally, a numerical example is presented to show how to approach this method and its efficacy. Full article

(This article belongs to the Special Issue Industrial Engineering and Management: Current Issues and Trends)

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23 pages, 1395 KiB

Open AccessFeature PaperArticle

A Combined Use of TRIZ Methodology and Eco-Compass tool as a Sustainable Innovation Model

by Rodrigo Boavida, Helena Navas, Radu Godina, Helena Carvalho and Hiroshi Hasegawa

Appl. Sci. 2020, 10(10), 3535; https://doi.org/10.3390/app10103535 - 20 May 2020

Cited by 33 | Viewed by 5702

Abstract

In recent years, there has been an increase in the adoption of quality tools by companies. As such, there has been a commitment to innovation by the organizations to obtain competitive advantages by the development of new products and technologies focused on the [...] Read more.

In recent years, there has been an increase in the adoption of quality tools by companies. As such, there has been a commitment to innovation by the organizations to obtain competitive advantages by the development of new products and technologies focused on the creation of economic value but also on delivering sustainability. This study aims to develop an application model of the inventive resolution theory in conjunction with the Eco-Compass ecological innovation tool, in order to allow solutions to be obtained systematically, and to present a performance increase of certain environmental parameters, promoting thus sustainable innovation. The case study research methodology is used to frame the research. The company under study is Nokia enterprise, located in Portugal, which offers a set of services related to telecommunications infrastructures. The unit of analysis is the department of transformation and continuous improvement, and the study illustrated the application of combined use of theory of inventive problem solving (TRIZ) and Eco-compass to develop innovative solutions systematically. The results show that it is possible to achieve innovation according to a certain level of established sustainable environmental parameters, while at the same time solving the identified inventive problem. Full article

(This article belongs to the Special Issue Industrial Engineering and Management: Current Issues and Trends)

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21 pages, 401 KiB

Open AccessFeature PaperArticle

Supplier Replacement Model in a One-Level Assembly System under Lead-Time Uncertainty

by Hasan Murat Afsar, Oussama Ben-Ammar, Alexandre Dolgui and Faicel Hnaien

Appl. Sci. 2020, 10(10), 3366; https://doi.org/10.3390/app10103366 - 13 May 2020

Cited by 4 | Viewed by 2598

Abstract

Supplier selection/replacement strategies, purchasing price negotiation and optimized replenishment policies play a key role in efficient supply chain management in today’s dynamic market. Their importance increases even more in Industry 4.0. In this paper, we propose a joint model of replenishment planning and [...] Read more.

Supplier selection/replacement strategies, purchasing price negotiation and optimized replenishment policies play a key role in efficient supply chain management in today’s dynamic market. Their importance increases even more in Industry 4.0. In this paper, we propose a joint model of replenishment planning and purchasing price negotiation in the context of supplier replacement in a one-level assembly system (OLAS) producing one type of finished product. The real component lead times are stochastic. There is consequently a non-negligible risk that the assembly process may be stopped if all components for assembly are not delivered on the due date. This incurs inventory-related costs, holding and backlogging, which should be minimized. We consider a set of suppliers characterized by their prices and the probability distributions of their lead-times, and we present a model and an approach that optimize not only replenishment policy, but also purchasing prices. For a given unit, it is possible to model several alternative suppliers with alternative pricing and lead-time uncertainties, and evaluate their impacts on the total cost: composed of holding, backlogging and purchasing costs for the assembly system. The findings of this study indicate that it can be beneficial to pay suppliers an additional purchase cost in order to reduce the holding and backlogging costs related to uncertainty. In consequence, decision makers can use the proposed approach to negotiate prices and delivery delays or to select suppliers. Full article

(This article belongs to the Special Issue Industrial Engineering and Management: Current Issues and Trends)

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12 pages, 3636 KiB

Open AccessCommunication

Remote Sensing of Sewing Work Levels Using a Power Monitoring System

by Woo-Kyun Jung, Yong-Chul Park, Jae-Won Lee and Eun Suk Suh

Appl. Sci. 2020, 10(9), 3104; https://doi.org/10.3390/app10093104 - 29 Apr 2020

Cited by 5 | Viewed by 3578

Abstract

The measurement of sewing work in the labor-intensive garment industry depends considerably on the person performing the measurements, making it difficult to quantitatively define the level of skill (L_S) of the sewing machine operator and the level of difficulty ( [...] Read more.

The measurement of sewing work in the labor-intensive garment industry depends considerably on the person performing the measurements, making it difficult to quantitatively define the level of skill (L_S) of the sewing machine operator and the level of difficulty (L_D) of the unit process. In this study, a power monitoring system attached to the sewing machine was used to remotely collect power consumption data, which were then analyzed to extract the working times for a series of sewing tasks. L_S of each operator was then classified and L_D of each process was analyzed in terms of working time and quality. Finally, the resulting L_S and L_D weight factors considered to optimize the subject garment production line were compared against those proposed by experts. The L_S weight factor proposed by the experts was ~15% less than that indicated by the experimental results, whereas the L_D weight factor proposed by the experts was ~15%–40% greater than that indicated by the experimental results. The results of this study suggest that the proposed method could be applied in real time to inform the arrangement of line workers to increase the productivity of a garment production line. Full article

(This article belongs to the Special Issue Industrial Engineering and Management: Current Issues and Trends)

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20 pages, 3982 KiB

Open AccessArticle

Towards an Ergonomic Assessment Framework for Industrial Assembly Workstations—A Case Study

by Ana Colim, Carlos Faria, Ana Cristina Braga, Nuno Sousa, Luís Rocha, Paula Carneiro, Nélson Costa and Pedro Arezes

Appl. Sci. 2020, 10(9), 3048; https://doi.org/10.3390/app10093048 - 27 Apr 2020

Cited by 51 | Viewed by 8994

Abstract

Work-related musculoskeletal disorders (WMSD) are one of the main occupational health problems. The best strategy to prevent them lies on ergonomic interventions. The variety of industrial processes and environments, however, makes it difficult to define an all-purpose framework to guide these ergonomic interventions. [...] Read more.

Work-related musculoskeletal disorders (WMSD) are one of the main occupational health problems. The best strategy to prevent them lies on ergonomic interventions. The variety of industrial processes and environments, however, makes it difficult to define an all-purpose framework to guide these ergonomic interventions. This undefinition is exacerbated by recurrent introduction of new technologies, e.g., collaborative robots. In this paper, we propose a framework to guide ergonomics and human factors practitioners through all stages of assessment and redesign of workstations. This framework was applied in a case study at an assembly workstation of a large furniture enterprise. Direct observation of work activity and questionnaires were applied to characterize the workstations, the process, and the workers’ profiles and perceptions. An ergonomic multi-method approach, based on well-known and validated methods (such as the Finnish Institute of Occupational Health and Rapid Upper Limb Assessment), was applied to identify the most critical risk factors. We concluded that this approach supports the process redesign and tasks’ allocation of the future workstation. From these conclusions, we distill a list of requirements for the creation of a collaborative robot cell, specifying which tasks are performed by whom, as well as the scheduling of the human-robot collaboration (HRC). Full article

(This article belongs to the Special Issue Industrial Engineering and Management: Current Issues and Trends)

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15 pages, 1237 KiB

Open AccessArticle

Will Bid/No-Bid Decision Factors for Construction Projects Be Different in Economic Downturns? A Chinese Study

by Jinxiu Wang, Lin Wang, Kunhui Ye and Yongwei Shan

Appl. Sci. 2020, 10(5), 1899; https://doi.org/10.3390/app10051899 - 10 Mar 2020

Cited by 12 | Viewed by 4593

Abstract

Whether to bid on construction work is a traditional question that is often challenged in different economic situations. What will the decision factors be when contractors have to struggle to achieve growth in economic downturns? Since previous studies have not widely agreed with [...] Read more.

Whether to bid on construction work is a traditional question that is often challenged in different economic situations. What will the decision factors be when contractors have to struggle to achieve growth in economic downturns? Since previous studies have not widely agreed with each other on this issue, this study aims to examine China’s construction engineering contractors in recent “bad” years. The research findings reveal that the cluster related to expected profitability, including terms of payment, reputation of the client regarding his/her commitment to making timely payments, original price estimated by the client, profit track record for similar projects, and contract type, were the most significant determinants. The bid/no-bid decision-making process comprises three modules, including the contractor’s strategies, the contractor’s competency for a project, and expected competition. These results suggest that competing for survival is the dominant position of contractors in making bid/no-bid decisions in economic downturns. Full article

(This article belongs to the Special Issue Industrial Engineering and Management: Current Issues and Trends)

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22 pages, 3395 KiB

Open AccessArticle

Assessment of Handover Prediction Models in Estimation of Cycle Times for Manual Assembly Tasks in a Human–Robot Collaborative Environment

by Kuo-Hao Tang, Chia-Feng Ho, Jan Mehlich and Shih-Ting Chen

Appl. Sci. 2020, 10(2), 556; https://doi.org/10.3390/app10020556 - 12 Jan 2020

Cited by 12 | Viewed by 3528

Abstract

The accuracy and fluency of a handover task affects the work efficiency of human–robot collaboration. A precise and proactive estimation of handover time points by robots when handing over assembly parts to humans can minimize waiting times and maximize efficiency. This study investigated [...] Read more.

The accuracy and fluency of a handover task affects the work efficiency of human–robot collaboration. A precise and proactive estimation of handover time points by robots when handing over assembly parts to humans can minimize waiting times and maximize efficiency. This study investigated and compared the cycle time, waiting time, and operators’ subjective preference of a human–robot collaborative assembly task when three handover prediction models were applied: traditional method-time measurement (MTM), Kalman filter, and trigger sensor approaches. The scenarios of a general repetitive assembly task and repetitive assembly under a learning curve were investigated. The results revealed that both the Kalman filter prediction model and the trigger sensor method were superior to the MTM fixed-time model in both scenarios in terms of cycle time and subjective preference. The Kalman filter prediction model could adjust the handover timing according to the operator’s current speed and reduce the waiting time of the robot and operator, thereby improving the subjective preference of the operator. Moreover, the trigger sensor method’s inherent flexibility concerning random single interruptions on the operator’s side earned it the highest scores in the satisfaction assessment. Full article

(This article belongs to the Special Issue Industrial Engineering and Management: Current Issues and Trends)

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20 pages, 2658 KiB

Open AccessArticle

A Fuzzy-Based Holistic Approach for Supply Chain Risk Assessment and Aggregation Considering Risk Interdependencies

by Alina Díaz-Curbelo, Ángel M. Gento, Alfonso Redondo and Faisal Aqlan

Appl. Sci. 2019, 9(24), 5329; https://doi.org/10.3390/app9245329 - 6 Dec 2019

Cited by 9 | Viewed by 3185

Abstract

Supply chain risk management requires dealing with uncertainty, interrelations, and subjectivity inherent in the risk assessment process. This paper proposes a holistic approach for risk management that considers the impact on multiple performance objectives, the relation between risk agents, and the risk event [...] Read more.

Supply chain risk management requires dealing with uncertainty, interrelations, and subjectivity inherent in the risk assessment process. This paper proposes a holistic approach for risk management that considers the impact on multiple performance objectives, the relation between risk agents, and the risk event interdependencies. An aggregated risk score is proposed to capture the cascading effects of common risk triggers and quantify the aggregated score by risk agent and objective. The approach also uses fuzzy logic to allow for the treatment of vague and ambiguity data as input parameters to the model from different domains and scales, according to knowledge and criteria nature. The integration of the balanced scorecard tool improves the analysis and prioritization of mitigation strategies in decision-making, both by risk agent and by strategic objective. A case study of a telecommunication company is presented to illustrate the applicability of the proposed approach. Full article

(This article belongs to the Special Issue Industrial Engineering and Management: Current Issues and Trends)

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18 pages, 2549 KiB

Open AccessArticle

Supplier Selection and Performance Evaluation for High-Voltage Power Film Capacitors in a Fuzzy Environment

by Chun-Ming Yang, Kuen-Suan Chen, Ting-Hsin Hsu and Chang-Hsien Hsu

Appl. Sci. 2019, 9(23), 5253; https://doi.org/10.3390/app9235253 - 3 Dec 2019

Cited by 8 | Viewed by 3426

Abstract

Rapid advances in technology have shortened the upgrade and replacement cycles in industries such as electronics, household appliances, and communication technologies. Within these industries, high-voltage power film capacitors have become indispensable electrical components due to their good electrical performance and high reliability. The [...] Read more.

Rapid advances in technology have shortened the upgrade and replacement cycles in industries such as electronics, household appliances, and communication technologies. Within these industries, high-voltage power film capacitors have become indispensable electrical components due to their good electrical performance and high reliability. The selection and evaluation of suppliers of these capacitors is therefore increasingly important. Suppliers play a crucial role in the electronics industry; the quality of their products determines the degree to which the quality of the final product can be guaranteed. Supplier quality also affects the ability of all the members in a supply chain to control costs. Evaluation by decision-makers is highly significant in the supplier selection process. However, when the opinions of multiple decision-makers are combined, issues such as cognitive differences, fuzzy linguistics, and uncertainty are common. This study presents a supplier performance index S_PL and derives the estimates of the index S_PL and its statistical properties. The proposed index is not only helpful for the accurate measurement of supplier performance; it can also reduce cognitive differences among evaluators in the decision-making process (that is, the sample variability associated with the Likert scale). Evaluation scores for each criterion for the linguistic labels are converted to triangular fuzzy numbers in order to reduce ambiguity. Subsequently, integrated crisp values are obtained by defuzzification in a fuzzy inference system. A real-world case study of the supplier selection of high-voltage power film capacitors is provided to illustrate the efficacy of the proposed method. Full article

(This article belongs to the Special Issue Industrial Engineering and Management: Current Issues and Trends)

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12 pages, 503 KiB

Open AccessArticle

Modeling and Analysis of Multiple-Supplier Selection Problem with Price Discounts and Routing Decisions

by Selin Çabuk and Rızvan Erol

Appl. Sci. 2019, 9(17), 3480; https://doi.org/10.3390/app9173480 - 23 Aug 2019

Cited by 5 | Viewed by 2742

Abstract

This study investigates a multiple-supplier selection problem in which a firm or buyer aims to find an optimal set of suppliers to satisfy its demand for multiple components for a planning horizon. A distinctive feature of our problem formulation is to integrate decisions [...] Read more.

This study investigates a multiple-supplier selection problem in which a firm or buyer aims to find an optimal set of suppliers to satisfy its demand for multiple components for a planning horizon. A distinctive feature of our problem formulation is to integrate decisions relevant to supplier selection, such as determining the order quantities from each supplier under price discounts and the order collection routes for multiple vehicles. In other words, the traveling purchaser problem is combined with multiple supplier selection. A new mixed-integer programming model is developed to optimally solve this problem. The model considers costs of inventory holding, ordering, transportation and purchasing along with supplier’s supply capacity, vehicle capacity constraints. A numerical example is provided to illustrate how the model is executed. Scenario analysis is performed to assess the model’s results under varying conditions. Full article

(This article belongs to the Special Issue Industrial Engineering and Management: Current Issues and Trends)

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18 pages, 2586 KiB

Open AccessArticle

Analysis of the Impact of the “Sea Toll” Program for Seaports: Resilience and Competitiveness

by Lalu Tri Wijaya Nata Kusuma and Fu-Shiang Tseng

Appl. Sci. 2019, 9(16), 3407; https://doi.org/10.3390/app9163407 - 19 Aug 2019

Cited by 11 | Viewed by 5182

Abstract

Maritime transportation is one of the most important global activities, especially for archipelagic countries. Inland components that exist within the seaport system, such as port authorities who manage passenger and cruise services even for container unloading and loading areas, have become an important [...] Read more.

Maritime transportation is one of the most important global activities, especially for archipelagic countries. Inland components that exist within the seaport system, such as port authorities who manage passenger and cruise services even for container unloading and loading areas, have become an important aspect to improve performance and determine competitive strategies for seaports. The importance of this interdependence between ports with passenger services and container seaports led us to investigate the impact of the “sea toll” program on seaport resilience and competitiveness. Although the concept of a “sea toll” was initiated by the US government in 2011, there are only a few, if any, studies or clear standards related to the development of “sea toll” systems in archipelago countries. We conducted an empirical study in Indonesia through an online survey of key stakeholders of seaports, including shipping companies, seaport authorities, commodities companies, and government. The data were analyzed using the analytical hierarchy process technique and the results showed that the “sea toll” had an impact on seaport resilience and competitiveness. For seaport resilience, the “sea toll” had an impact on the strategic alliance. For competitiveness, the “sea toll” had an impact on seaport performance, including ship calling frequency and reliability. Full article

(This article belongs to the Special Issue Industrial Engineering and Management: Current Issues and Trends)

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16 pages, 1288 KiB

Open AccessArticle

Service Innovation Model of the Automobile Service Industry

by Chia-Nan Wang, Jen-Der Day and Muhammad Farid

Appl. Sci. 2019, 9(12), 2403; https://doi.org/10.3390/app9122403 - 13 Jun 2019

Cited by 7 | Viewed by 6467

Abstract

Service innovations in the service industry will improve its ability to compete in maintenance as well as increase the number of customers. Measuring service innovations according to the characteristics of the automobile industry is important. Thus, the aim of this paper is to [...] Read more.

Service innovations in the service industry will improve its ability to compete in maintenance as well as increase the number of customers. Measuring service innovations according to the characteristics of the automobile industry is important. Thus, the aim of this paper is to develop a model to measure service innovation in the automobile service industry. A structural equation model is created based on theory and previous models. Data about the industry’s perception of service innovation are collected from questionnaires in Kaohsiung, Taiwan. Samples were collected from 61 authorized automobile service centers. The results indicate that customer demand, competition, and a knowledge-based network as enabler factors are positively correlated with service innovation. Furthermore, a new service concept, new client interface, new service delivery system, and new technology options are positively related to service innovation. Finally, service innovation has a significant positive effect on a firm’s performance. This study developed an effective service innovation model of the automobile service industry. Full article

(This article belongs to the Special Issue Industrial Engineering and Management: Current Issues and Trends)

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20 pages, 776 KiB

Open AccessArticle

A Study of Applying Fuzzy Theory in Simulation-Based Education

by Shao-Yu Liu and Yu-Cheng Wang

Appl. Sci. 2019, 9(10), 1989; https://doi.org/10.3390/app9101989 - 15 May 2019

Cited by 4 | Viewed by 2883

Abstract

Among all aviation accidents in Taiwan’s general aviation industry from 1998 to 2016, human factors account for the most at 51.2%, including negligence of external obstacles, poor autopilot flight ability, poor resources management of the crew, inability to follow aviation regulations, lack of [...] Read more.

Among all aviation accidents in Taiwan’s general aviation industry from 1998 to 2016, human factors account for the most at 51.2%, including negligence of external obstacles, poor autopilot flight ability, poor resources management of the crew, inability to follow aviation regulations, lack of understanding of the landing area, not fully comprehending the operational functions and not alert to situations. Those factors have seriously affected flight safety. Resources management training for crew members may thus be the best measure to prevent human errors. Following the Evidence-Based Training (EBT) promoted by ICAO and International Air Transport Association (IATA), this study constructs the assessment indices of EBT for helicopter crews. After collecting the opinions of helicopter flight instructors of military and civil helicopter units, we apply the Fuzzy Delphi Method (FDM) for the preliminary assessment guidelines, use the Fuzzy Analytic Hierarchy Process (FAHP) to construct the hierarchy, and then calculate each criterion and each criterion weight. Full article

(This article belongs to the Special Issue Industrial Engineering and Management: Current Issues and Trends)

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18 pages, 2783 KiB

Open AccessArticle

Using Product Network Analysis to Optimize Product-to-Shelf Assignment Problems

by Haisong Huang, Liguo Yao, Jyu-Shang Chang, Chieh-Yuan Tsai and R.J. Kuo

Appl. Sci. 2019, 9(8), 1581; https://doi.org/10.3390/app9081581 - 17 Apr 2019

Cited by 4 | Viewed by 3791

Abstract

A good product-to-shelf assignment strategy not only helps customers easily find desired product items but also increases retailer profit. Recent research has attempted to solve product-to-shelf problems using product association analysis, a powerful data mining tool that can detect significant co-purchase rules underlying [...] Read more.

A good product-to-shelf assignment strategy not only helps customers easily find desired product items but also increases retailer profit. Recent research has attempted to solve product-to-shelf problems using product association analysis, a powerful data mining tool that can detect significant co-purchase rules underlying a large amount of purchase transaction data. While some studies have developed efficient approaches for this task, they largely overlook important factors related to optimizing product-to-shelf assignment, including product characteristics, physical proximity, and category constraints. This paper proposes a three-stage product-to-shelf assignment method to address this shortcoming. The first stage constructs a product relationship network that represents the purchase association among product items. The second stage derives the centrality value of each product item through network analysis. Based on the centrality of each product, an item is classified as an attraction item, an opportunity item, or a trivial item. The third stage considers purchase association, physical relationship, and category constraint when evaluating the location preference of each product. Based on the location preference values, a product assignment algorithm is then developed to optimize locations for opportunity items. A series of analyses and comparisons on the performance of different network types are conducted. It is found that the two network types provide variant managerial meanings for store managers. In addition, the implementation and experimental results show the proposed method is feasible and helpful. Full article

(This article belongs to the Special Issue Industrial Engineering and Management: Current Issues and Trends)

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Review

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23 pages, 3068 KiB

Open AccessReview

Modeling of Business Intelligence Systems Using the Potential Determinants and Theories with the Lens of Individual, Technological, Organizational, and Environmental Contexts-A Systematic Literature Review

by Sumera Ahmad, Suraya Miskon, Tawfeeq Abdullah Alkanhal and Iskander Tlili

Appl. Sci. 2020, 10(9), 3208; https://doi.org/10.3390/app10093208 - 4 May 2020

Cited by 39 | Viewed by 8665

Abstract

Race towards industry 4.0 increases the hyper competition and puts pressure on organizations to integrate the advanced technologies. Business intelligence system (BIS) is one of the top prioritized technologies that attracted the significant attention of policy-makers and industry experts due to its ability [...] Read more.

Race towards industry 4.0 increases the hyper competition and puts pressure on organizations to integrate the advanced technologies. Business intelligence system (BIS) is one of the top prioritized technologies that attracted the significant attention of policy-makers and industry experts due to its ability to provide more informed and intelligent knowledge for decision-making processes. It is evident by literature that organizations and industries are prone to integrate the BIS at large scale, but more than 70% BIS projects fail to give the expected results. Hence, it is pertinent to explore the significant determinants that influence the BIS adoption and acceptance in organizations. Although previous literature did not have any comprehensive review relevant to the individual, technological, organizational, and environmental determinants. Therefore, the current study tries to narrow this gap by a systematic literature review (SLR) of 84 studies that were published during the period of 2011–2020. A total of 93 determinants are identified based on content analysis by using text mining techniques of Yoshikoder and human coding skills. The identified determinants are ranked according to their frequency of use. A theoretical framework has been developed with potential determinants and theories. The study results will enrich the recent BIS literature and improve the understanding of practitioners’ decision-making processes to leverage maximum value from the adoption of BIS. Full article

(This article belongs to the Special Issue Industrial Engineering and Management: Current Issues and Trends)

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