Showing 225 results for Ai
Mansour Abedian, Amirhossein Karimpour, Morteza Pourgharibshahi, Atefeh Amindoust,
Volume 35, Issue 2 (6-2024)
Abstract
The area coverage of machines on the production line to address the scheduling and routing problem of autonomous guided vehicles (AGV) is an innovative way to improve productivity in manufacturing enterprises. This paper proposed a new model for the optimal area coverage of machines in the production line by applying a single AGV to minimize both the transfer costs and the number of breakpoints of AGV. One of the unique advantages of the area coverage employed in the present study is that it minimizes transfer costs and breakpoints, and makes it possible to provide service for several machines simultaneously since the underlying assumption was finding a path to ensure that every point in a given workspace is covered at least once. Since rail AGV is used in this study, AGV can only pass horizontal and vertical distances in the production line. The reversal of the AGV path in vertical and horizontal distances implies failure and breakpoint in the present paper. The simulation results confirm the feasibility of the proposed method.
Zahra Taherikhonakdar, Hamed Fazlollahtabar,
Volume 35, Issue 2 (6-2024)
Abstract
These days, industries, individuals and organizations are highly dependent on software. Software plays an important role in our daily life. They use in embedded systems, databases, computers, mobiles etc. Great demand for ICT cause environmental problem and endanger the future sustainability. In this case, sustainable development has become a hot research topic in software engineering community. Sustainability as a software quality is a general term. Therefore, there is a chance that software developers mislead about develops sustainable software. Therefore, there are some questions that should be answered to help practitioners to develop sustainable software: how developers could develop green and sustainable software? What requirements should be considered to reach green and sustainable software? Which non-functional requirement has an effect on each sustainability dimension? In this paper, we selected 20 non-functional requirements out of 60. It was identified the effective non-functional requirements in green and sustainable software development by using Delphi method then via interpretive structural modeling (ISM). The study aimed to pave the way for software eco-labeling and help users to choose the green and sustainable one. Also, provide software developers with guideline to develop green and sustainable software by identifying effective non-functional requirements. This would lead to the sustainable future and green environment.
Dian Dewi, Yustinus Hermanto, Martinus Sianto, Jaka Mulyana, Dian Trihastuti, Ivan Gunawan,
Volume 35, Issue 2 (6-2024)
Abstract
Supply chain agility (SCA) has emerged as a significant focus for industries and businesses, serving as a cornerstone for gaining a competitive edge and playing a pivotal role in supply chain management. This importance is further underscored in the context of Product–Service Systems (PSS), which involve the development of both products and services. Despite the existing body of research on SCA and PSS, there has been a notable dearth of empirical studies examining the readiness of PSS SCA. This study makes a substantial contribution by developing a valid and reliable framework to assess the readiness of PSS for supply chain agility. The process involves defining domains, generating items, analyzing agreement among raters, testing for response bias, and conducting exploratory and confirmatory factor analyses. Using structural equation modeling, the model's validity and reliability were evaluated through an online survey with 405 participants from official motorcycle service partners. The findings identify six key capability constructs: collaboration, knowledge transfer, service partner development, information sharing, logistic integration and supply chain agility. This examination of PSS SCA readiness and its constructs provides a validated tool for industry practitioners to enhance their supply chain agility.
Daniel Atnafu, Shimelis Zewdie Werke,
Volume 35, Issue 2 (6-2024)
Abstract
The incorporation of sustainable practices becomes crucial as firms transition from Industry 4.0 to Industry 5.0. Therefore, this systematic review explores the relationship between the two sustainability approaches; Green Human Resource Management (GHRM) and Green Supply Chain Management (GSCM) using peer-reviewed studies from 2016-2023, retrieved from Scopus and Web of Science databases. 2016 marks the starting point as the first relevant paper emerged in the literature in that year. The PRISMA approach was used to identify relevant studies, resulting in the inclusion of 30 studies for analysis purposes. The study reveals a growing interest in understanding the relationship between GHRM and GSCM practices and their impact on sustainable performance. The majority of reviewed studies utilized quantitative survey methods, suggesting the need for future research utilizing qualitative and mixed methods for gaining deeper insights. The review indicates that most studies are conducted in emerging countries, and there is a significant gap in research on the relationship between GHRM and GSCM practices in other context. Finally, the study provides valuable insights for practitioners and researchers, emphasising the importance of integrating GHRM and GSCM practices for a sustainable competitive advantage.
Melinska Ayu Febrianti, Qurtubi Qurtubi, Roaida Yanti, Hari Purnomo,
Volume 35, Issue 2 (6-2024)
Abstract
The retail industry is a vital sector of the world economy and is characterized by fierce competition, tight profit margins, and demanding consumers. Understanding customer buying behavior patterns is essential in devising the best retail strategy to enhance product sales. This research aims to comprehend customer shopping behaviors based on retail sales transactions and formulate the best strategies. By employing multi-level association rules, the dataset is arranged hierarchically into categories, sub-categories, and items. The sales transaction data used comprises 5830 transaction records over a month. The results of this study reveal 24 associations of categories, 49 associations of sub-categories, and 12 associations of product items. Moreover, the proposed marketing strategy offers recommendations including store layout improvement, planogram design, and bundled product offerings. This research addresses the gap in empirical evidence from a previous study and suggests further observation from diverse locations to authenticate the findings, which may yield various outcomes
Tenaw Tegbar Tsega, Thoben Klaus-Dieter, Rao D.k.nageswara, Bereket Haile Woldegiorgis,
Volume 35, Issue 2 (6-2024)
Abstract
Ethiopia has made enormous efforts in the leather industry to gain manufacturing capabilities that can be scaled up to other sectors. Those efforts have resulted in the industry shifting its role from raw material supplier to producer of value-added products for the global supply chain (GSC). However, the industry has faced severe challenges in generating the expected revenue, utilizing capacity, and finally coping with the global competitive environment. Studies reveal that manufacturing firms tackle similar challenges by improving their supply chain performance (SCP). The challenges that appeared in the leather industry of Ethiopia could also be solved by improving its SCP. Nonetheless, there is a lack of study on the basic characteristics and SCP of the industry after it has shifted its role. The main objective of this study is, therefore, to measure the SCP to know where it stands using a bench mark and identify the elements that contribute considerably to the low overall SCP in order to lay the foundation for subsequent improvement. To achieve the research objective, data was collected from primary and secondary sources through a questionnaire, survey, observation, and focus group discussion. The data is analyzed using the supply chain operations reference model (SCOR version 12.0). Accordingly, the overall SCP is found to be 67.33%, suggesting an average rating as per the set benchmark. The source process is identified as the most influential element for the overall low SCP, with a percentage gap of 17.23%. Taking corrective action on the identified elements could help the industry overcome the existing challenges by improving its SCP.
Mariam Atwani, Mustapha Hlyal , Jamila El Alami ,
Volume 35, Issue 2 (6-2024)
Abstract
In today's dynamic and competitive manufacturing landscape, accurate demand forecasting is paramount for optimizing production processes, reducing inventory costs, and meeting customer demands efficiently. With the advent of Artificial Intelligence (AI), there has been a significant evolution in demand forecasting methods, enabling manufacturers to enhance the accuracy of the forecasts.
This systematic literature review aims to provide a comprehensive overview of the state-of-the-art on demand forecasting models in the manufacturing sector, whether AI-based models or hybrid methods merging both the AI technology and classical demand forecasting methods. The review begins by establishing an overview on demand forecasting methods, it then outlines the systematic methodology used for the literature search.
The review encompasses a wide range of scholarly articles published up to September 2023. A rigorous screening process is applied to select relevant studies. Accordingly, a thorough analysis in the basis of the forecasting methods adopted and data used have been carried out. By synthesizing the existing knowledge, this review contributes to the ongoing advancement of demand forecasting practices in the manufacturing sector providing researchers and practitioners an overview on the advancements on the use of AI models to improve the accuracy of demand forecasting models.
Amin Amini, Alireza Alinezhad, Davood Gharakhani,
Volume 35, Issue 2 (6-2024)
Abstract
The selection of a sustainable supplier is a multi-criteria decision-making issue that covers a range of criteria (quantitative-qualitative). Selecting the most eco-friendly suppliers requires balancing tangible and intangible elements that may be out of sync. The problem gets more complicated when volume discounts are taken into account, as the buyer needs to decide between two issues: 1) What are the best sustainable suppliers? 2) Which amount needs to be bought from each of the selected eco-friendly suppliers? In current study a combined attitude of best-worst method (BWM) ameliorated via multi-objective mixed integer programming (MOMIP) and rough sets theory is developed. The aim of this work is to contemporaneously ascertain the order quantity allocated to these suppliers in the case of multiple sourcing, multiple products with multiple criteria and with capacity constraints of suppliers and the number of suppliers to employ. In this situation, price reductions are offered by suppliers based on add up commerce volume, not on the amount or assortment of items acquired from them. Finally, a solution approach is proposed to solve the multi-objective model, and the model is demonstrated using a case study in Iran Khodro Company (IKCO). The results indicate that ISACO is the most sustainable supplier and the most orders are assigned to this supplier.
Fakhri Ikhwanul Alifin, Bermawi Priyatna Iskandar, Nadia Fasa, Fransisca Debora,
Volume 35, Issue 2 (6-2024)
Abstract
This study develops warranty cost models for repairable products subject to Lemon Laws, encompassing Critical and Non-Critical components forming a multi-component system. Failures can arise naturally or be induced by other components (i.e., failure interaction), defining a lemon if recurrent failures reach a threshold (k) during the warranty period. A lemon declaration triggers a refund or replacement by the manufacturer. Four warranty cost models are proposed from the manufacturer's standpoint, considering failure mechanisms. Increasing failure thresholds in the warranty scheme substantially decreases warranty cost rates. For instance, a threshold (k) of 5 in refund and replacement schemes yields the lowest cost rates of 33.7159 and 25.8249, respectively. Failure interactions escalate total warranty costs; for instance, in a refund scheme (k = 5), costs with failure interaction reach 31.0169 compared to 28.7603 without. Similar trends apply to replacement schemes. Moreover, a lower warranty cost rate will extend the period, indicating regulation fulfillment due to a closer warranty period to the Lemon period. Sensitivity analysis also underscores the role of higher reliability in reducing warranty costs and complying with Lemon Laws. Finally, maintenance strategies and product reliability are emphasized to fulfill Lemon Laws with minimal costs, i.e., fewer warranty claims.
Theodore Alvin Hartanto, Seng Hansun,
Volume 35, Issue 3 (9-2024)
Abstract
One method to diagnose retinal diseases is by using the Optical Coherence Tomography (OCT) scans. Annually, it is estimated that around 30 million OCT scans are performed worldwide. However, the process of analyzing and diagnosing OCT scan results by an ophthalmologist requires a long time so machine learning, especially deep learning, can be utilized to shorten the diagnosis process and speed up the treatment process. In this study, several pre-trained deep learning models are compared, including EfficientNet-B0, ResNet-50V2, Inception-V3, and DenseNet-169. These models will be fine-tuned and trained with a dataset containing OCT scanned images to classify four retinal conditions, namely Choroidal Neovascularization (CNV), Diabetic Macular Edema (DME), Drusen, and Normal. The models that have been trained are then tested to classify the test set and the results are evaluated using a confusion matrix in terms of accuracy, recall, precision, and F1-score. The results show that the model with the best classification results in the batch size of 32 scenario is the ResNet-50V2 model with an accuracy value of 98.24%, precision of 98.25%, recall of 98.24%, and F1-score of 98.24%. While for the batch size of 64, the EfficientNet-B0 model is the model with the best classification results with an accuracy value of 96.59%, precision of 96.84%, recall of 96.59%, and F1-score of 96.59%.
Yuvaraj M, Jothi Basu,
Volume 35, Issue 3 (9-2024)
Abstract
Refrigerated trucks in the cold chain enhance the shelf-life of food. In the fruit supply chain (FSC), if each different fruit necessitates its dedicated fleet of refrigerated vehicles, the total cost of the supply chain would increase. On the other hand, if there are several fruits in a single compartment, the quality and freshness of the fruits will be impacted since each fruit requires a different operating temperature. Therefore, partitions are necessary within the container. While the use of cold chain infrastructure will result in a reduction in food loss and an enhancement in food security, it will also incur an increase in the overall cost of the supply chain. Therefore, this paper aims to create a mixed integer non-linear programming (MINLP) mathematical model considering multi-compartment reefer trucks (MCRTs) to minimize the total cost in the FSC. To assess the efficiency of the model, a case study is carried out in India, and the formulated mathematical model is solved using a heuristic approach. The findings indicate that utilizing MCRTs leads to a reduction in the number of vehicles required and a drop in total supply chain cost. Three-compartment reefer trucks offer a more significant cost-saving advantage in the FSC compared to two-compartment reefer trucks. Furthermore, it is noted that operating three distribution centers (DCs) results in a reduction in the overall cost. The decrease in total supply chain costs enhances the affordability of fruits for low-income populations and contributes to the enhancement of food security. In addition to cost reduction, implementing MCRT has also beneficial environmental impacts such as decreased emissions due to a decrease in the number of trucks utilized and reduced food waste.
Khamiss Cheikh, El Mostapha Boudi, Hamza Mokhliss, Rabi Rabi,
Volume 35, Issue 3 (9-2024)
Abstract
Maintenance plan efficacy traditionally prioritizes long-term predicted maintenance cost rates, emphasizing performance-centric approaches. However, such criteria often neglect the fluctuation in maintenance costs over renewal cycles, posing challenges from a risk management perspective. This study challenges conventional solutions by integrating both performance and robustness considerations to offer more suitable maintenance options.
The study evaluates two representative maintenance approaches: a block replacement strategy and a periodic inspection and replacement strategy. It introduces novel metrics to assess these approaches, including long-term expected maintenance cost rate as a performance metric and variance of maintenance cost per renewal cycle as a robustness metric.
Mathematical models based on the homogeneous Gamma degradation process and probability theory are employed to quantify these strategies. Comparative analysis reveals that while higher-performing strategies may demonstrate cost efficiency over the long term, they also entail greater risk due to potential cost variability across renewal cycles.
The study underscores the necessity for a comprehensive evaluation that balances performance and resilience in maintenance decision-making. By leveraging the Monte Carlo Method, this research offers a critical appraisal of maintenance strategies, aiming to enhance decision-making frameworks with insights that integrate performance and robustness considerations.
Arifa Khan, Saravanan P,
Volume 35, Issue 3 (9-2024)
Abstract
Optimizing production in the plastic extrusion industry is a pivotal task for small scale industries. To enhance the efficiency in today’s competitive market being a small-scale manufacturer over their peers is challenging. With the limited resources, having constraints on manpower, capital, space, often facing fluctuations in demand and production, simultaneously maintaining high quality became very important for the success. Among the plethora of KPIS used in manufacturing, Overall Equipment Effectiveness (OEE) stands out as corner stone. In this study, we collected real-world data from a plastic extrusion company. i.e., an HDPE Pipe manufacturing company. It serves as the backdrop for our study, this is based on the plastic extrusion sector and set out a goal of enhancing OEE through a comparative investigation of various ML models. To forecast and estimate OEE values, we used various Machine Learning models and examine each algorithm’s performance using metrics like Mean Squared Error (MSE) and model comparisons using the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC), creating a comprehensive picture of each algorithm’s strength which enables the small businesses to make informed decisions and empowers them to stay agile and adapt to the changes in the manufacturing environment.
Zahrasadat Hasheminasab, Esmaeil Mazroui Nasrabadi, Zahra Sadeqi-Arani,
Volume 35, Issue 3 (9-2024)
Abstract
In today’s world, supply chains must adopt new and intelligent technologies to achieve objectives such as enhancing productivity and performance, competitiveness, and overcoming challenges. The Internet of Things (IoT), as an emerging and transformative technology, is considered one of the most significant technology areas today and has garnered considerable attention across various industries. However, the implementation of IoT at the supply chain (SC) level faces numerous challenges and obstacles, and its acceptance at this level requires specific drivers. To date, no specific classification has been provided for drivers at the SC level, and existing classifications for challenges also need to be reviewed and updated. Given the importance of IoT in SC management, a systematic review at this level is necessary. This article provides a systematic literature review to identify and classify the challenges and drivers of IoT at the SC level. The study reviewed articles published from 2004 to 2023, ultimately identifying and categorizing 92 challenges into 16 categories: financial, standards and government regulations, privacy and security, energy consumption, health issues, hardware and software issues, culture in the SC, lack of knowledge and awareness, poor IT management, coordination in the SC, perception, the Challenge of uncertainty, lack of Plan and Strategy, incompatibility with existing technology, supply Problems, and user acceptance and trust in technology. Additionally, the study identified 4 antecedent drivers (pressures, understanding the benefits, government regulations, government incentives) and 10 consequent drivers (production benefits, improving competitive advantage, inventory management, cost management, improving transparency, efficiency of information flow, development of responsiveness and agility, sustainable development, facilitation of management, and development of cooperation and coordination). Finally, a model for implementing IoT technology in the SC is presented. This model synthesizes the findings from the literature review and offers a practical roadmap for organizations seeking to leverage IoT in their supply chains. By addressing the identified challenges and utilizing the drivers, organizations can effectively integrate IoT technology, thereby enhancing the efficiency, transparency, and overall performance of their SC operations.
Pardis Roozkhosh, Amir Mohammad Fakoor Saghih,
Volume 35, Issue 3 (9-2024)
Abstract
The reliability of each component in a system plays a crucial role, as any malfunction can significantly reduce the system's overall lifespan. Optimizing the arrangement and sequence of heterogeneous components with varying lifespans is essential for enhancing system stability. This paper addresses the redundancy allocation problem (RAP) by determining the optimal number of components in each subsystem, considering their sequence, and optimizing multiple criteria such as reliability, cost uncertainty, and weight. A novel approach is introduced, incorporating a switching mechanism that accommodates both correct and defective switches. To assess reliability benefits, Markov chains are employed, while cost uncertainty is evaluated using the Monte-Carlo method with risk criteria such as percentile and mean-variance. The problem is solved using a modified genetic algorithm, and the proposed method is benchmarked against alternative approaches in similar scenarios. The results demonstrate a significant improvement in the Model Performance Index (MPI), with the best RAPMC solution under a mixed strategy achieving an MPI of 0.98625, indicating superior model efficiency compared to previous studies. Sensitivity analysis reveals that lower percentiles in the cost evaluations correlate with reduced objective function values and mean-variance, confirming the model's robustness in managing redundancy allocation to optimize reliability and control cost uncertainties effectively.
Rahma Fariza, Melinska Ayu Febrianti, Qurtubi Qurtubi, Hari Purnomo,
Volume 35, Issue 4 (12-2024)
Abstract
A business faces challenges in terms of product structuring, design, and space layout; it needs to adapt traditional design management models to scientific developments, like customer shopping behavior data. This article contains a systematic review of planograms and is essential because a similar complete literature review has yet to be found. Therefore, this research is necessary, especially for business actors such as retailers and suppliers. This research aims to analyze studies on shelf-space allocation and store layout and provide advice for future research. This study used the systematic review methodology to incorporate relevant literature, of which 50 articles were later obtained. The review protocol guides a comprehensive and systematic analysis of the articles. This study proposes potential avenues for future research to offer a thorough and precise examination of the impact of shelf-space allocation and store layout. The gaps in previous studies are opportunities to create more complex and comprehensive research results on similar topics. This article added scientific value by presenting an exhaustive literature review, and it can fill the theoretical gap by completing the previous literature review.
Dwi Kurniawan, Aghnia Nazhiifah Ulhaq, Aditya Fadhilah Althofian, Rubby Nur Rachman,
Volume 35, Issue 4 (12-2024)
Abstract
In industrial and commercial settings, inventory systems often involve managing multiple products with diverse demand patterns, making the direct application of the single-item newsvendor model inefficient. To address this complexity, this study proposes an adaptation of the newsvendor model through demand aggregation, where related items are grouped into a product family. By aggregating demand and financial parameters, the traditional newsvendor approach can be extended to multi-item systems, simplifying the inventory management process. This method was tested in two different case studies—a coffee roaster company and a meatball producer—demonstrating its validity and applicability. The aggregated newsvendor model was found to enhance inventory accuracy and efficiency, reducing random error and improving operational performance. This approach offers a valuable extension of the newsvendor model, with potential for broader application across various industries.
Parinaz Esmaeili, Morteza Rasti-Barzoki,
Volume 35, Issue 4 (12-2024)
Abstract
This paper examines the simultaneous decisions regarding advertising, pricing, and service to supply chain coordination involving one manufacturer and one retailer. Demand is impacted by these decisions, with service playing a crucial role in enhancing customer loyalty and boosting sales. The study employs three well-known game theory approaches—Nash, Stackelberg-Retailer, and Cooperative games—to analyze their effects on the supply chain. Optimal strategies for both the manufacturer and the retailer are identified within each approach, and the strategies' results are compared. Results show that the retailer manufacturer, and the entire system achieves higher profits through the Stackelberg-Retailer game compared to the Nash game, while the Cooperative game results in the highest overall profits. Finally, the Nash bargaining model is outlined and analyzed to assess opportunities for sharing profits.
Hana Catur Wahyuni, Rahmania Sri Untari, Rima Azzara, Marco Tieman, Diva Kurnianingtyas,
Volume 35, Issue 4 (12-2024)
Abstract
This research discusses the application of the Failure Mode and Effect Analysis (FMEA) method in designing a blockchain system for mitigating food safety and halal risks in the beef supply chain. The complexity of the meat supply chain involving various parties increasing the risk of contamination and changes in the halal status of the meat. This research aims to identify food safety and halal risks, prioritise the risks, and design blockchain-based mitigation solutions. Blockchain was chosen for its advantages in providing high transparency and accountability, enabling real-time tracking at every stage of the supply chain. The research results show that most of the risks in the meat supply chain fall into the low category, but there are some critical medium risks, especially related to the slaughtering process. The proposed blockchain design includes product traceability features, halal certification, temperature monitoring, and smart contracts to ensure automatic validation of food safety and halal compliance. The implementation of this blockchain is expected to increase consumer trust in meat products, reduce the risk of contamination, and strengthen accountability throughout the meat supply chain.
Nia Budi Puspitasari, Anggit Kurnia Alfiati Devytasari, Aries Susanty ,
Volume 36, Issue 1 (3-2025)
Abstract
Sustainable Development Goals (SDGs) 12 promotes environmentally responsible consumption and production. One of its sub-objectives is to improve sustainable public procurement practices, in line with national policies and priorities. Sustainable Public Procurement (SPP) is a process of public organizations carrying out goods/services procurement activities that consider economic, social, and environmental aspects. This study identifies and evaluates the factors that drive the implementation of SPP in Yogyakarta Provinces, and seeks recommended solutions based on these driving factors. The respondents selected as the object of this study were 30 procurement actors in Yogyakarta Province. In this study, the driving factors for the application of SPP were divided into 6 factors with 22 subfactors. The analysis method used is the RII method. RII is a method for identifying the relative importance of causation of an event based on its likelihood and effect using the Likert Scale. The results showed that 6 of the 22 subfactors that encourage the implementation of SPP are the availability of sustainable products, sustainable goods/services procurement policies and procedures, the availability of sustainable human resources, the availability of sustainable product/service suppliers, organizational values, and the cost of sustainable products/services.
