World Academy of Science, Engineering and Technology

Authors: Atinkut Atinafu Yilma, Eyob Messele Sefene

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Anomaly detection is one of the essential mechanisms to control and reduce production loss, especially in today's smart manufacturing. Quick anomaly detection aids in reducing the cost of production by minimizing the possibility of producing defective products. However, developing an anomaly detection model that can rapidly detect a production change is challenging. This paper proposes Gated Recurrent Unit (GRU) combined with Random Forest (RF) to detect anomalies in the production process in real-time quickly. The GRU is used as a feature detector, and RF as a classifier using the input features from GRU. The model was tested using various synthesis and real-world datasets against benchmark methods. The results show that the proposed GRU-RF outperforms the benchmark methods with the shortest time taken to detect anomalies in the production process. Based on the investigation from the study, this proposed model can eliminate or reduce unnecessary production costs and bring a competitive advantage to manufacturing industries.

Keywords: anomaly detection, multivariate time series data, smart manufacturing, gated recurrent unit network, random forest

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Authors: Eyob Messele Sefene, Atinkut Atinafu Yilma

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The highest strength-to-weight ratio criterion has fascinated increasing curiosity in virtually all areas where weight reduction is indispensable. One of the recent advances in manufacturing to achieve this intention endears friction stir welding (FSW). The process is widely used for joining similar and dissimilar non-ferrous materials. In FSW, the mechanical properties of the weld joints are impelled by property-selected process parameters. This paper presents verdicts of optimum process parameters in attempting to attain enhanced mechanical properties of the weld joint. The experiment was conducted on a 5 mm 6061 aluminum alloy sheet. A butt joint configuration was employed. Process parameters, rotational speed, traverse speed or feed rate, axial force, dwell time, tool material and tool profiles were utilized. Process parameters were also optimized, making use of a mixed L18 orthogonal array and the Grey relation analysis method with larger is better quality characteristics. The mechanical properties of the weld joint are examined through the tensile test, hardness test and liquid penetrant test at ambient temperature. ANOVA was conducted in order to investigate the significant process parameters. This research shows that dwell time, rotational speed, tool shape, and traverse speed have become significant, with a joint efficiency of about 82.58%. Nine confirmatory tests are conducted, and the results indicate that the average values of the grey relational grade fall within the 99% confidence interval. Hence the experiment is proven reliable.

Keywords: friction stir welding, optimization, 6061 AA, Taguchi

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Authors: Monojit Manna, Arpan Adhikary

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In Mobile cloud sensing across the globe, an emerging paradigm is selected by the user to compute sensing tasks. In urban cities current days, Mobile vehicles are adapted to perform the task of data sensing and data collection for universality and mobility. In this work, we focused on the optimality and mobile nodes that can be selected in order to collect the maximum amount of data from urban areas and fulfill the required data in the future period within a couple of minutes. We map out the requirement of the vehicle to configure the maximum data optimization problem and budget. The Application implementation is basically set up to generalize a realistic online platform in which real-time vehicles are moving apparently in a continuous manner. The data center has the authority to select a set of vehicles immediately. A deep learning-based scheme with the help of mobile vehicles (DLMV) will be proposed to collect sensing data from the urban environment. From the future time perspective, this work proposed a deep learning-based offline algorithm to predict mobility. Therefore, we proposed a greedy approach applying an online algorithm step into a subset of vehicles for an NP-complete problem with a limited budget. Real dataset experimental extensive evaluations are conducted for the real mobility dataset in Rome. The result of the experiment not only fulfills the efficiency of our proposed solution but also proves the validity of DLMV and improves the quantity of collecting the sensing data compared with other algorithms.

Keywords: mobile crowdsensing, deep learning, vehicle recruitment, sensing coverage, data collection

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Authors: Pram Abhayawardhana, Ali Reza Nazmi, Hossein Najaf Zadeh

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This study examines the use of additive manufacturing (AM) to develop sustainable and intelligent agricultural formulations that can gradually release fertilisers. AM offers the ability to design customised formulations with precise geometries and controlled release properties while taking into account their mechanical, chemical, and environmental properties. The study specifically investigates the use of an aerogel matrix mixed with a potential fertiliser in agriculture. Highly porous 3D printed aerogel structures were designed to enable the slow release of fertilisers. The performance of the formulated mixture is evaluated against other commonly used materials for slow-release applications. The findings suggest that the 3D printed gel made has great potential for slow-release fertilisers, providing an environmentally friendly solution for agricultural practices. The combination of AM technology and sustainable materials can play a vital role in mitigating the negative environmental impact of traditional fertilisers, as well as improving the efficiency and sustainability of agricultural production.

Keywords: 3D printing, hydrogel, aerogel, fertiliser, agriculture

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Authors: Edemealem Desalegn Kingawa, Kafte Tasew Timkete, Mekashaw Girmaw Abebe, Terefe Feyisa, Abiyot Bitew Mihretie, Senait Teklemarkos Haile

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Currently, hate speech is a growing challenge for society, individuals, policymakers, and researchers, as social media platforms make it easy to anonymously create and grow online friends and followers and provide an online forum for debate about specific issues of community life, culture, politics, and others. Despite this, research on identifying and detecting hate speech is not satisfactory performance, and this is why future research on this issue is constantly called for. This paper provides a systematic review of the literature in this field, with a focus on approaches like word embedding techniques, machine learning, deep learning technologies, hate speech terminology, and other state-of-the-art technologies with challenges. In this paper, we have made a systematic review of the last six years of literature from Research Gate and Google Scholar. Furthermore, limitations, along with algorithm selection and use challenges, data collection, and cleaning challenges, and future research directions, are discussed in detail.

Keywords: Amharic hate speech, deep learning approach, hate speech detection review, Afaan Oromo hate speech detection

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Authors: Liubov Magerramova, Mikhail Petrov, Vladimir Isakov, Liana Shcherbinina, Suren Gukasyan, Daniil Povalyukhin, Olga Klimova-Korsmik, Darya Volosevich

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Aircraft engines are developing along the path of increasing resource, strength, reliability, and safety. The building of gas turbine engine body parts is a complex design and technological task. Particularly complex in the design and manufacturing are the casings of the input stages of helicopter gearboxes and central drives of aircraft engines. Traditional technologies, such as precision casting or isothermal forging, are characterized by significant limitations in parts production. For parts like housing, additive technologies guarantee spatial freedom and limitless or flexible design. This article presents the results of computational and experimental studies. These investigations justify the applicability of additive technologies (AT) to reduce the weight of aircraft housing gearbox parts by up to 32%. This is possible due to geometrical optimization compared to the classical, less flexible manufacturing methods and as-casted aircraft parts with over-insured values of safety factors. Using an example of the body of the input stage of an aircraft gearbox, visualization of the layer-by-layer manufacturing of a part based on thermal deformation was demonstrated.

Keywords: additive technologies, gas turbine engines, topological optimization, synthesis process

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Authors: Henrique Fernandes, Sofia Catalucci, Richard Leach, Kapil Sugand

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Background: Holograms are 3D images formed by the interference of light beams from a laser or other coherent light source. Pepper’s ghost is a form of hologram conceptualised in the 18th century. This Holographic visualisation with metrology measuring techniques by displaying measurements taken in real-time in holographic form can assist in research and education. New structural designs such as the Plexiglass Stand and the Hologram Box can optimise the holographic experience. Method: The equipment used included: (i) Zeiss’s ATOS Core 300 optical coordinate measuring instrument that scanned real-world objects; (ii) Cloud Compare, open-source software used for point cloud processing; and (iii) Hologram Box, designed and manufactured during this research to provide the blackout environment needed to display 3D point clouds in real-time measurements in holographic format, in addition to a portability aspect to holograms. The equipment was tailored to realise the goal of displaying measurements in an innovative technique and to improve on conventional methods. Three test scans were completed before doing a holographic conversion. Results: The outcome was a precise recreation of the original object in the holographic form presented with dense point clouds and surface density features in a colour map. Conclusion: This work establishes a way to visualise data in a point cloud system. To our understanding, this is a work that has never been attempted. This achievement provides an advancement in holographic visualisation. The Hologram Box could be used as a feedback tool for measurement quality control and verification in future smart factories.

Keywords: holography, 3D scans, hologram box, metrology, point cloud

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Authors: Chieh Lee

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Today, supply chain managers face extensive disruptions in raw material pricing, transportation block, and quality issue due to product complexity. While digitalization might help managers to mitigate the disruption risk and increase supply chain resilience by sharing information between sellers and buyers through the supply chain, entities are reluctant to build such a system. The main reason is it is not clear what information should be shared and who has access to the stored information. In this research, we propose a smart contract built by blockchain technology. This contract helps both buyer and seller to identify the type of information, the access to the information, and how to trace the information. This contract helps managers control their orders through the supply chain and address any disruption they see fit. Furthermore, with the same smart contract, the supplier can track the production process of an order and increase production efficiency by eliminating waste.

Keywords: blockchain, production process, smart contract, supply chain resilience

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Authors: Mayank Sharma, Anubhaw Kumar, Siddharth Desai, Ankit Tomar

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With the advent of cost-effective hardware and communication technologies, the scope of digitalising operations within a supply chain has tremendously increased. This has provided the opportunity to create digital twins of entire supply chains through the use of Internet-of-Things (IoT) and communication technologies. Adverse events like the COVID-19 pandemic and unpredictable geo-political situations have further warranted the importance of digitalization and remote operability of day-to-day operations at critical nodes. Globalisation, rising consumerism & e-commerce has exponentially increased the complexities of existing supply chains. We discuss here a scalable, future-ready and inclusive framework for creating digital twins developed along with the industry leaders from Cisco, Bosch, Accenture, Intel, Deloitte & IBM. We have proposed field-tested key technologies and frameworks required for creating digital twins. We also present case studies of real-life stable deployments done by us in the supply chains of a few marquee industry leaders.

Keywords: internet-of-things, digital twins, smart factory, industry 4.0, smart manufacturing

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Authors: Masoud Shahmanzari

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The aim of this paper is to present a Variable Neighborhood Search (VNS) with Tabu Search (TS) conditions for the Roaming Salesman Problem (RSP). The RSP is a special case of the well-known traveling salesman problem (TSP) where a set of cities with time-dependent rewards and a set of campaign days are given. Each city can be visited on any day and a subset of cities can be visited multiple times. The goal is to determine an optimal campaign schedule consist of daily open/closed tours that visit some cities and maximizes the total net benefit while respecting daily maximum tour duration constraints and the necessity to return campaign base frequently. This problem arises in several real-life applications and particularly in election logistics where depots are not fixed. We formulate the problem as a mixed integer linear programming (MILP), in which we capture as many real-world aspects of the RSP as possible. We also present a hybrid metaheuristic algorithm based on a VNS with TS conditions. The initial feasible solution is constructed via a new matheuristc approach based on the decomposition of the original problem. Next, this solution is improved in terms of the collected rewards using the proposed local search procedure. We consider a set of 81 cities in Turkey and a campaign of 30 days as our largest instance. Computational results on real-world instances show that the developed algorithm could find near-optimal solutions effectively.

Keywords: optimization, routing, election logistics, heuristics

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Authors: Mirza Ahsan Baig, Paul Evans

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Due to the high demand for automobiles, manufacturers have to run their production lines non-stop for long periods. At such a scale, unplanned downtime could cost up to $50 billion annually. Improper training of new hires could lead to safety issues causing unplanned downtimes. The project developed a virtual reality simulation that could train personnel for key operations on an automobile manufacturing floor, reducing the risk of unplanned downtime while eliminating any disruption (due to training) on the assembly line. An automation firm sponsored it to explore the possibilities the likes of Jaguar and BMW are yet to achieve! The project was inspired by Bentley, the only company that succeeded in simulation training scenarios within virtual space. The project aims to inspire other significant firms to do the same. It was increasing employee safety, eliminating downtimes, and improving efficiency. The developed prototype uncovered various limitations within existing simulation providers and was able to simulate state-of-the-art training scenarios. It also explored the possibility of a multiuser interface and resolved complex issues such as lack of movement space within the training area.

Keywords: virtual reality, scenario training, limited movement, multiuser

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Authors: Michael A. Sprayberry, Vincent C. Paquit

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Process parameter optimization in metal powder bed electron beam melting (MPBEBM) is crucial to ensure the technology's repeatability, control, and industry-continued adoption. Despite continued efforts to address the challenges via the traditional design of experiments and process mapping techniques, there needs to be more successful in an on-the-fly optimization framework that can be adapted to MPBEBM systems. Additionally, data-intensive physics-based modeling and simulation methods are difficult to support by a metal AM alloy or system due to cost restrictions. To mitigate the challenge of resource-intensive experiments and models, this paper introduces a Multi-Objective Reinforcement Learning (MORL) methodology defined as an optimization problem for MPBEBM. An off-policy MORL framework based on policy gradient is proposed to discover optimal sets of beam power (P) – beam velocity (v) combinations to maintain a steady-state melt pool depth and phase transformation. For this, an experimentally validated Eagar-Tsai melt pool model is used to simulate the MPBEBM environment, where the beam acts as the agent across the P – v space to maximize returns for the uncertain powder bed environment producing a melt pool and phase transformation closer to the optimum. The culmination of the training process yields a set of process parameters {power, speed, hatch spacing, layer depth, and preheat} where the state (P,v) with the highest returns corresponds to a refined process parameter mapping. The resultant objects and mapping of returns to the P-v space show convergence with experimental observations. The framework, therefore, provides a model-free multi-objective approach to discovery without the need for trial-and-error experiments.

Keywords: additive manufacturing, metal powder bed fusion, reinforcement learning, process parameter optimization

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Authors: Nwauzoma Ohale Rowland, Bright Ugochukwu Umunna

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The world has been referred to as a global village for decades, adapting various technological and digital innovations to progress along the lines of development. Different continents have fully automated processes and procedures in the various sectors of their economies. This paper attempts to ascertain why the West African sub-continent while displaying a slow progression, has also joined the race toward having a fully automated process, albeit only in certain areas of its economy. Different reasons for this have been posited and will be discussed in this work. These reasons include high illiteracy rates and poor acceptance of new technologies. Studies were carried out that involved interactions with different business sectors and also a secondary-level investigation of experiments to ascertain the impact of automation in supply chain management on the West African market. Our reports show remarkable growth in businesses and sectors that have automated their processes. While this is the case, other results have also confirmed as due to the high illiteracy rates; the labour force has also been affected.

Keywords: Africa, automation, business, innovation, supply chain management, technology

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Authors: Vangelis Papadimitropoulos

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This paper is part of the research program “Techno-Social Innovation in the Collaborative Economy”, funded by the Hellenic Foundation for Research and Innovation (H.F.R.I.) for the years 2022-2024. The paper showcases the Open Food Network (OFN) as an open-sourced digital platform supporting short food supply chains in local agricultural production and consumption. The paper outlines the research hypothesis, the theoretical framework, and the methodology of research as well as the findings and conclusions. Research hypothesis: The model of open cooperativism as a vehicle for systemic change in the agricultural sector. Theoretical framework: The research reviews the OFN as an illustrative case study of the three-zoned model of open cooperativism. The OFN is considered a paradigmatic case of the model of open cooperativism inasmuch as it produces commons, it consists of multiple stakeholders including ethical market entities, and it is variously supported by local authorities across the globe, the latter prefiguring the mini role of a partner state. Methodology: Research employs Ernesto Laclau and Chantal Mouffe’s discourse analysis -elements, floating signifiers, nodal points, discourses, logics of equivalence and difference- to analyse the breadth of empirical data gathered through literature review, digital ethnography, a survey, and in-depth interviews with core OFN members. Discourse analysis classifies OFN floating signifiers, nodal points, and discourses into four themes: value proposition, governance, economic policy, and legal policy. Findings: OFN floating signifiers align around the following nodal points and discourses: “digital commons”, “short food supply chains”, “sustainability”, “local”, “the elimination of intermediaries” and “systemic change”. The current research identifies a lack of common ground of what the discourse of “systemic change” signifies on the premises of the OFN’s value proposition. The lack of a common mission may be detrimental to the formation of a common strategy that would be perhaps deemed necessary to bring about systemic change in agriculture. Conclusions: Drawing on Laclau and Mouffe’s discourse theory of hegemony, research introduces a chain of equivalence by aligning discourses such as “agro-ecology”, “commons-based peer production”, “partner state” and “ethical market entities” under the model of open cooperativism, juxtaposed against the current hegemony of neoliberalism, which articulates discourses such as “market fundamentalism”, “privatization”, “green growth” and “the capitalist state” to promote corporatism and entrepreneurship. Research makes the case that for OFN to further agroecology and challenge the current hegemony of industrial agriculture, it is vital that it opens up its supply chains into equivalent sectors of the economy, civil society, and politics to form a chain of equivalence linking together ethical market entities, the commons and a partner state around the model of open cooperativism.

Keywords: sustainability, the digital commons, open cooperativism, innovation

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Authors: Ran Etgar

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The process of rounding off measurements in continuous variables is commonly encountered. Although it usually has minor effects, sometimes it can lead to poor outcomes in statistical process control using X̄ chart. The traditional control limits can cause incorrect conclusions if applied carelessly. This study looks into the limitations of classical control limits, particularly the impact of asymmetry. An approach to determining the distribution function of the measured parameter ȳ is presented, resulting in a more precise method to establish the upper and lower control limits. The proposed method, while slightly more complex than Shewhart's original idea, is still user-friendly and accurate and only requires the use of two straightforward tables.

Keywords: SPC, round-off data, control limit, rounding error

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Authors: Panagiotis I. Mallios, Vassilis S. Moustakis

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The research reported herein presents a conceptual model that explores the relationship between social media factors and entrepreneurial intention, with a focus on the Greek startup ecosystem. The significance of the study is that social media have gained importance in explaining the entrepreneurial process, and through them, nascent and potential entrepreneurs seem to get inspired and motivated to initiate their businesses. The research methodology employed in this study included a qualitative research approach, utilizing in-depth interviews with a sample of 15 startup entrepreneurs providing valuable retrospective information. The data collected were analyzed using the content analysis method. The major findings of the study are that social media factors such as usefulness, influence, and credibility have a significant impact on entrepreneurial intention. We also found that social media can be a powerful tool for entrepreneurs to access resources, knowledge and networks that can help them in their venture creation. Overall, this research contributes to the entrepreneurship literature by uncovering the relationship between social media factors and entrepreneurial intention and has implications for entrepreneurial education, policymakers, and official partners, highlighting the potential of social media to enhance the startup ecosystem.

Keywords: entrepreneurial intention, social media, start up ecosystem, entrepreneurship

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Authors: Racha Khairallah, Lamia Ben Hamida

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Our paper attempts to examine how Swiss manufacturing firms manage to learn from patent citations to improve their innovation performance. We argue that the assessment of these effects needs a detailed analysis of spillovers according to the source of knowledge with respect to formal and informal patent citations made in European and internal search, the horizontal and vertical mechanisms by which knowledge spillovers take place, and the technological characteristics of innovative firms that able them to absorb external knowledge and integrate it in their existing innovation process. We use OECD data and find evidence that knowledge spillovers occur only from horizontal and backward linkages. The importance of these effects depends on the type of citation, in which the references to non-patent literature (informal citations made in European and international searches) have a greater impact. In addition, only firms with high technological capacities benefit from knowledge spillovers from formal and informal citations. Low-technology firms fail to catch up and efficiently learn external knowledge from patent citations.

Keywords: innovation performance, patent citation, absorptive capacity, knowledge spillover mechanisms

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Authors: Mohit Taneja, Ravi Kiran, S. C. Bose

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Entrepreneurs’ role in achieving Sustainable development goals is crucial as the growth potential of any region depends upon the number and the success rate of entrepreneurial firms. This paper is an effort to examine the relationship between Sustainable growth (SG) with Entrepreneurial attitude (EA) and Entrepreneurial intention (EI) in the context of the Indian economy. The mediation effect of EI between EA and SG has been considered. Partial least square (PLS) –Structural Equation Model (SEM) software was used to design the framework. Students enrolled in entrepreneurship courses of higher educational institutes (HEI) of Punjab, Haryana, and the National Capital Region NCR were contacted for data collection. The National Institutional Ranking Framework (NIRF) framework was used in selecting HEIs and data collected from 589 students was considered for analysis. McGee’s multi-dimensional scale for measuring ESE and the scale of Linan & Chen for measuring EI & ES (SG) was used. Results highlight that EA has a strong impact on EI (p≤ 0.001) and EI has a positive and strong relationship with SG (ES) as β value for the same is 0.683 (p≤ 0.001). The current study also reflects the mediating effect of EI among EA and ES, as the results show that the combined β value of both EA and EI (i.e.0.684*0.683= 0.467) is more than the direct influence of EA on ES (β=0.265). EA, with the mediating effect of EI can enhance the opportunity for achieving SG, which suggests that in order to increase the venture success rate and to attain SG, emphasis should be given to EI along with EA. The study has been investigated in three regions of India. Future studies can be extended to other South Asian countries for generalization.

Keywords: entrepreneurship, sustainable growth, entrepreneurship intention, entrepreneurship attitude

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Authors: Alexandre Bédard, Caroline Coulombe, Jonathan Harvey

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Envisioning process (EP) in medium enterprises is treated equally in very small enterprises. Building on the concept of social construction, this study aims to explore how envisioning is constructed in a medium enterprise in which stakeholders are involved and how it is influenced. We use a unique case method based on qualitative data collected through 11 interviews representing various members of the organization. Through the discussion of the findings, we were able to confirm the social construction of the EP and to identify three main stakeholders responsible for the construction of the vision, mainly political and social powers, actors of the organization, and financial providers. Moreover, EP is influenced by external factors; in this case, the history of the organization and the value and importance of the art and the culture for Cambodians.

Keywords: envisioning process, social constructivism, medium enterprise, legitimacy

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Authors: Birgit A. A. Solem, Kristin Bentsen

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Scholarly attention in entrepreneurship is currently directed towards understanding entrepreneurial venture creation as a process -the journey of new economic activities from nonexistence to existence often studied through flow- or network models. To complement existing research on entrepreneurial venture creation with more interactivity-based research of organized activities, this study examines two pop-up stores as anchor events involving on-site activities of fifteen participating entrepreneurs launching their new ventures. The pop-up stores were arranged in two middle-sized Norwegian cities and contained different brand stores that brought together actors of sub-networks and communities executing venture creation activities. The pop-up stores became on-site arenas for the entrepreneurs to create, maintain, and rejuvenate their networks, at the same time as becoming venues for temporal coordination of activities involving existing and potential customers in their venture creation. In this work, we apply a conceptual framework based on frequently addressed dilemmas within entrepreneurship theory (discovery/creation, causation/effectuation) to further shed light on the broad aspect of on-site anchor event activities and their venture creation outcomes. The dilemma-based concepts are applied as an analytic toolkit to pursue answers regarding the nature of anchor event activities typically found within entrepreneurial venture creation and how these anchor event activities affect entrepreneurial venture creation outcomes. Our study combines researcher participation with 200 hours of observation and twenty in-depth interviews. Data analysis followed established guidelines for hermeneutic analysis and was intimately intertwined with ongoing data collection. Data was coded and categorized in NVivo 12 software, and iterated several times as patterns were steadily developing. Our findings suggest that core anchor event activities typically found within entrepreneurial venture creation are; a concept- and product experimentation with visitors, arrangements to socialize (evening specials, auctions, and exhibitions), store-in-store concepts, arranged meeting places for peers and close connection with municipality and property owners. Further, this work points to four main entrepreneurial venture creation outcomes derived from the core anchor event activities; (1) venture attention, (2) venture idea-realization, (3) venture collaboration, and (4) venture extension. Our findings show that, depending on which anchor event activities are applied, the outcomes vary. Theoretically, this study offers two main implications. First, anchor event activities are both discovered and created, following the logic of causation, at the same time as being experimental, based on “learning by doing” principles of effectuation during the execution. Second, our research enriches prior studies on venture creation as a process. In this work, entrepreneurial venture creation activities and outcomes are understood through pop-up stores as on-site anchor event arenas, particularly suitable for interactivity-based research requested by the entrepreneurship field. This study also reveals important managerial implications, such as that entrepreneurs should allow themselves to find creative physical venture creation arenas (e.g., pop-up stores, showrooms), as well as collaborate with partners when discovering and creating concepts and activities based on new ideas. In this way, they allow themselves to both strategically plan for- and continually experiment with their venture.

Keywords: anchor event, interactivity-based research, pop-up store, entrepreneurial venture creation

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Authors: Korpapa Srisamai, Pawee Siriruk

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The purpose of this study is to forecast product demands and develop appropriate and adequate procurement plans to meet customer needs and reduce costs. When the product exceeds customer demands or does not move, it requires the company to support insufficient storage spaces. Moreover, some items, when stored for a long period of time, cause deterioration to dead stock. A case study of the wholesale company of electronic equipment and components, which has uncertain customer demands, is considered. The actual purchasing orders of customers are not equal to the forecast provided by the customers. In some cases, customers have higher product demands, resulting in the product being insufficient to meet the customer's needs. However, some customers have lower demands for products than estimates, causing insufficient storage spaces and dead stock. This study aims to reduce the loss of sales opportunities and the number of remaining goods in the warehouse, citing 30 product samples of the company's most popular products. The data were collected during the duration of the study from January to October 2022. The methods used to forecast are simple moving averages, weighted moving average, and exponential smoothing methods. The economic ordering quantity and reorder point are used to calculate to meet customer needs and track results. The research results are very beneficial to the company. The company can reduce the loss of sales opportunities by 20% so that the company has enough products to meet customer needs and can reduce unused products by up to 10% dead stock. This enables the company to order products more accurately, increasing profits and storage space.

Keywords: demand forecast, reorder point, lost sale, dead stock

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Authors: Ercan Karadogan, Fatih Usta

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Auxetic materials have a negative Poisson’s ratio (NPR), which is not often found in nature. They are metamaterials that have potential applications in many engineering fields. Mechanical metamaterials are synthetically designed structures with unusual mechanical properties. These mechanical properties are dependent on the properties of the matrix structure. They have the following special characteristics, i.e., improved shear modulus, increased energy absorption, and intensive fracture toughness. Non-auxetic materials compress transversely when they are stretched. The system naturally is inclined to keep its density constant. The transversal compression increases the density to balance the loss in the longitudinal direction. This study proposes to improve the crushing performance of hybrid auxetic materials. The re-entrant honeycomb structure has been combined with a star honeycomb, an S-shaped unit cell, a double arrowhead, and a structurally hexagonal re-entrant honeycomb by 9 X 9 cells, i.e., the number of cells is 9 in the lateral direction and 9 in the vertical direction. The Finite Element (FE) and experimental methods have been used to determine the compression behavior of the developed hybrid auxetic structures. The FE models have been developed by using Abaqus software. The specimens made of polymer plastic materials have been 3D printed and subjected to compression loading. The results are compared in terms of specific energy absorption and strength. This paper describes the quasi-static crushing behavior of two types of hybrid lattice structures (auxetic + auxetic and auxetic + non-auxetic). The results show that the developed hybrid structures can be useful to control collapse mechanisms and present larger energy absorption compared to conventional re-entrant auxetic structures.

Keywords: auxetic materials, compressive behavior, metamaterials, negative Poisson’s ratio

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Authors: Anek Apipatkul, Paphakorn Pitayachaval

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Preventive maintenance is a standardized procedure to control and prevent risky problems affecting production in order to increase work efficiency. Machine monitoring also routinely works to collect data for a scheduling maintenance period. This paper is to present the application of machine monitoring by using the internet of things (IOTs) and a lean technique in order to manage with complex maintenance tasks of an automated plastic granule packing machine. To organize the preventive maintenance, there are several processes that the machine monitoring was applied, starting with defining a clear scope of the machine, establishing standards in maintenance work, applying a just-in-time (JIT) technique for timely delivery in the maintenance work, solving problems on the floor, and also improving the inspection process. The result has shown that wasted time was reduced, and machines have been operated as scheduled. Furthermore, the efficiency of the scheduled maintenance period was increased by 95%.

Keywords: internet of things, preventive maintenance, machine monitoring, lean technique

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Authors: Jirayut Phetchuen, Jongkol Srithorn

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The study examines the unloading and repacking process of Read With Me Group Company Limited. The research aims to improve the old work process and build a new efficient process with the Lean Technique and new machines for faster delivery without increasing the number of employees. Currently, two employees work based on five days on and off. However, workplace injuries have delayed the delivery time, especially the delivery to the neighboring countries. After the process improvement, the working space increased by 25%, the Process Lead Time decreased by 40%, the work efficiency increased by 175.82%, and the work injuries rate was reduced to zero.

Keywords: lean technique, plant layout design, U-shaped disassembly line, value stream mapping

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Authors: Jeerasak Wisatphan, Nara Samattapapong

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This study's goals were to enhance nitroglycerin manufacturing efficiency through simulation, recover nitroglycerin from the storage facility, and enhance nitroglycerine recovery and purge systems. It was found that the problem was nitroglycerin reflux. Therefore, the researcher created three alternatives to solve the problem. The system of Nitroglycerine Recovery and Purge was then simulated using the FlexSim program, and each alternative was tested. The results demonstrate that the alternative system-led Nitroglycerine Recovery and Nitroglycerine Purge System collaborate to produce Nitroglycerine, which is more efficient than other alternatives and can reduce production time. It can also improve the recovery of nitroglycerin. It also serves as a guideline for developing a real-world system and modeling it for training staff without wasting raw chemical materials or fuel energy.

Keywords: efficiency increase, nitroglycerine recovery and purge system, production improvement, simulation

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Authors: Abdulaziz Alageel, Martino Luis, Shuya Zhong

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The main focus of this research study is on the challenges faced in decision-making in a supply chain network regarding the facility location while considering carbon emissions. The study aims (i) to locate facilities (i.e., distribution centeres) in a continuous space considering limitations of capacity and the costs associated with opening and (ii) to reduce the cost of carbon emissions by selecting the mode of transportation. The problem is formulated as mixed-integer linear programming. This study hybridised a greedy randomised adaptive search (GRASP) and variable neighborhood search (VNS) to deal with the problem. Well-known datasets from the literature (Brimberg et al. 2001) are used and adapted in order to assess the performance of the proposed method. The proposed hybrid method produces encouraging results based on computational analysis. The study also highlights some research avenues for future recommendations.

Keywords: supply chain, facility location, weber problem, sustainability

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Authors: Inyene Nathaniel Nkanta

Abstract:

The present economic situation in Nigeria, with an increase in inflation rate due to the fall of crude oil prices and post covid-19 crisis, has increased the level of poverty and suffering in Nigeria, particularly the women. Against that backdrop, this research project is initiated to explore ways to empower women through entrepreneurship education and training to ameliorate the poverty level amongst women in Nigeria. A qualitative approach to data collection will be applied in this study and to test the assertions of this research project empirically, this research adopts a case study research method as this will enable me to obtain and probe ways women can be empowered through semi-structured interviews and focus groups. The result of this research project will provide an original perspective on human capital development, most importantly, the need for entrepreneurial education and entrepreneurial literature and practice.

Keywords: women, Nigeria, entrepreneurship education, Economic development, human capital

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Authors: Tony Bediako Arthur, Nejat Rahmanian, Nana Gyan Sekyi

Abstract:

The possibility of producing seeded granules from fine and course powders is a major challenge as the control parameters that affect its producibility is still under investigation. The seeded granulation is a novel form of producing granules where the granule is made up of larger particles at the core, which are surrounded by fine particles. The possibility of managing granulation through course particle feed rate control makes seeded granulation in continuous granulation useful in terms of process control. Twin screw granulation is now a major process of choice for the wet continuous granulation process in the industry. It is, therefore, imperative to investigate the process control parameters that influence the formation of seeded granules in twin screw granulation. In this paper, the effect of the twin screws rotating speed on the production of seeded granules has been examined. Pictorial and quantitative analysis indicates a high number of seeded granules forming at low screw rotating speeds. It is also instructive to say that higher tensile stress occurs at the kneading section of the screws; thus, higher rotating speed courses the fines for breaking off from the seed particle.

Keywords: DEM, twin-screw, Seeded granules, Simulation

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Authors: Nuno Biga

Abstract:

Artificial Intelligence (AI) allows machines to interpret information and learn from context analysis, giving them the ability to make predictions adjusted to each specific situation. In addition to learning by performing deterministic and probabilistic calculations, the 'artificial brain' also learns through information and data provided by those who train it, namely its users. The "Assisted-BIGAMES" version of the Accident & Emergency (A&E) simulator introduces the concept of a "Virtual Assistant" (VA) that provides users with useful suggestions, namely to pursue the following operations: a) to relocate workstations in order to shorten travelled distances and minimize the stress of those involved; b) to identify in real time the bottleneck(s) in the operations system so that it is possible to quickly act upon them; c) to identify resources that should be polyvalent so that the system can be more efficient; d) to identify in which specific processes it may be advantageous to establish partnership with other teams; and e) to assess possible solutions based on the suggested KPIs allowing action monitoring to guide the (re)definition of future strategies. This paper is built on the BIGAMES© simulator and presents the conceptual AI model developed in a pilot project. Each Virtual Assisted BIGAME is a management simulator developed by the author that guides operational and strategic decision making, providing users with useful information in the form of management recommendations that make it possible to predict the actual outcome of different alternative management strategic actions. The pilot project developed incorporates results from 12 editions of the BIGAME A&E that took place between 2017 and 2022 at AESE Business School, based on the compilation of data that allows establishing causal relationships between decisions taken and results obtained. The systemic analysis and interpretation of this information is materialised in the Assisted-BIGAMES through a computer application called "BIGAMES Virtual Assistant" that players can use during the Game. Each participant in the Virtual Assisted-BIGAMES permanently asks himself about the decisions he should make during the game in order to win the competition. To this end, the role of the VA of each team consists in guiding the players to be more effective in their decision making through presenting recommendations based on AI methods. It is important to note that the VA's suggestions for action can be accepted or rejected by the managers of each team, and as the participants gain a better understanding of the game, they will more easily dispense with the VA's recommendations and rely more on their own experience, capability, and knowledge to support their own decisions. Preliminary results show that the introduction of the VA provides a faster learning of the decision-making process. The facilitator (Serious Game Controller) is responsible for supporting the players with further analysis and the recommended action may be (or not) aligned with the previous recommendations of the VA. All the information should be jointly analysed and assessed by each player, who are expected to add “Emotional Intelligence”, a component absent from the machine learning process.

Keywords: artificial intelligence (AI), gamification, key performance indicators (KPI), machine learning, management simulators, serious games, virtual assistant

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Authors: Mari Chaikovskaia, Jean-Philippe Gayon, Alain Quilliot

Abstract:

We consider a fleet of elementary robots that can be connected in different ways to transport loads of different types. For instance, a single robot can transport a small load, and the association of two robots can either transport a large load or two small loads. We seek to determine the optimal number of robots to transport a set of loads in a given time interval, with or without reconfiguration. We show that the problem with reconfiguration is strongly NP-hard by a reduction to the bin-packing problem. Then, we study a special case with unit capacities and derive simple formulas for the minimum number of robots, up to 3 types of loads. For this special case, we compare the minimum number of robots with or without reconfiguration and show that the gain is limited in absolute value but may be significant for small fleets.

Keywords: fleet sizing, reconfigurability, robots, transportation

Procedia PDF Downloads 51