Hasil untuk "Production management. Operations management"

Ali Ebrahimi Kordlar, Hossein Safari, Mohammad Rozbeh

Objective: The construction industry has been increasingly criticized for its poor sustainability performance in recent decades, creating a chance for the sector to play a key role in global sustainability efforts. Rapid technological advancements and increasing construction project complexities have driven the need for flexible, sustainability-focused project management frameworks. This study introduces a fuzzy inference system designed to evaluate construction project sustainability, built on insights from extensive literature and expert input.Methods: To design the proposed model, the system inputs—criteria for evaluating the sustainability level of construction projects at various layers—were first identified. Next, the necessary if-then rules were developed based on expert opinions. The system output was determined in alignment with the research’s final objective. By offering a comprehensive assessment of construction project sustainability, the model enables organizations to identify their strengths and weaknesses, assess their current position, and make informed decisions to enhance their sustainable performance. Results: The output of the research includes a detailed analysis of the sustainability performance of construction projects. The designed model, along with its measurement tools, provides an opportunity for leaders and managers in the construction industry who are concerned about sustainability to gradually enhance their sustainability status and advance the sustainability level of projects. This model consists of three subsystems named the Direction, Execution, and Results subsystems. The aforementioned subsystems are the result of a literature review and are considered inputs to the final level of the model.Conclusion: The designed model serves as a tool to identify and implement improvement methods and potential areas for project advancement from a sustainability perspective. By utilizing this model, the quality of project execution in line with sustainability indicators, while addressing all three dimensions—economic, social, and environmental—improves continuously and proportionately.

hamed mansouri, Valiallah Yousefabadi, Hamze Hamze et al.

IntroductionSugar beet is the main source of sugar production in Iran, accounting for approximately 60% of the country's sugar production comes. The rest comes from sugar cane (Ribeiro et al., 2016). Hamedan province, with a cultivated area of ​​about 7 percent of the total cultivated area of ​​the country, is one of the most important provinces in terms of sugar beet cultivation and sugar production. Nahavand and Asadabad regions also have the largest cultivated area of ​​sugar beet in Hamedan Province and are considered the most important sugar beet cultivation areas in the province. Seed is a crucial agricultural input. It provides farmers with significant added value by improving the efficiency of other inputs, such as water, fertilizer, pesticides, and machinery. Maximizing yield is impossible without using the right seeds, even with significant energy investment (Sadeghzadeh Hemayati et al., 2024). The primary aim of conducting variety comparison experiments is to select and introduce suitable varieties to farmers in each region, this study was conducted to compare sugar beet varieties and introduce the best variety in the Nahavand and Asadabad regions of Hamedan province. Materials and MethodsTo evaluate the root yield and quality characteristics of some breeding commercial sugar beet varieties in Hamedan province, an experiment was conducted in two regions: Asadabad-Vanderabad Village and Nahavand-Gyan Village, in 2023, under farm conditions. The study included five Iranian commercial cultivars—Sina, Nika, Shokofa, Asia, and Dena—as well as a foreign cultivar, Urslina, which served as the control. Planting took place in Nahavand on March 10, 2022, and in Asadabad on April 15, 2023. A total of 30 planting lines, each measuring 300 meters in length and spaced 50 centimeters apart, were allocated for each cultivar. Each cultivar was planted in an area of 4,500 square meters. The farmer carried out all land preparation and farm management operations in accordance with local customs. At the end of the growing season, four samples (as four replicates) of each variety were randomly harvested and weighed, and root yield was obtained. The harvested roots were washed, pulped, and sent to the Sugar Technology Laboratory at the Sugar Beet Seed Institute for quality characteristic measurement. Cluster analysis and factor analysis were performed using R v.4.2.2 software. Results and DiscussionBecause of the significant interaction effect between cultivar and environment, which indicated independent responses of cultivars in the two different locations, all data analyses were performed separately for each site. In Nahavand, the highest sugar content and white sugar content were observed with 18.24 and 15.87 percent, respectively, and the highest sugar yield and white sugar yield were observed with 19.29 and 16.79 ton.ha-1, respectively, in the foreign cultivar Urslina. Among the Iranian cultivars, the two cultivars Dena and Asia had the highest yield. In Asadabad, results showed that the foreign cultivar Urslina had the highest values ​​among the studied cultivars in terms of sugar content (18.29%), sugar yield (19.80 ton.ha-1), white sugar content (16.17%), white sugar yield (17.51 ​​ ton.ha-1), and sugar extraction coefficient (88.4%). Cluster analysis results indicated that the cultivars were grouped into three clusters in Nahavand and four clusters in Asadabad. Based on the results of the cluster analysis conducted in the Nahavand environment, two clusters were introduced as superior clusters. The first cluster included the Urslina variety, while the second cluster comprised the Dena, Asia, and Shokofa varieties. In the Asadabad environment, the first cluster also included the Urslina variety, and the fourth cluster contained the Nika variety, both of which were recognized as superior clusters. Factor analysis identified two significant factors, explaining 95.57% of the variation in Nahavand and 95.94% in Asadabad. ConclusionOverall, the Urslina cultivar emerged as the superior cultivar in both environments. Among the Iranian cultivars, the Dena and Asia cultivars were recommended for the Nahavand environment, while the Nika cultivar was suggested for the Asadabad environment due to their better quantitative and qualitative characteristics.

J.B. Collins, Rachel Choo, Amanda O. Shaver et al.

Resistance to benzimidazole (BZ) anthelmintics is a widespread problem in parasitic nematodes that infect production animals such as sheep and goats, and an emerging issue in ascarid parasites of poultry. Ascarid parasites are highly prevalent across commercial poultry species and are associated with significant production losses. The BZ drug fenbendazole (FBZ) is the only approved treatment for ascarid infections in poultry, and previously, FBZ resistance has been identified in Ascaridia dissimilis, the large ascarid of turkeys, and Heterakis gallinarum, the cecal ascarid. Here, we have conducted a small-scale survey of the prevalence of resistance by screening FBZ efficacy against thirteen isolates of Ascaridia galli and eight isolates of H. gallinarum. Four weeks after initial infection, treated animals received FBZ (SafeGuard Aquasol) for five days, per the manufacturer’s directions. One week post-treatment, animals were necropsied for parasite quantification to determine treatment efficacy. A single isolate of A. galli and all of the isolates of H. gallinarum were found to be resistant. This finding demonstrates that resistance has emerged in all three major species of poultry ascarid and is potentially common in H. gallinarum, highlighting that resistance is a major problem to be considered. Poultry production lacks other approved options for mitigating ascarid infections, and as resistance increases in prevalence, production loss associated with infections will continue to increase, impacting the economics of the industry. The current study uses sampling and screening of parasites. Methods for larger-scale screenings are necessary to understand the full scope of resistance within poultry production, necessitating partnerships with production operations and country-wide sampling efforts. However, from our survey, it is clear that stakeholders should be aware of the concerns associated with resistance, and that the industry should consider the development of new treatments and management strategies for parasite control.

Luis Rojas, Álvaro Peña, José Garcia

The mining industry faces increasing challenges in maintaining high production levels while minimizing unplanned failures and operational costs. Critical assets, such as crushers, conveyor belts, mills, and ventilation systems, operate under extreme conditions, leading to accelerated wear and failure risks. Traditional maintenance strategies often fail to prevent unexpected downtimes, safety hazards, and economic losses. As a response, industries are integrating predictive monitoring technologies, including machine learning, the Internet of Things, and digital twins, to enhance early fault detection and optimize maintenance strategies. This Systematic Literature Review analyzes 166 high-impact studies from Scopus and Web of Science, identifying key trends in fault detection algorithms, hybrid AI models, and real-time monitoring techniques. The findings highlight the increasing adoption of deep learning, reinforcement learning, and digital twins for anomaly detection and process optimization. Additionally, AI-driven methods are improving sensor-based data acquisition and asset management, extending equipment lifecycles while reducing failures. Despite these advancements, challenges such as data standardization, model scalability, and system interoperability persist, requiring further research. Future work should focus on real-time AI applications, explainable models, and academia-industry collaboration to accelerate the implementation of intelligent maintenance solutions, ensuring greater reliability, efficiency, and sustainability in mining operations.

Zelenović Vera, Zelenović Jelena, Đaković Miloš et al.

Background: Innovations in the domain of banking services in the household sector are primarily related to easier access to a current account and new payment methods, which are practical and simple for the consumer. Financial innovation and financial development are positively related, and their impact grows over time. Constant changes in client demands, and constant pressure to reduce costs and increase efficiency leave banks with no choice but to apply modern technology. Purpose: This is to point out the importance of financial innovations and their application in the banking market of Serbia. This is all the more so, as the level and growth of real wages in Serbia, as well as the increased inflationary pressure since the time of COVID-19, make these services for bank clients in Serbia much more expensive and inaccessible, due to differences from clients in developed markets. Methodology/approach: Materials from scientific journals and primary sources were used in the presented research, using the method of content analysis. The presented research was done on the basis of official data available on the National Bank of Serbia's website, which cover a time series of five years. An appropriate statistical regression method was applied. Findings/conclusions: The conducted research showed that financial innovations have adequate application in Serbia as a developing market. The Covid-19 pandemic forced the process of digitization and the adoption of financial innovations to accelerate, and judging by the results of the research, this process is irreversible. Limitations/future research: Future research could address the value of the transactions made in the same period. Is the increase in the value of financial transactions due to an increase in the number of users or an increase in the volume of transactions? Another question would be whether the inflation factor is noticeable in the increase in the financial value of transactions. Certain limitations may appear in future research, related to a real reduction in wages, or even job loss, and that is to what extent are bank clients ready to continue using existing financial innovations, i.e. buy new innovations, at the expense of this reduction.

somayeh Shirzadi Laskookalayeh

Extended Abstract Background: The inadequacy of the supply of agricultural inputs with the demand for various products of this sector reveals the need for the optimal use of resources and increasing productivity. In this regard, addressing the issue of productivity in rice production is very important due to its essential role in feeding different sections of society, providing food security, reducing dependence on imports and foreign exchange, strengthening trade interactions with other countries, generating income, creating employment, creating balance in the business and capital market, and many other issues. In 2022, Mazandaran Province produced 1.6 million tons of paddy as a strategic product, responsible for 44.47% of Iran's paddy production, and in this sense, it has been ranked first in the country. This province has long been known as the hub of rice production, and this user product, having about 76% of Mazandaran's irrigated crop area, has always made an important contribution to the province's employment. For this purpose, the present study aimed to identify factors affecting the prosperity of the rice production business in Mazandaran Province, focusing on measuring the inefficiency of various production inputs, especially the labor force. Methods: Three institutional, managerial, and policy-market criteria effective in the prosperity of rice production business were extracted in this study. The input criterion includes all production factors affecting the productivity of this product, which includes eight subcriteria as water, labor, land, fertilizer, poison, machinery, capital, and seed. The management criterion is all management actions by relevant organizations and bodies (Jahad Keshavarzi, Regional Water, Room of Commerce), which includes six regulatory, executive, organizational, service, and innovation options. The political-market criterion also covered the macro-government policies that can affect the productivity of rice, and there are six financial, economic, structural, commercial, marketing, and strategic development options. Thus, 19 effective options in the productivity of rice production were considered in this study. In this study, factors affecting the productivity of this product were exracted and prioritized using the Analytical Hierarchy Process (AHP) method, measuring the production efficiency of important cultivars of this product (high-quality rice and high-yielding rice) using the data envelopment analysis method (DEA), and then examining productivity changes over time using the Malmquist Index (MI). The data needed for identifying and prioritizing factors in this research were collected by designing a questionnaire, which was completed based on the opinions of 18 experts, including those from the Agricultural Jihad Organization of Mazandaran Province and Sari City, as well as the academic community. The statistics and information of the Agricultural Jahad Organization of the province were used to complete the data in measuring the productivity of production and efficiency of inputs. Results: The results indicate that among the eight production factors, water, mechanization, and land are the most important input factors in rice production with weights of 0.36, 0.2, and 0.14, respectively. Among the five management factors, benefiting from the opinions of agricultural experts, implementing the optimal cultivation pattern of crops according to the climatic conditions and the status of water resources in the province, and using new technologies in agricultural operations with weights of 0.40, 0.25, and 0.14, respectively, were known as three important and superior factors for the management of rice production business. In addition, the financial, economic options, and improvement of the structure of the rice product marketing system were determined with the weights of 0.30, 0.22, and 0.19, respectively, as three policy-market subcriteria affecting the rice productivity of this province. Based on the findings in the agricultural year of 2017-2018 in the east of this province, Qaemshahr City, the land, machinary, poison, and fertilizer inputs were inefficient at 52.68%, 48.26%, 34.37%, and 33.16%, respectively. In 2018, the inefficiency rates in the use of land, labor, and poison inputs were 71.36%, 15.09%, and 4.46%, respectively. In the production of high-yielding rice in the east of the province, there has been inefficiency in the use of land, machinary, seed, water, and fertilizer inputs. Accordingly, Behshahr City acted inefficiently in consuming the mentioned inputs by 68.29, 52.60, 16.65, 12.63, and 7.55%, respectively. In 1998, the cities of Behshahr and Neka acted inefficiently in the consumption of all the investigated inputs, except for machinery. The percentages of inefficiency in the labor input are 16.14 and 42.07%, respectively. In addition, the productivity growth index values of Malmquist in the production of high-quality rice and high-yielding rice are 1.155 and 1.094, respectively. Hence, it can be concluded that the production productivity of this product has increased in this province. Conclusion: The results indicate that the productivity of different rice varieties has increased during the studied period. In the case of high-yielding rice, however, the technical efficiency of producers in newer technology is lower than in older technology. Therefore, it is necessary for trustee organizations and knowledge-based companies to invest in the research, innovation, and promotion of new technology in training to use this technology. In this study, "water" has been determined as the most important input affecting the productivity of this product; therefore, it is recommended to take necessary measures to promote water storage and reduce its consumption. It is also suggested to provide financial support to rice farmers and the development of knowledge-based companies to provide new irrigation systems. Referring to the results of this study, the use of "machinery" is considered the second most effective factor in increasing productivity. In addition to reducing the cost of manpower and saving time, the uniformity and accuracy of the work are increased with mechanized cultivation, and seedlings are exposed to less damage. However, this issue does not mean to ignore the role and importance of the workforce in the production and elimination of job opportunities. Rather, it is recommended to train skilled and specialized human resources to benefit from mechanization for the long-term stability of the rice production business and stable rural employment.

Stig-Johan Wiklund, Magnus Ytterstad

Project portfolio management is an essential process for organizations aiming to optimize the value of their R&D investments. In this article, we introduce a new tool designed to support the prioritization of projects within project portfolio management. We label this tool the PIT-plot, an acronym for Project Impact Tornado plot, with reference to the similarity to the Tornado plot often used for sensitivity analyses. Many traditional practices in portfolio management focus on the properties of the projects available to the portfolio. We are with the PIT-plot changing the perspective and focus not on the properties of the projects themselves, but on the impact that the projects may have on the portfolio. This enables the strategic portfolio management to identify and focus on the projects of largest impact to the portfolio, either for the purpose of risk mitigation or for the purpose of value-adding efforts.

Zenghua Huang, Shirong Ge, Yonghua He et al.

Despite the pressure of carbon emissions and clean energy, coal remains the economic backbone of many developing countries due to its abundant resources and widespread distribution. The stable supply of coal is also vital for the global economy and remains irreplaceable in the future global energy structure. China has been a major contributor to annual coal output, accounting for nearly 50% worldwide since 2014. However, despite implementing intelligent coal mining technology, China’s coal mining industry still employs over 1.5 million underground miners, posing significant safety risks associated with underground mining operations. Therefore, the introduction of coal mining robots in underground mines is an urgently needed scientific and technological solution for upgrading China’s and even the world’s coal energy industry. The working face needs a shearer, hydraulic support, a scraper conveyor, and other equipment for coordination. The deep integration of intelligent technology with factors such as “humans, machines, the environment, and management” in the workplace is the core content of intelligent coal mines. This paper puts forward an advanced framework for robot technology systems in coal mining, including single robots, robotized equipment, robot crowds, and unmanned systems. The framework clarifies the common key technologies of coal mining robot research and development and the cross-integration with new technologies such as 5G, the industrial internet, big data, artificial intelligence, and digital twins to improve the autonomous and intelligent application of coal mining robots. By establishing a scientific and complete standard system for coal mining robots, we aim to achieve the customized research and development and standardized production of various types of robot. A specific analysis is conducted on the research progress of common key technologies such as the explosion-proof design, mechanical system innovation, power drive, intelligent sensing, positioning and navigation, and underground communication of coal mining robots. The current research and application status of various types of coal mining robots in China are summarized. A new direction for future coal mining robot research and development is proposed. Robotic mining systems should be promoted to enhance the overall intelligence level and efficiency of mining equipment. To develop human–machine environment-integrated robots to improve the autonomy and collaboration level of coal mining robots, the digital twinning of the entire mine robot system should be accelerated; the normalized operation level of coal mine robots should be improved; research on coal mining robots, shield support robots, and transportation robots should be performed; intelligence should be achieved in fully mechanized mining faces; and equipment shield support for fully mechanized mining faces should be provided. The practical process of implementing coal mining robotization is summarized in this paper, and the technical and engineering feasibility of the coal mining machine population is verified.

Naza Mmbaga, Joseline Tarimo, Julius Modest

Abstract The overall objective of this study was to assess the role of wildlife tourism in improving the livelihood of communities in Burunge Wildlife Management Area (BWMA) by focusing on the economic and the socio-cultural roles. Data were obtained through household questionnaire, focus group discussions, and key informant interviews in three study villages. The data were analyzed using the Statistical Package for Social Science (SPSS) version 26 and Microsoft Excel. The findings revealed that wildlife tourism operations in the three villages associated with BWMA have generated significant benefits. Several economic and socio-cultural livelihood indicators in the study villages were significantly impacted by wildlife tourism activities. Wildlife tourism appears to have a considerable impact on increasing household incomes, but a relatively lesser impact on reducing agricultural production, which is the economic mainstay for many households in the Babati district. In terms of socio-cultural livelihood indicator, wildlife tourism operation seem to have a significant (x2 = 191.613, df = 8, N = 117 and p < 0.0001) impact in raising the profile and fame of the villages, while having a lesser impact on the erosion of local customs and culture, as most of the villagers continue to uphold their cultural practices. These findings suggest that wildlife tourism in the WMAs can improve people's standard of living and strengthen cultural values. The study recommends full consideration of socio-economic and cultural values of the communities at individual level by the potential stakeholders including policy makers. This will enhance the achievement of sustainable conservation in WMAs and community development through wildlife tourism activities.

Endy Gunanto Marsasi, Asih Dewi Yuanita

In recent years, luxury fashion brands have experienced drastic growth. This study examines how hedonic motivation, self-image congruence, brand experience, and brand attachment are interrelated factors driving the purchase intention of industrial luxury fashion brands. Our research aims to construct a consumer behaviour model to complete the hedonic motivation process, which influences brand attachment and is influenced by demographic factors. The research model will fully predict the proposed model to examine the effect of gender, age, and income. The survey was conducted in Indonesia with a sample of 324 respondents. Multiple group analysis SEM (Structural Equation Modelling) was used to test the model across samples. The results reveal substantial consumer behaviour disparities based on respondents' gender, age, and income level. Research findings can aid the luxury brand industry, particularly the fashion industry, in comprehending demographic differences. It is crucial to develop specific marketing strategies to promote luxury brands, influencing consumers' purchase intentions.

Arnon Archankul, Giorgio Ferrari, Tobias Hellmann et al.

We consider a singular control model of cash reserve management, driven by a diffusion under ambiguity. The manager is assumed to have maxmin preferences over a set of priors characterized by $κ$-ignorance. A verification theorem is established to determine the firm's cost function and the optimal cash policy; the latter taking the form of a control barrier policy. In a model driven by arithmetic Brownian motion, we use Dynkin games to show that an increase in ambiguity leads to higher expected costs under the worst-case prior and a narrower inaction region. The latter effect can be used to provide an ambiguity-driven explanation for observed cash management behavior. Our findings can be applied to broader applications of singular control in managing inventories under ambiguity.

Luis Delgado, Gérald Gurtner, Piero Mazzarisi et al.

This paper presents results from the SESAR ER3 Domino project. Three mechanisms are assessed at the ECAC-wide level: 4D trajectory adjustments (a combination of actively waiting for connecting passengers and dynamic cost indexing), flight prioritisation (enabling ATFM slot swapping at arrival regulations), and flight arrival coordination (where flights are sequenced in extended arrival managers based on an advanced cost-driven optimisation). Classical and new metrics, designed to capture network effects, are used to analyse the results of a micro-level agent-based model. A scenario with congestion at three hubs is used to assess the 4D trajectory adjustment and the flight prioritisation mechanisms. Two different scopes for the extended arrival manager are modelled to analyse the impact of the flight arrival coordination mechanism. Results show that the 4D trajectory adjustments mechanism succeeds in reducing costs and delays for connecting passengers. A trade-off between the interests of the airlines in reducing costs and those of non-connecting passengers emerges, although passengers benefit overall from the mechanism. Flight prioritisation is found to have no significant effects at the network level, as it is applied to a small number of flights. Advanced flight arrival coordination, as implemented, increases delays and costs in the system. The arrival manager optimises the arrival sequence of all flights within its scope but does not consider flight uncertainties, thus leading to sub-optimal actions.

SofÍa Molfese, Diego Rossit, Mariano Frutos et al.

Municipal solid waste management is a paramount activity in modern cities due to the environmental, social and economic problems that can arise when mishandled. In this work, the sequencing of micro-routes in the Argentine city of Bahía Blanca is addressed, which is modeled as a vehicle routing problem with travel time limit and the vehicle's capacity. Particularly, we propose two mathematical formulations based on mixed-integer programming and we solve a set of instances of the city of Bahía Blanca based on real data. Moreover, with this model we estimate the total distance and travel time of the waste collection and use this data to analyze the possibility of installing a transfer station. The results demonstrate the competitiveness of the approach to resolve realistic instances of the target problem and suggest the convenience of installing a transfer station in the city considering the reduction of the traveled distance.

Denis S. Gusev, Elena G. Demidova, Olga A. Novikova

The purpose of the research presented in this article is to develop a dynamic system for forecasting and minimizing the risks of an industrial company based on their quantitative assessment. The article considers the conceptual apparatus of the essential content of risk management of an industrial enterprise, reviews the theoretical aspects of risk management systems and the most significant risk management methods from a practical point of view. The methodological apparatus of qualitative and quantitative analysis and risk assessment has been expanded on the basis of some conditionality of risk classification features identified and a systematic approach to the classification of risks of an industrial enterprise has been proposed, taking into account the dynamics of their impact on the object, the stages of building a dynamic risk management system are given. The article substantiates the need to supplement the dynamic risk management system of industrial enterprises with methods of qualitative and quantitative risk assessment in order to form effective risk management strategies

Yang Li, Chunling Wang, Guoqing Li et al.

In order to balance the interests of integrated energy operator (IEO) and users, a novel Stackelberg game-based optimization framework is proposed for the optimal scheduling of integrated demand response (IDR)-enabled integrated energy systems with uncertain renewable generations, where the IEO acts as the leader who pursues the maximization of his profits by setting energy prices, while the users are the follower who adjusts energy consumption plans to minimize their energy costs. Taking into account the inherent uncertainty of renewable generations, the probabilistic spinning reserve is written in the form of a chance constraint; in addition, a district heating network model is built considering the characteristics of time delay and thermal attenuation by fully exploiting its potential, and the flexible thermal comfort requirements of users in IDR are considered by introducing a predicted mean vote (PMV) index. To solve the raised model, sequence operation theory is introduced to convert the chance constraint into its deterministic equivalent form, and thereby, the leader-follower Stackelberg game is tackled into a mixed-integer quadratic programming formulation through Karush-Kuhn-Tucker optimality conditions and is finally solved by the CPLEX optimizer. The results of two case studies demonstrate that the proposed Stackelberg game-based approach manages to achieve the Stackelberg equilibrium between IEO and users by the coordination of renewable generations and IDR. Furthermore, the study on a real integrated energy system in China verifies the applicability of the proposed approach for real-world applications.

D. Samson

Shupeng Huang, A. Potter, D. Eyers

Recently, industrial and academic communities in the operations and supply chain management (OSCM) field are paying increasing attention to social media. However, the value of social media in OSCM is quite unclear, and more investigations are still needed. To pave the way for directed future research, this paper systematically reviewed and synthesised 152 peer-review journal papers to identify research focus and gaps in this area, supported by an appropriate conceptual framework. The result reveals that the research interests in this area have increased dramatically within the last decade across various industries and regions. Different companies’ OSCM activities, such as sourcing and delivery, can benefit from employment of social media. This paper also indicates that future research can explore the value of social media in sourcing, delivery, product return and reverse logistics, forecasting and inventory management, and product development and production.

Więcek Dorota, Więcek Dariusz, Dulina Luboslav

One of the rationalization areas is the material supply process. New tasks of material supply are: integration of supply with the operation of the entire system, especially at the product design stage, effective use of material resources, reduction of the level of supply costs from the point of view of production costs. In the conditions of unit and small batch production the materials requirement needs to be carefully planned and optimized due to the use of many different kinds, types and sizes of materials and dynamic changes of demand over time. In this situation there are needed tools enabling the measurement of production costs for particular tasks on the basis of currently realized processes. One of these tools is activity based costing which is a groundwork for decision making process in the material supply area. Basing on activity based costing, a model of materials requirements planning was developed, which considers minimizing the number of different kinds and sizes of materials by using alternative materials and, consequently, lowering production costs.

Simonova Marina, Lyachenkov Yuri, Kravchenko Anton

The purpose of the study is to identify the risks of automation and robotization of personnel management systems, the pace of which is increasing and it needs a balanced approach to their use, taking into account the well-known and new risks and constraints. Systematic automation of routine processes leads to a change in the structure of the workflow, making it possible to shorten the production cycle and improve the quality of standard operations with a predictable result, but it does not consider mental and social constraints. The author analyzes the main trends and innovations related to digital resources in personnel selection and management, giving new horizons for career paths, defines the essence of each of selection tools, reveals the existing and future threats in using artificial intelligence in the most common automated HR systems and modern digital instruments with signs of artificial intelligence. The classification of digital tools used in personnel selection was developed, and the possibilities of using these tools in the professional and service career development were analyzed. There is a strong need to formulate a strategic development model of the company using information systems that integrate corporate knowledge bases and the intelligent decision support system, which can eventually be transformed into the individual human development.

Bhuvaneswari Madasamy, Paramasivan Balasubramaniam, Ritaban Dutta

Cotton is an essential commercial crop. Unfortunately, this crop is affected by many pests and diseases, which can cause considerable loss in yield. Climate has a strong correlation with the occurrence of pests and diseases in crops. Currently, weather forecasting services are available to the farmers, which help with weather-based planning of farm operations. Still, weather-based pest and disease forewarning services are not available to all the farmers. Unfortunately, cotton cultivation consumes about one-third of total pesticide consumption, which increases the cost of production apart from polluting the environment. An information and communication technology (ICT) based intelligent pest and disease forewarning system for cotton is an innovative system for providing forewarning on pests and diseases. It aims at improving farm productivity through better crop management. In this paper, the proposed method aims to predict the occurrence of pests and diseases based on microclimatic parameters. This pest and disease forewarning information and appropriate crop management practices will be disseminated to the farmers using electronic media through short message service (SMS), the Internet, etc. In this way, both livelihood security and environmental security are achieved. The proposed model shows a higher optimal performance then the two related works in terms of the average root mean square error rate, average accuracy rate, average percentage error rate, and prediction accuracy.