Study of Demand Forecasting Using Time-Series Analysis (ARIMA)

Study of Demand Forecasting Using Time-Series Analysis (ARIMA) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Study of Demand Forecasting Using Time-Series Analysis (ARIMA) Vivek Kumar Pathak, Tanmay tiwari, Marmik Chaurasia, Gyanendra Bagri This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6801470/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Demand forecasting plays a pivotal role in the manufacturing industry, influencing inventory management, production planning, and operational efficiency. This research explores the application of time series analysis, specifically the Auto Regressive Integrated Moving Average (ARIMA) model, in forecasting demand within the manufacturing sector. The study aims to assess the effectiveness of the ARIMA model in predicting demand patterns, addressing the challenges posed by dynamic market conditions and fluctuating consumer preferences. By analyzing historical data and employing the ARIMA methodology, this research seeks to provide insights into the accuracy and reliability of demand forecasts in the manufacturing industry. The findings of this study contribute to enhancing decision-making processes, optimizing resource distribution, and improving supply chain management (scm) strategies in manufacturing enterprises. Supply Chain Management Demand Forecasting ARIMA Full Text Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 05 Jul, 2025 Reviewers invited by journal 23 Jun, 2025 Editor invited by journal 22 Jun, 2025 Editor assigned by journal 05 Jun, 2025 First submitted to journal 03 Jun, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6801470","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":474976778,"identity":"a222cad1-ddf0-49fa-b992-3fe9739f55be","order_by":0,"name":"Vivek Kumar Pathak","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA90lEQVRIiWNgGAWjYHACNgaGAww8QJr9xwcQl52gDma4FgbJGSAtzERqAdsmzQMWIKDBnP38sQc/zhyWMTjelmBs82ubPB8zA+OHjzm4tVj2JLMb9tw4zGNw5tiB5Ny+24ZtzAzMkjO34dZicCCZTYLnQxqP5Iz0hsO5PbcZgVrYmHnxaTn/mE3yD0jL/OeNzZY9t+0Ja7mRzCbNc8OGh1+C7TAzw4/biQS1WM54bCYtcwaohSctjbG34XZyGzNjM16/mPMnPpN8c0zCno39mBnDjz+3bee3Nx/88BGfw1B4jG1gsgG3egwtDH/wKh4Fo2AUjIIRCgBR3U16dXwF+wAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0003-0584-6120","institution":"SRM Institute of Science and Technology: SRM Institute of Science and Technology (Deemed to be University)","correspondingAuthor":true,"prefix":"","firstName":"Vivek","middleName":"Kumar","lastName":"Pathak","suffix":""},{"id":474976779,"identity":"4af7bf6d-e3f0-4018-987f-ca5e93d3e14c","order_by":1,"name":"Tanmay tiwari","email":"","orcid":"","institution":"KIET Group of Institutions: Krishna Institute of Engineering \u0026 Technology","correspondingAuthor":false,"prefix":"","firstName":"Tanmay","middleName":"","lastName":"tiwari","suffix":""},{"id":474976780,"identity":"c0c37374-51c6-4696-85d0-b31383dbc177","order_by":2,"name":"Marmik Chaurasia","email":"","orcid":"","institution":"KIET Group of Institutions: Krishna Institute of Engineering \u0026 Technology","correspondingAuthor":false,"prefix":"","firstName":"Marmik","middleName":"","lastName":"Chaurasia","suffix":""},{"id":474976781,"identity":"aca74036-8920-48b0-98cb-dff36ac4c7b2","order_by":3,"name":"Gyanendra Bagri","email":"","orcid":"","institution":"SRM University - Delhi Campus: SRM University - NCR Campus","correspondingAuthor":false,"prefix":"","firstName":"Gyanendra","middleName":"","lastName":"Bagri","suffix":""}],"badges":[],"createdAt":"2025-06-02 10:53:44","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6801470/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6801470/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":85535518,"identity":"f9b06f07-8533-4b1f-89f0-83f2ff8add3c","added_by":"auto","created_at":"2025-06-27 04:47:47","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":726753,"visible":true,"origin":"","legend":"","description":"","filename":"ReasearchPaperMarmik2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6801470/v1_covered_21b6409a-1b23-4be8-9800-d53c42fc5dd3.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003eStudy of Demand Forecasting Using Time-Series Analysis (ARIMA)\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"international-journal-of-system-assurance-engineering-and-management","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ijsa","sideBox":"Learn more about [International Journal of System Assurance Engineering and Management](http://link.springer.com/journal/13198)","snPcode":"13198","submissionUrl":"https://www.editorialmanager.com/ijsa/default2.aspx","title":"International Journal of System Assurance Engineering and Management","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":" Supply Chain Management, Demand, Forecasting, ARIMA","lastPublishedDoi":"10.21203/rs.3.rs-6801470/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6801470/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Demand forecasting plays a pivotal role in the manufacturing industry, influencing inventory management, production planning, and operational efficiency. 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