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Axiomatic Design for Redesign of the Mucuna Slicing Machine Febrina Agusti; Ringgo Ismoyo Buwono; Pitoyo Amrih; Damara Jibran Novianto; Adit Tri Wahyono; Winda Indriyani
International Journal of Mechanical, Industrial and Control Systems Engineering Vol. 3 No. 2 (2026): June : International Journal of Mechanical, Industrial and Control Systems Engi
Publisher : Asosiasi Riset Ilmu Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/ijmicse.v3i2.393

Abstract

Machine redesign was now very important to solve existing design problems and adapt production flows to the development of industrial needs. One of the medium-sized industries that uses machines for its production is the Tempe Chips Industrial Center located in Grobog Village, Wonogiri District. The slicing machine currently used by the Tempe Chips Industrial Center located in Grobog Village, Wonogiri District often produces unstable cuts and a lot of waste. This study aims to present the Axiomatic Design (AD) model as a structured framework for redesigning a high-quality slicing machine. The Axiomatic Design method was used to translate customer needs (Voice of Customer) and environmental criteria (Voice of Environment) into Functional Requirements (FRs). FRs were then used as the main input in developing Design Parameters (DPs), resulting in a Design Matrix. The design results that the proposed design has two blades with a thickness of 2 mm, a 1/4 Hp dynamo, which requires an adjustment to the target capacity of ±10 kg/hour, dimensions of machine had 300 mm in length, 250 mm in width, and 399 mm in height. Axiomatic Design can be effectively applied as a framework for redesigning medium-scale industrial food processing machines, especially for Mucuna commodities, a relatively hard commodity that demands cutting precision. Further research was recommended to develop this design result to the detailed design and prototyping stage.
DESIGNING A BLUEPRINT FOR THE SEMI- AUTOMATION OF SAMPLE SHIPMENT DOCUMENTATION IN SAP USING ENTERPRISE ARCHITECTURE PLANNING (EAP) Winda Indriyani; Cahyani Windarto; Pitoyo Amrih
Proceeding of the International Conference Health, Science And Technology (ICOHETECH) 2026: Proceeding of the 7th International Conference Health, Science And Technology (ICOHETECH)
Publisher : LPPM Universitas Duta Bangsa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47701/pyfwyj14

Abstract

PT Eco Smart Garment Indonesia (PT ESGI) is a garmentmanufacturing company that has implemented anEnterprise Resource Planning (ERP) system based on SAP(System Applications and Products). However, the processof generating sample shipment documents within theShipping Department still faces inefficiencies due torepetitive manual procedures and data redundancy.Administrative staff must perform manual data entry,resulting in a cycle time of 30–40 minutes per shipment anda human error rate of 10–15% per cycle. This study aims todesign a semi-automation blueprint for sample shipmentdocuments within SAP using the Enterprise ArchitecturePlanning (EAP) approach to enhance the efficiency andaccuracy of the shipment administration process. Theresearch methodology follows Spewak’s EAP framework,encompassing an analysis of the existing state, a gapanalysis, data architecture design using Entity RelationshipDiagrams (ERD), and application architecture design in theform of an integrated DHL Report within SAP. The researchyields a semi-automation blueprint featuring an integrateddata architecture based on the "single source of truth"principle, a system architecture comprising an SAP DHLReport add on, and a new workflow that eliminatesredundant manual activities. Implementing this blueprint isprojected to reduce document generation cycle time from30–40 minutes to 15–20 minutes per shipment, minimizehuman error to near-zero levels, and eliminate the need forintermediate Excel files. This study contributes to thedevelopment of information system architectureframeworks within the garment manufacturing sector andserves as a strategic guide for the company’s digital transformation toward more efficient and integratedbusiness processes.