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R.E.M (Rekyasa Energi Manufaktur) Jurnal
Published by Universitas Muhammadiyah Sidoarjo
ISSN : 25275674     EISSN : 25283723     DOI : https://doi.org/10.21070/r.e.m
Core Subject : Engineering,
Engineering
Focus and Scope Aim: to facilitate scholar, researchers, and teachers for publishing the original articles of review articles. Scope: Mechanical Engineering include: Energy Conversion Renewable Energy Manufacturing Materials and Design Engineering Mechatronics
Arjuna Subject : Teknik (semua kategori) - Teknik Mesin
Articles 183 Documents
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Design and Experimental Evaluation of a Low-Power Organic Waste Shredder with Conveyor Feeding Mechanism Wilarso Wilarso; Riyan Mardiyana
R.E.M. (Rekayasa Energi Manufaktur) Jurnal Vol 11 No 2 (2026): In Progress
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/r.e.m.v11i2.1842

Abstract

Household composting benefits from controlled size reduction, but many reported organic-waste shredders require power levels or three-phase supplies that are unsuitable for domestic use. This study designed and experimentally evaluated a 250 W, single-phase organic-waste shredder equipped with a conveyor-assisted feeding mechanism. The design procedure comprised requirement definition, transmission and shaft calculations, CAD modelling, finite-element analysis (FEA), prototype fabrication, and repeated capacity tests using leaves, fruit peels, and corn cobs. A 1:10 gearbox and a two-stage V-belt transmission were used to increase torque, while the conveyor supplied material to the cutting chamber at 0.17 m/s. The frame analysis produced a maximum von Mises stress of 45.46 MPa, a maximum displacement of 0.12 mm, and a minimum factor of safety of 4.06 under the specified 80 kg static load. Mean throughput was 12.0 kg/h for leaves, 10.0 kg/h for fruit peels, and 7.5 kg/h for corn cobs. The configuration therefore demonstrates the feasibility of low-power household shredding; however, its claimed feeding advantage must be interpreted as a design feature until a controlled conveyor-versus-direct-feeding experiment is completed. Particle-size distribution and inferential statistics must also be reported before final acceptance.
Energy Performance Analysis of the Crushing Area at PT. X Using Energy Performance Indicators (EnPI) Based on ISO 50001:2018: Analisis Kinerja Energi pada Area Crushing di PT. X Menggunakan Energy Performance Indicator (EnPI) Berdasarkan ISO 50001:2018 Arifia Ekayuliana; Andi Ulfiana; Carelita Maulidi Agnia; Asep Apriana; Ahmad Bustomi
R.E.M. (Rekayasa Energi Manufaktur) Jurnal Vol 11 No 2 (2026): In Progress
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/r.e.m.v11i2.1863

Abstract

Energy consumption in the mining industry is a key factor influencing operational costs and the sustainability of production processes. The crushing area represents a Significant Energy Use (SEU), accounting for over 50% of total operational energy consumption. This study analyzes the energy performance of the crushing area at PT. X using Energy Performance Indicators (EnPI) based on the ISO 50001:2018 framework. Data on electrical energy consumption and ore production from January to November 2025 were used to calculate the EnPI, establish the Energy Baseline (EnB), and analyze energy deviations. SEUs were identified through Pareto analysis based on installed power contribution. The results indicate an average EnPI of 7.886 kWh/tonne for the crushing area, with an established Energy Baseline of 7.8 kWh/tonne. Among 18 electric motors with a total power of 570.45 kW, four units were identified as SEUs—the Secondary Crusher Motor (150 kW), Warman Motor 1 (110 kW), Warman Motor 2 (110 kW), and Primary Crusher Motor (90 kW)—contributing a cumulative 80.64% of the load. Load factor analysis revealed that three of the four SEU units operated above nominal capacity (>100%). The largest positive deviations occurred in October (7.71%) and November (4.82%), findings that were corroborated by field observations. The identified potential energy savings amount to 31,877 kWh/year (1.25%), equivalent to IDR 38,379,600/year. Opportunities for energy efficiency lie primarily in operational improvements and enhanced equipment reliability rather than investments in new technology.
Expert System Application for Production Planning and Control Optimization in Jobshop Manufacturing: A Review for Developing Economies Abiodun Gbemileke ABIOYE; Musibaudeen Olatunde IDRIS; Olakunle OLUKAYODE; Oriyomi O. ADETAYO; Abdulhafiz Ademola ADEFAJO; Babajide Joshua OJERINDE
R.E.M. (Rekayasa Energi Manufaktur) Jurnal Vol 11 No 2 (2026): In Progress
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/r.e.m.v11i2.1869

Abstract

Production planning and control (PPC) in job-shop manufacturing is complicated by factors such as high product variety, small batch sizes, changing routings, and frequent disruptions. These difficulties are more severe in developing economies, where limited infrastructure, shortage specialist expertise, unreliable energy supply, and financial constraints restrict the adoption of advanced planning systems. This review critically examines the application of expert systems (ESs) to PPC in job shops. It evaluates their capacity to integrate forecasting, manpower planning, energy utilization, machine scheduling, inventory control, cost estimation, and due-date determination. The review follows a sequential process of literature identification, screening, thematic classification, quality appraisal, and synthesis. Its novelty lies in treating these PPC functions as interdependent rather than isolated decisions and in translating  evidence into an explainable, feedback-based ES–PPC architecture designed for the operational realities of small and medium-sized enterprises in developing economies. The synthesis shows that existing studies generally optimize individual functions, while only a limited number integrate rule-based reasoning, optimization models, shop-floor data, and performance feedback within a unified framework. The review therefore proposes an integrated architecture and identifies priorities for real-time adaptation, low-cost deployment, explanation of recommendations, and validation with shop-floor data. These contributions provide a structured foundation for the development of practical ES-enabled PPC systems for job-shop manufacturing.

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