Evaluasi Produktivitas Proses Produksi Anchor Bold melalui Penerapan Objective Matrix (OMAX) di Industri Manufaktur

AJB, as a manufacturing company, has faced difficulties in meeting its production targets for anchor bold despite utilizing various resources such as labor, raw materials, energy, and working hours. This study aims to measure and evaluate production productivity using the objective matrix (OMAX) method and propose improvements through the fishbone diagram and 5W+1H approach. Data were collected from January to December 2023, covering inputs of materials, labor, energy, and production outputs. Results indicate fluctuating productivity levels, peaking in November (98%) and dropping in August (-39%). Key factors reducing productivity include raw material delays, energy waste, ineffective operators, and inefficient workspace layout. This studi contributes an applicable productivity evaluation model for manufacturing industries.

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Publication Details

Journal
Journal of Industrial and Engineering System
Published
2026-10-29
DOI
https://doi.org/10.31599/xv6zac09
Primary Topic
Management and Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Evaluasi Produktivitas Proses Produksi Anchor Bold melalui Penerapan Objective Matrix (OMAX) di Industri Manufaktur

Sonny Nugroho Aji, Roberta Heni Anggit Tanisri, Noval Dwy Setiawan
1 links
Journal of Industrial and Engineering System
Management and Optimization Techniques
article

Evaluasi Produktivitas Proses Produksi Anchor Bold melalui Penerapan Objective Matrix (OMAX) di Industri Manufaktur

Sonny Nugroho Aji, Roberta Heni Anggit Tanisri, Noval Dwy Setiawan
article en

Abstract

AJB, as a manufacturing company, has faced difficulties in meeting its production targets for anchor bold despite utilizing various resources such as labor, raw materials, energy, and working hours. This study aims to measure and evaluate production productivity using the objective matrix (OMAX) method and propose improvements through the fishbone diagram and 5W+1H approach. Data were collected from January to December 2023, covering inputs of materials, labor, energy, and production outputs. Results indicate fluctuating productivity levels, peaking in November (98%) and dropping in August (-39%). Key factors reducing productivity include raw material delays, energy waste, ineffective operators, and inefficient workspace layout. This studi contributes an applicable productivity evaluation model for manufacturing industries.

Journal of Industrial and Engineering System
Universitas Bhayangkara Jakarta Raya (ID)
Decent work and economic growth, Industry, innovation and infrastructure
Openalex Percentile: Top 21%
Management and Optimization Techniques
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