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Tytuł pozycji:

Development of a Model Supporting the Analysis of Costs Related to Equipment Relocation in a Manufacturing Facility

Tytuł:
Development of a Model Supporting the Analysis of Costs Related to Equipment Relocation in a Manufacturing Facility
Autorzy:
Ostowska, Weronika
Stryhunivska, Olena
Data publikacji:
2025
Słowa kluczowe:
relocation
machinery relocation
cost estimation model
factory layout
manufacturing facility
spatial planning
ABC classification
equipment repositioning
Język:
angielski
Dostawca treści:
BazTech
Artykuł
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This paper presents a universal Excel-based cost estimation model for internal machinery relocation within manufacturing facilities. The objective of the study is to develop and validate a practical tool that enables accurate cost estimation and supports planning decisions in various industrial contexts. Although previous research has primarily focused on full-site relocations, internal repositioning of equipment has received limited academic attention despite its practical and financial relevance. The proposed model divides total relocation costs into three main components: equipment costs, labor costs and transport rental costs. To assist in decision-making and prioritization, the model applies the ABC classification method, grouping activities based on their financial impact. Selected principles of the OLESTR methodology, which integrates spatial and technological planning, are incorporated to enhance layout optimization. Developed in Microsoft Excel, the model was tested using a case study of a printing facility. Two layout variants were evaluated, each involving specific equipment relocation activities. Input parameters such as labor rates and equipment rental prices were defined as ranges to simulate real-world variability. The resulting variation in cost estimates across different simulation runs reflects the uncertain nature of industrial environments. The model offers a transparent, flexible and structured framework that supports industrial managers in evaluating layout alternatives, managing relocation budgets and minimizing disruption. Its adaptable design makes it applicable to a broad range of manufacturing settings and supports data-driven decision-making aimed at optimizing internal relocation processes and reducing associated costs.

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