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    Economic and Environmental Sustainability Performance Improvements in the Outdoor Wood Furniture Industry Through a Lean-Infused FMEA-Supported Fuzzy QFD Approach
    (Mdpi, 2025) Ince, Melike Nur; Arpaci, Emrecan; Tasdemir, Cagatay; Gazo, Rado
    Fiercer competition across all industries has made identifying and eliminating lean wastes to enhance sustainability performance an effective route that many companies take. This study focuses on the production process of wood park/garden benches at a company that manufactures outdoor wood furniture. The goal was to identify lean wastes within a sustainability framework across seven operations and integrate multi-criteria decision making (MCDM) methodologies for waste elimination. Eleven lean KPIs addressing economic and environmental sustainability were used to develop and prioritize 13 lean failure modes (LFMs) with Risk Priority Numbers (RPNs) above 100, leading to lean project proposals for each LFM. Eighteen lean tools were ranked using the Fuzzy Quality Function Deployment (Fuzzy QFD) method. A total of eight improvement propositions, namely, Kaizen and continuous improvement, upgrade machinery for energy efficiency, Just-In-Time (JIT), optimize production processes with lean methodologies, implement cost reduction strategies, Total Productive Maintenance (TPM), Investing in Automation, and Andon were implemented. Significant improvements were observed post-implementation: total lead time was reduced by approximately 38.46%, value-added time by 22.05%, and non-value-added time by 47.64%. The required number of workers decreased by 14.29%, and the total inventory decreased by approximately 57.31%. The results contribute to sustainability goals by reducing energy consumption and waste while increasing economic efficiency. It also provides a robust framework for decision making in fuzzy environments, guiding practitioners and academics in lean management and sustainability.
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    Facility Location Selection and Layout Planning through AHP, PROMETHEE, and CORELAP Methods in the Furniture Industry
    (North Carolina State Univ Dept Wood & Paper Sci, 2024) Ince, Melike Nur; Tasdemir, Cagatay
    Facility location selection and internal layout planning are critical strategic decisions for long-term sustainability. This study identified the most feasible location and optimal layout for a commercial bedroom furniture manufacturing facility through a seven-phase evaluation of Istanbul, Ankara, Izmir, and Bursa. The Analytical Hierarchy Process (AHP) and PROMETHEE were used for city and district selection, with AHP calculating criteria weights and PROMETHEE ranking alternatives. The Borda Count Method aggregated MCDM results, selecting Istanbul as the optimal city and Dudullu Organized Industrial Zone (O.I.Z.) as the most favorable district. The CORELAP method developed an optimal single- story layout for a 2688 m2 2 production and assembly facility, enhancing production flow, reducing material handling costs, and improving efficiency. These findings underscore the importance of strategic facility location and layout planning in improving the furniture industry's competitiveness and sustainability. The practical implications of this research are significant, as the findings can be directly applied to improve the competitiveness of the furniture industry. The study offers a comprehensive framework for strategic decision-making, providing valuable insights and a systematic approach applicable to similar problems in various sectors.
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    Forecasting Retail Sales for Furniture and Furnishing Items through the Employment of Multiple Linear Regression and Holt-Winters Models
    (Mdpi, 2024) Ince, Melike Nur; Tasdemir, Cagatay
    Global economic growth, marked by rising GDP and population, has spurred demand for essential goods including furniture. This study presents a comprehensive demand forecasting analysis for retail furniture sales in the U.S. for the next 36 months using Multiple Linear Regression (MLR) and Holt-Winters methods. Leveraging retail sales data from 2019 to 2023, alongside key influencing factors such as furniture imports, consumer sentiment, and housing starts, we developed two predictive models. The results indicated that retail furniture sales exhibited strong seasonality and a positive trend, with the lowest forecasted demand in April 2024 (USD 9118 million) and the highest in December 2026 (USD 13,577 million). The average annual demand for 2024, 2025, and 2026 is projected at USD 12,122.5 million, USD 12,522.67 million, and USD 12,922.17 million, respectively, based on MLR, while Holt-Winters results are slightly more conservative. The models were compared using the Mean Absolute Percentage Error (MAPE) metric, with the MLR model yielding a MAPE of 3.47% and the Holt-Winters model achieving a MAPE of 4.21%. The study's findings align with global market projections and highlight the growing demand trajectory in the U.S. furniture industry, providing valuable insights for strategic decision-making and operations management.
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    Lean and Sustainable Supplier Selection in the Furniture Industry
    (Mdpi, 2023) Ince, Melike Nur; Tasdemir, Cagatay; Gazo, Rado
    The furniture manufacturing sector faces intricate challenges in pioneering sustainable supply chains, particularly with lean and sustainable supplier selection. This study focused on integrating key performance indicators (KPIs) associated with lean philosophy and sustainability into multi-criteria decision-making (MCDM) methodologies. The study methodically evaluated 18 criteria spanning economic, environmental, and social dimensions to discern supplier suitability in both leanness and sustainability realms. Through the ENTROPY method, weights were systematically assigned to these criteria. Subsequently, Fuzzy ARAS and Fuzzy TOPSIS methods were adeptly employed to comparatively assess supplier options. Noteworthy findings included the paramount importance of the distance to the customer and labor practices in supplier selection. The quality level, however, carried the least weight, mainly due to comparable performance scores among alternatives. Consistently, Fuzzy ARAS and Fuzzy TOPSIS results converged to pinpoint Supplier 2 as the optimal choice, reflecting its superior Ki and CCi metrics. Central to this research was the introduction of a structured and holistic framework for lean and sustainable supplier selection, a significant leap forward that promises to be an invaluable asset for practitioners and scholars in the furniture industry, supply chain management, multi-criteria decision-making, and policymaking.