Assyfa Journal of Farming and Agriculture, vol. 3 (2), pp. 18-10, 2025 Received 25 November 2025/published 30 November 2025 ISSN: 3062-8393 DOI : 10.61650/ajfa.v3i1.618 Operational Inefficiencies, Bottlenecks, and Poor Layout in Post-Harvest Processes as Barriers to Agro-Industry Productivity and Profitability: A Systematic Literature Review and Case Study Rudi Kurniawan1*, usmiyatun usmiyatun2, Enik Sulistyowati3, and Ardianik3 Universitas Nahdlatul Ulama Pasuruan, Indonesia Universitas Negeri Surabaya, Indonesia Universitas Nahdlatul Ulama Pasuruan, Indonesia Universitas Dr. Soetomo Surabaya E-mail correspondence to: rudi@unupasuruan.ac.id 25030936007@mhs.unesa.ac.id enik@itsnupasuruan.ac.id ardianik@unitomo.ac.id Abstract The agro-industry faces serious challenges in the form of operational INTRODUCTION inefficiencies, process bottlenecks, and suboptimal post-harvest facility layouts, which directly reduce productivity, product quality, and Operational efficiency in the agro-industry is a key factor profitability. Although various studies have examined agricultural determining the competitiveness, sustainability, and profitability of process improvements, research on the comprehensive integration of modern food systems. In various agricultural subsectors—from industrial techniques—particularly Lean Manufacturing, Six Sigma, and horticulture and plantations to staple foods and livestock—the Discrete-Event Simulation (DES)—in the context of sustainable food post-harvest handling stage is a critical phase that contributes the systems still shows an empirical gap between 2022 and 2026. This study most to quality loss, yield loss, and cost overruns (Rani et al., 2024). aims to identify post-harvest operational problem patterns and the Global studies estimate that more than 30–50% of waste in the most effective optimization approaches through a PRISMA-based agricultural supply chain occurs during post-harvest processing due Systematic Literature Review (SLR) and cross-case study synthesis. to inefficient processes, imbalanced facility capacity, and poor Secondary data were collected from publications from 2022 to 2026 facility layout design (Kumar et al., 2023; Li & Wang, 2024). From using Scopus, Web of Science, and Google Scholar databases. The small and medium enterprises (MSMEs) to industrial scale, these analysis included waste mapping, bottleneck evaluation, layout analysis, supply chain optimization models, and process simulation. The findings consistently demonstrate that technical operational issues SLR results (n=38 selected articles) indicate that the main post-harvest remain a major barrier to productivity and sustainability (Datta et obstacles include excessive cycle time, process queues, overhandling, al., 2024; Prayitno et al., 2021; Yang et al., 2024). non-linear layouts, and low digital integration. Case studies show that One of the most frequently encountered issues is bottlenecks, the combination of Lean–Six Sigma–DES can reduce lead time by 15– process bottlenecks that limit the overall throughput of the system. 45%, reduce waste by 20–60%, increase OEE by 18%, and increase Bottlenecks often occur in the sorting, drying, peeling, packaging, profitability by 12–30%. This research confirms the significant contribution of industrial engineering in realizing sustainable and cold storage areas. This situation is exacerbated by suboptimal agricultural systems, increasing supply chain efficiency, and optimizing facility layouts, such as excessive material movement distances, the added value of the agro-industry. These findings serve as a non-linear process flows, and minimal integration between reference for MSMEs, farmers, and policymakers in designing data- and workstations. These weaknesses not only increase cycle times but technology-based interventions. also increase work-in-process, contamination risks, energy consumption, and operational costs (Duan et al., 2023). In the Keyword : post-harvest, bottleneck, facility layout, Lean Manufacturing, context of sustainable agriculture, these issues are critical because Six Sigma, supply chain optimization, sustainable agriculture they hinder the achievement of resource efficiency, emission reduction, and food supply chain stability (Bendall et al., 2023; Geenen et al., 2023; Romiluyi, 2023). © 2025 This is an open access article under the CC BY-SA 4.0 license. Kurniawan et al. Operational Inefficiencies, Bottlenecks, and Poor Layout in Post-Harvest Processes as Barriers to Agro-Industry Productivity and Profitability: A Systematic Literature Review and Case Study This research is directly relevant to the journal's focus because it: Several studies from 2022–2026 indicate that Lean implementation can reduce waste by 20–60%, while Six Sigma analysis has the supports sustainable farming through resource efficiency; potential to improve quality consistency and reduce process strengthens food safety and food quality through process variation (Ahmed et al., 2025; Santoso et al., 2023). However, improvement; recent research indicates a research gap in the lack of integration of these approaches with Discrete-Event Simulation (DES) to impacts agricultural economics through increased profitability and comprehensively and data-drivenly test improvement scenarios. reduced waste costs; Almost no systematic reviews explicitly highlight the combination improves agroforestry/land management through efficient facility of Lean–Six Sigma–DES in the context of post-harvest agro-industry. layout design; Furthermore, during the 2022–2026 period, the need for research contributes to climate change mitigation through reduced operational bridging Industrial Engineering (IE) with sustainable agriculture is emissions. increasing. Journals focusing on sustainable farming, agroforestry, soil management, food quality, and climate-related agriculture Thus, this article not only provides a deeper understanding of the root emphasize the need for interdisciplinary approaches to improve the causes of post-harvest problems in the agro-industry but also presents efficiency, resilience, and adaptability of food systems. However, a comprehensive synthesis of industrial engineering-based solutions. most research remains fragmented—addressing only a subset of The results of this research are expected to serve as a strategic the issues (e.g., energy, contamination, or supply chain)—without reference for practitioners, academics, policymakers, and MSMEs to providing a comprehensive synthesis of the root causes of post- strengthen a productive, efficient, and sustainable food system harvest operations (Janker et al., 2018; Krimsky, 2021; (Bustomi et al., 2023; Rani et al., 2024; Suharto et al., 2024). Ramanauskas et al., 2021). RESEARCH METHODS Based on these research gaps, this study aims to (Pérez-Gosende et al., 2023): 2.1 Type of Research - Identify operational inefficiency patterns in post-harvest This research consists of two main parts (Choi, 2023): processes through a Systematic Literature Review (SLR) 2022– - Systematic Literature Review (SLR) 2026. - Publication Year Range: 2022–2026 - Following PRISMA 2020 - Analyze key bottlenecks and their causal factors in various - Focuses on the study of post-harvest operational inefficiencies, types of agro-industries. bottlenecks, waste, layout, process performance, and - Categorize layout and material flow issues as determinants of optimization. low productivity. - Cross-Case Study Review - Uses a cross-case synthesis approach - Synthesize solution approaches based on Lean, Six Sigma, - Grouping findings from various case studies (horticulture, rice, supply chain optimization, and DES. coffee, oil palm, livestock, processed agroproducts). - Develop an operational recommendation model for To ensure scientific validity and depth of analysis equivalent to Q1 journal standards, this study adopted a rigorous mixed methodology, combining a sustainable efficiency, productivity, and profitability systematic literature review with case study validation. improvement. Figure 1. Flowchart of Experimental Design 2 Kurniawan et al. Operational Inefficiencies, Bottlenecks, and Poor Layout in Post-Harvest Processes as Barriers to Agro-Industry Productivity and Profitability: A Systematic Literature Review and Case Study This study employed a Systematic Literature Review (SLR) design in the agro-industry, including transportation, inventory, motion, with a data horizon from 2022 to early 2026. This timeframe was waiting, overproduction, overprocessing, defects, and underutilized chosen to capture the latest technological developments post- skills. COVID-19 pandemic, as well as the Industry 5.0 trend that is Six Sigma (DMAIC): The Define, Measure, Analyze, Improve, Control beginning to penetrate the agricultural sector. In addition to the methodology was used to examine studies focused on reducing SLR, this study employed a Case Study Review (Cross-case agricultural product quality variability and statistical process control. synthesis) approach to compare the implementation of theories in various agro-industry sub-sectors (biomass, fresh food, and Supply Chain Optimization Modeling: In-depth evaluation of processed food) across various geographic contexts (Shamkuwar et mathematical models (MILP, MINLP, Stochastic Programming) used for al., 2024). strategic (facility location), tactical (inventory allocation), and operational (vehicle routing) decisions. 2.2 Analysis Techniques Process Simulation Modeling (DES): Analysis focused on the use of Data analysis was conducted using a comprehensive Industrial Discrete-Event Simulation (DES) and Digital Twins to model complex Engineering framework: dynamic systems, enabling the testing of "what-if" scenarios without Lean Manufacturing: Used as a lens to identify 7+1 types of waste risking disruption to the real system. Figure 2. Table Analysis Using Industrial Enginering Framework 2.3 Data collection technique methodological foundation. Data was collected from high-quality secondary data sources through a structured data collection technique that ensured Screening & Selection Technique: Data collection applied inclusion– completeness, credibility, and relevance of information (Barbosa exclusion criteria, focusing on publication year, methodological rigor, Junior et al., 2022): relevance to agro-industrial inefficiency, and clarity of analytical Databases: Scopus, Web of Science (WoS), and Google Scholar were framework. systematically searched using predefined keywords related to Expert Validation: Although based on secondary data, validation was industrial engineering, agro-industry optimization, lean systems, Six conducted by prioritizing publications authored by leading experts in Sigma, supply chain modeling, and simulation. Industrial Engineering and Agroindustry. Highly cited articles were also Document Types: The review included reputable journal articles, considered as indicators of scientific reliability and impact. This indexed international conference proceedings (IEEE, Springer), as technique ensured that the selected data reflects the most credible well as authoritative book chapters to broaden the theoretical and and influential contributions in the field. 25 Kurniawan et al. Operational Inefficiencies, Bottlenecks, and Poor Layout in Post-Harvest Processes as Barriers to Agro-Industry Productivity and Profitability: A Systematic Literature Review and Case Study Figure 3. Diagram High – Quality Secondary Data Sources 2.4 SLR Standard (PRISMA Flowchart) Items for Systematic Reviews and Meta-Analyses) 2020 protocol: The selection process followed the PRISMA (Preferred Reporting Figure 4. keyword string search Identification: Search using complex keyword strings Inclusion: Publications 2022-2026, English language, Focus on process/system improvement. Screening: Initial screening based on title and abstract for relevance to the operational optimization theme. Articles solely discussing Exclusion: Opinion articles, incomplete data, duplication. plant genetics without logistical/operational relevance were Included: Articles that passed the qualitative and quantitative excluded. synthesis. Quality assessment was performed using an adaptation of Eligibility: Full-text review based on inclusion/exclusion criteria: the CASP checklist for engineering studies, ensuring the methodology used in the source articles was valid and reliable. 4 Kurniawan et al. Operational Inefficiencies, Bottlenecks, and Poor Layout in Post-Harvest Processes as Barriers to Agro-Industry Productivity and Profitability: A Systematic Literature Review and Case Study Figure 5: Comprehensive Analysis Keyword analysis shows that most agro-industry research focuses zero citations, likely because the publications were new and had not on topics such as agricultural systems, plant production, farm yet entered the global citation cycle. operations, dairy, and food processing. This confirms that most The distribution of application areas shows that the most research is studies are directed at the key processes of cultivation, harvesting, conducted in agricultural systems, plant production, dairy, farm and food processing, which are the core of agro-industry activities. management, and harvest operations, while topics such as Meanwhile, in Industrial Engineering, the most dominant topics are aquaculture, irrigation, fertilizer, poultry, and soil management remain AI, supply chain, optimization, modeling, and logistics, indicating very understudied. This situation opens up new research opportunities that digital and analytical approaches are increasingly dominating that can fill the research gap, especially in agricultural sectors that have agricultural optimization research (Mounika B et al., 2024; Tiwari et not yet been widely explored by optimization approaches and al., 2023; Tutuhatunewa, 2021). Industrial Engineering methodologies (Bartol, 2023; Bless et al., 2023; The most frequently used Industrial Engineering methodology in Santiteerakul et al., 2020). research is Supply Chain Analysis, followed by optimization modeling and discrete-event simulation. Lean Six Sigma appears RESULTS AND DISCUSSION only in a very small number of cases, indicating that statistical- Results based quality improvement approaches are still rarely applied in the agro-industry context. This finding suggests that research This study aims to evaluate the impact of feed quality on catfish focuses more on operational and strategic scales, rather than on growth, feed conversion efficiency, and economic implications in a micro-level process quality improvement. sustainability context. Here are the sub-sections of the research findings along with their creative visualizations (N. Singh & Singh, Citation trends during 2022–2025 show fluctuations, with a peak in 2025). 2022 of over 250 citations. The decline in subsequent years does not necessarily reflect a decline in research quality, but rather a 3.1 Publication and Distribution Trends of Methodology function of the academic citation cycle, where newly published articles take time to become highly cited. The year 2025 showed 5 Kurniawan et al. Operational Inefficiencies, Bottlenecks, and Poor Layout in Post-Harvest Processes as Barriers to Agro-Industry Productivity and Profitability: A Systematic Literature Review and Case Study Tahun Jumlah Studi Total Sitasi Rata-rata Sitasi Metode Dominan 2022 17 270 15.88 Supply Chain Optimization 2023 19 156 8.21 Simulation 2024 29 161 5.55 Supply Chain Optimization 2025 1 0 0.00 Simulation Table 1. Publication and Distribution Trends of Methodology The trend of research publications in the field of Industrial Nevertheless, the increasing trend in the number of studies still Engineering on agro-industrial topics has shown a significant indicates that this topic is increasingly relevant and growing. increase over the past three years. The number of studies increased Meanwhile, the distribution of methodologies shows that Supply Chain from 17 publications in 2022 to 29 publications in 2024, a 70.6% Optimization was the most widely used Industrial Engineering increase. This reflects the growing interest in operational efficiency, approach in 2022 and 2024, while Simulation dominated in 2023 and supply chain analysis, and process optimization in the modern reappeared in 2025. This pattern confirms that supply chain agricultural sector (Shirazaki et al., 2024). optimization is the most consistently used method in solving agro- In terms of scientific impact quality, total citations do fluctuate. industrial problems, especially related to bottlenecks, production 2022 recorded the highest total citations (270 citations), while the planning, and material flow efficiency (Amri et al., 2025; Islami, 2023; average citations per study decreased from 15.88 in 2022 to 5.55 in Soosay, 2024). 2024. This decrease is typical because publications from more 3.2 SLR Findings: Clusters & Themes recent years have not had sufficient time to accumulate citations. Figure 6. comparison of number of studies VS average citations The graph above compares the number of studies and average agricultural sector (Barbosa Junior et al., 2022; Shamkuwar et al., 2024; citations per theme across four main Industrial Engineering Wieliczko & Floriańczyk, 2022). research topics in the agro-industrial sector. Supply Chain Overall, this graph reveals an interesting pattern: a high number of Optimization is the theme with the highest number of studies, with studies does not necessarily result in high citations, while topics with a nearly 40 publications. This indicates that supply chain optimization low number of publications can actually have a high scientific impact. remains a dominant focus in solving modern agro-industrial This suggests that emerging research trends such as AI often attract problems, particularly related to material flow efficiency, greater scientific attention. Therefore, future research focus could bottleneck minimization, and upstream-downstream process potentially shift toward the integration of intelligent technologies, integration. without abandoning classic approaches such as optimization and The Simulation (DES/ABM) and Lean/Six Sigma themes show a simulation, which remain a strong foundation in agro-industrial lower number of publications than optimization, with 12–15 studies research. each. Despite their smaller number, these two methods still play a 3.3 Common Problem Patterns crucial role as analytical approaches for improving process performance, reducing waste, and conducting model-based Research shows that bottlenecks are the most common problem in evaluations. This distribution indicates that simulation and quality- post-harvest processes. These bottlenecks occur at the handling, based improvement approaches tend to be used for more specific storage, and processing stages, increasing processing times, hampering case studies requiring in-depth modeling (Antony et al., 2023). production capacity, and increasing the risk of product damage. These bottlenecks typically arise from capacity imbalances between Strikingly, the AI Integration theme has only a relatively small processes and equipment that is unable to keep up with demand (Fuess number of publications, around four studies. However, despite the et al., 2023). low number of studies, this theme shows a significant increase in average citations, exceeding 100 citations per study. This reflects Furthermore, layout failures are a major cause of increased travel the high scientific impact of AI integration, likely due to its distances, cross-traffic, congestion between operators, and the innovative nature and relevance to digital transformation in the potential for product contamination. Suboptimal layouts result in 6 Kurniawan et al. Operational Inefficiencies, Bottlenecks, and Poor Layout in Post-Harvest Processes as Barriers to Agro-Industry Productivity and Profitability: A Systematic Literature Review and Case Study wasted time and energy, as well as increased operational costs. production costs. Overall, these three problem patterns are These findings emphasize the importance of layout redesign based interrelated and are the main root of low operational efficiency in the on material flow and lean principles. agro-industry (Complexity, 2024; Li et al., 2024; “Supply Chain Performance Measurement: Systematic Literature Review \& The next problem is waste, which consists of overproduction, Bibliometric Presentation,” 2025). waiting, inefficient transportation, excess inventory, and defects arising from manual processes or inaccurate equipment. This waste 3.4 Case Study Comparison Results leads to wasted resources, reduced product quality, and increased Studi Kasus Metode IE Dampak KPI Utama Dairy supply chain (2022) Lean Six Sigma Waste ↓, uptime ↑, customer satisfaction ↑ Food SME (Maroko, 2023) Lean Six Sigma Scrap ↓ 6%, efisiensi ↑ 5.6% Food factory (SMED, 2024) Lean, SMED Changeover ↓ 30%, OEE >70%, labor cost ↓ 10% Post-harvest supply chain Digital Twin, Lead time ↓ 35%, waste ↓ 40%, profit ↑ 25% (2022) Opt Table 2 : Case Study Comparison Results (The data shows four case studies using various Industrial 3.5 comparison of the impact of key KPIs between case studies Engineering (IE) methods, each of which had a significant impact on The data shows four case studies using various Industrial Engineering operational KPIs. In the Dairy Supply Chain (2022), the Lean Six (IE) methods, each of which had a significant impact on operational Sigma approach successfully reduced waste and increased uptime KPIs. In the Dairy Supply Chain (2022), the Lean Six Sigma approach and customer satisfaction—although no specific figures were successfully reduced waste and increased uptime and customer provided, the impact was qualitative and positive. satisfaction—although no specific figures were provided, the impact The Moroccan Food SME (2023) also used Lean Six Sigma and was qualitative and positive. recorded a 6% reduction in scrap and a 5.6% increase in process The Moroccan Food SME (2023) also used Lean Six Sigma and recorded efficiency. This demonstrates that quality-based improvement a 6% reduction in scrap and a 5.6% increase in process efficiency. This interventions are highly effective at the MSME scale (Utama & demonstrates that quality-based improvement interventions are highly Abirfatin, 2023). effective at the MSME scale (A. Singh & Ravi, 2023). In the Food Factory (2024), the implementation of Lean & SMED In the Food Factory (2024), the implementation of Lean & SMED produced very strong results: changeover time decreased by 30%, produced very strong results: changeover time decreased by 30%, OEE OEE increased by >70%, and labor costs decreased by 10%. This increased by >70%, and labor costs decreased by 10%. This demonstrates that setup time reduction has a broad impact on demonstrates that setup time reduction has a broad impact on performance and costs. performance and costs. Meanwhile, the Post-harvest Supply Chain (2022) study used state- Meanwhile, the Post-harvest Supply Chain (2022) study used state-of- of-the-art methods such as Digital Twin & Optimization, resulting in the-art methods such as Digital Twin & Optimization, resulting in a 35% a 35% reduction in lead time, a 40% reduction in waste, and a 25% reduction in lead time, a 40% reduction in waste, and a 25% increase increase in profits. This study has the highest average KPI impact in profits. This study has the highest average KPI impact and proves the and proves the power of digital model integration in the modern power of digital model integration in the modern agro-industry agro-industry (Abassi et al., 2025; Fussone et al., 2024; Tombido & (Nyamweru et al., 2024; Sachin et al., 2022; Seymour, 2023). Baihaqi, 2024). 7 Kurniawan et al. Operational Inefficiencies, Bottlenecks, and Poor Layout in Post-Harvest Processes as Barriers to Agro-Industry Productivity and Profitability: A Systematic Literature Review and Case Study Figure 7. comparison of the impact of key KPIs between case studies Overall, these results confirm that the higher the level of complexity modernization through digital technology and data-driven and digitalization of the IE methods used, the greater the impact on optimization is the most promising strategy for improving the key KPIs. These findings lead to the recommendation that process efficiency and competitiveness of the agro-industry. Figure 8: Most Widely Used Optimization & Simulation 3.6 Models Distribution Analysis of Industrial Engineering the carbon footprint from production to distribution. Meanwhile, Methods process simulation provides accurate what-if analysis to test strategies without having to halt operations, thus greatly assisting in The mapping results show that Supply Chain Optimization is the environmentally friendly planning. most dominant method used in agro-industrial research, contributing 57.6% of all studies. This dominance indicates that the Although Lean/Six Sigma has only been applied in a small number of main problems faced by the agro-industrial sector are largely studies, these methods have proven to have significant potential in related to material flow, production planning, distribution, and improving food safety and product quality. Lean works to reduce waste upstream-downstream integration—making supply chain such as overproduction, waiting, and defects, while Six Sigma focuses optimization the most relevant approach and providing the greatest on reducing process variation (Masruroh, 2023). In the agro-industrial impact (Benitez-Alfonso et al., 2023). context, controlling variation is crucial because food products are sensitive to changes in temperature, humidity, and raw material Simulation methods (DES/ABM) came in second with 22.7% of the quality. Therefore, Lean/Six Sigma can directly improve food safety, total studies. This figure indicates that simulation is widely used to quality consistency, and reduce the risk of contamination—three model uncertainty, bottlenecks, and operational dynamics that are essential pillars of a sustainable agricultural system. not easily analyzed directly. This approach is generally used in scenarios involving high variability, such as post-harvest, Implications for Supply Chain Agriculture scheduling, and process capacity. The implementation of supply chain optimization and layout Most interestingly, Lean/Six Sigma was used in only 1.5% of studies, improvements has been proven to strengthen food security by reducing creating a significant gap compared to the other two methods. The post-harvest losses, increasing product flow speed, and minimizing low adoption of Lean/Six Sigma does not necessarily imply its spoilage. In numerous studies, reduced lead time and waste contribute ineffectiveness, but rather reflects the fact that most of the to increased profits for farmers and agro-industry MSMEs. The reviewed studies focused on macrosystem optimization (supply integration of technologies such as AI, digital twins, and IoT sensors chains) rather than micro-quality improvements at the process enables real-time product condition monitoring, demand prediction, level. This finding indicates a significant research opportunity gap: and adaptive response to disruptions such as extreme weather or Lean/Six Sigma implementation in the agro-industry remains transportation delays. This approach creates a more resilient minimal and has the potential to become a valuable research agricultural ecosystem that is responsive to market and environmental opportunity (Nugroho et al., 2023; Sriwana et al., 2022; Triatmo et dynamics(Benjlil et al., 2024; Tian et al., 2021) (R. L. & Kulkarni, 2024). al., 2024). Alignment with Journal Focus & Scope Discussion The research findings are highly relevant to the scope of the journal's Research results show that the application of Industrial Engineering work on sustainable agriculture. (IE) methods, particularly supply chain optimization and process Sustainable Farming & Soil Management simulation (DES/ABM), plays a highly strategic role in achieving sustainable agriculture goals. Supply chain optimization can reduce Process optimization and input planning prevent excessive use of waste, reduce distribution inefficiencies, and ensure smoother fertilizer or water, thus helping maintain soil health and reduce land material flow. This directly impacts resource efficiency, as energy, degradation. labor, and material usage are better controlled, thereby reducing 8 Kurniawan et al. Operational Inefficiencies, Bottlenecks, and Poor Layout in Post-Harvest Processes as Barriers to Agro-Industry Productivity and Profitability: A Systematic Literature Review and Case Study Food Safety & Quality REFERENCE Layout redesign and process control reduce the potential for cross- Abassi, B., Turki, S., Dellagi, S., & Bellamine, I. (2025). Low-carbon contamination, improving food safety standards. manufacturing-remanufacturing supply chain: systematic review and bibliometric analysis. Supply Chain Forum: An International Climate Change & Agriculture Journal, 1–23. https://doi.org/10.1080/16258312.2025.2468633 Process efficiency, waste minimization, and lower energy use Achibat, F. E., Lebkiri, A., Aouane, E. mahjoub, Lougraimzi, H., Berrid, N., contribute to reduced greenhouse gas emissions, thus supporting & Maqboul, A. (2023). ANALYSIS OF THE IMPACT OF SIX SIGMA adaptation to climate change. AND LEAN MANUFACTURING ON THE PERFORMANCE OF COMPANIES. Management Systems in Production Engineering, Agricultural Economics & Policy 31(2). https://doi.org/10.2478/mspe-2023-0020 Amri, S., Kurniawan, R., & Anwar, S. (2025). Optimizing the Classification Increased gains from operational efficiency support the formulation Model for Plant Medicine Supplies Using the Decision Tree of more equitable, inclusive, and sustainable food policies. Algorithm at the Anugrah Tani Shop, Brebes Regency: Inggris. Journal of Artificial Intelligence and Engineering Applications This alignment reinforces that IE-based research is not merely (JAIEA) 4 (2 …. technical but has a direct impact on the sustainability of the food Antony, J., McDermott, O., Powell, D., & Sony, M. (2023). The evolution system holistically. and future of lean Six Sigma 4.0. TQM Journal, 35(4). The Contribution of Industrial Engineering to Modern Agriculture https://doi.org/10.1108/TQM-04-2022-0135 Barbosa Junior, M., Pinheiro, E., Sokulski, C. C., Ramos Huarachi, D. A., & Industrial Engineering offers a systematic framework for de Francisco, A. C. (2022). How to Identify Barriers to the understanding and improving complex agro-industrial systems. Adoption of Sustainable Agriculture? A Study Based on a Multi- Through material flow analysis, process optimization, and digital Criteria Model. Sustainability (Switzerland), 14(20). modeling, IE helps build more efficient, safe, and sustainable https://doi.org/10.3390/su142013277 agricultural systems (Wegren, 2021). The integration of data from Bartol, T. (2023). Smallholders and small-scale agriculture: Mapping and field sensors, predictive models, and supply chain analytics creates visualization of knowledge domains and research trends. Cogent an agricultural ecosystem based on data-driven decision-making. Social Sciences, 9(1). https://doi.org/10.1080/23311886.2022.2161778 The results of this study emphasize the importance of Bendall, E. E., Callear, A. P., Getz, A., Goforth, K., Edwards, D., Monto, A. multidisciplinary collaboration between IE, agronomy, agricultural S., Martin, E. T., & Lauring, A. S. (2023). Rapid transmission and economics, and digital technology in developing innovations in tight bottlenecks constrain the evolution of highly transmissible future food systems (Riaman et al., 2022; Siebrecht, 2020; Tourtelier SARS-CoV-2 variants. Nature Communications, 14(1). et al., 2023). https://doi.org/10.1038/s41467-023-36001-5 Benitez-Alfonso, Y., Soanes, B. K., Zimba, S., Sinanaj, B., German, L., Integration of Lean, Six Sigma, Optimization, and Simulation (DES) Sharma, V., Bohra, A., Kolesnikova, A., Dunn, J. A., Martin, A. C., The main conclusion of these findings is that the integration of Khashi u Rahman, M., Saati-Santamaría, Z., García-Fraile, P., various IE methods results in holistic improvements. Lean and Six Ferreira, E. A., Frazão, L. A., Cowling, W. A., Siddique, K. H. M., Sigma are effective in reducing waste and process variation; supply Pandey, M. K., Farooq, M., … Foyer, C. H. (2023). Enhancing chain optimization increases throughput and profits; Meanwhile, climate change resilience in agricultural crops. In Current Biology simulation provides predictive capabilities and strategy validation (Vol. 33, Issue 23). https://doi.org/10.1016/j.cub.2023.10.028 Benjlil, H., Filali Alaoui, I., Aït Hamza, M., Braimi, A., Oubidari, T., (Putra et al., 2025). This combination creates overall performance Idhmida, A., Ihitassen, A., Tazi, H., El Kherrak, H., Paulitz, T., improvements: reduced waste, increased throughput, stable Fossati-Gaschignard, O., Ferji, Z., Cherifi, K., & Mayad, E. H. quality, and increased profits. However, the low adoption of (2024). Nematodes associated with saffron II: Bioindication for Lean/Six Sigma in the agro-industry indicates both a research gap soil health assessment and impact of agricultural practices. and significant opportunities. Implementation of these methods Applied Soil Ecology, 193. needs to be improved through worker training, development of https://doi.org/10.1016/j.apsoil.2023.105111 local case studies, and policy support that encourages quality Bless, A., Davila, F., & Plant, R. (2023). A genealogy of sustainable management transformation in the agricultural sector (Achibat et agriculture narratives: implications for the transformative al., 2023; de Sousa et al., 2023; Mittal et al., 2023). potential of regenerative agriculture. Agriculture and Human Values, 40(4). https://doi.org/10.1007/s10460-023-10444-4 CONCLUSION Bustomi, A. A., Sholahuddin, A., Hariyanto, T., & Rofik, A. (2023). Anti hoax and media literacy in pesantren in the post-truth era. This study concludes that the main challenges in the post-harvest International Journal of Humanities Technology and Civilization, agro-industry stem from operational inefficiencies, process 1(1), 99–108. bottlenecks, and suboptimal facility layouts, which directly reduce Choi, J. (2023). Target-Aware Feature Bottleneck for Real-Time Visual productivity and profitability. The findings indicate that supply chain Tracking. Applied Sciences (Switzerland), 13(18). optimization and simulation are the most effective IE methods for https://doi.org/10.3390/app131810198 improving performance, although the application of Lean/Six Sigma Complexity. (2024). Retracted: Digital Technology Empowers Grain and layout optimization is still very limited and requires further Supply Chain Optimization Simulation. Complexity, 2024. attention. https://doi.org/10.1155/2024/9845168 Datta, P., Behera, B., & Rahut, D. B. (2024). Assessing the role of agriculture-forestry-livestock nexus in improving farmers’ food To achieve a more sustainable, resilient, and profitable food system, security in South Asia: A systematic literature review. Agricultural the application of Industrial Engineering methods needs to be Systems, 213. https://doi.org/10.1016/j.agsy.2023.103807 expanded through the integration of digital technologies. The use of de Sousa, E. L., Andretti, F. V., & de Castro, M. T. G. (2023). Overview of AI, IoT, and predictive modeling are important directions for future stages of change of lean six sigma programs in organizations research, as they can provide real-time monitoring, process from 2005 to 2021. Gestao e Producao, 30. condition prediction, and adaptive decision-making that support the https://doi.org/10.1590/1806-9649-2023v30e6522 modern transformation of the agro-industry. Duan, J., Zeng, G., Serok, N., Li, D., Lieberthal, E. B., Huang, H. J., & 9 Kurniawan et al. Operational Inefficiencies, Bottlenecks, and Poor Layout in Post-Harvest Processes as Barriers to Agro-Industry Productivity and Profitability: A Systematic Literature Review and Case Study Havlin, S. (2023). Spatiotemporal dynamics of traffic Lean Six Sigma Pada Upaya Peningkatan Kualitas Dan Efisiensi bottlenecks yields an early signal of heavy congestions. Proses Pada Produksi Embossed Signage. Jurnal Mitra Teknik Nature Communications, 14(1). Industri, 3(3), 222–232. https://doi.org/10.1038/s41467-023-43591-7 https://doi.org/10.24912/jmti.v3i3.33044 Fuess, L. T., Braga, A. F. M., Eng, F., Gregoracci, G. B., Saia, F. T., R. L., M., & Kulkarni, N. (2024). Does the financialization of agricultural Zaiat, M., & Lens, P. N. L. (2023). Solving the bottlenecks of commodities impact food security? An empirical investigation. sugarcane vinasse biodigestion: Impacts of temperature and Borsa Istanbul Review, 24(2). substrate exchange on sulfate removal during dark https://doi.org/10.1016/j.bir.2024.01.001 fermentation. Chemical Engineering Journal, 455. Ramanauskas, J., Vienazindienė, M., Rauluškevičienė, J., & Zukovskis, J. https://doi.org/10.1016/j.cej.2022.140965 (2021). Collaboration Perspectives Developing Sustainable Fussone, R., Cannella, S., Dominguez, R., & Framinan, J. M. (2024). Agriculture: The Case of Lithuanian Farmers. European Exploring symbiotic supply chains dynamics. Computers and Countryside, 13(4). https://doi.org/10.2478/euco-2021-0037 Industrial Engineering, 187. Rani, K. S., Shree, S., Islam, Md. Z., Kumar, A., Gupta, R. K., & Verma, R. https://doi.org/10.1016/j.cie.2023.109833 B. (2024). Post-harvest Storage Losses Study in Onion Genotypes. Geenen, C., Raymenants, J., Gorissen, S., Thibaut, J., McVernon, J., International Journal of Plant & Soil Science, 36(4). Lorent, N., & André, E. (2023). Individual level analysis of https://doi.org/10.9734/ijpss/2024/v36i44455 digital proximity tracing for COVID-19 in Belgium highlights Riaman, Sukono, Supian, S., & Ismail, N. (2022). Mapping in the Topic of major bottlenecks. Nature Communications, 14(1). Mathematical Model in Paddy Agricultural Insurance Based on https://doi.org/10.1038/s41467-023-42518-6 Bibliometric Analysis: A Systematic Review Approach. Islami, X. (2023). Lean manufacturing and firms’ financial Computation, 10(4), 50. performance: the role of strategic supplier partnership and https://doi.org/10.3390/computation10040050 information sharing. Benchmarking, 30(9). Romiluyi, O. (2023). (Invited) Successes and Bottlenecks in Scaling CO 2 https://doi.org/10.1108/BIJ-02-2022-0084 and CO Electrolysis for Commercial Demonstration . ECS Meeting Janker, J., Mann, S., & Rist, S. (2018). What is sustainable Abstracts, MA2023-01(26). https://doi.org/10.1149/ma2023- agriculture? Critical analysis of the international political 01261717mtgabs discourse. Sustainability (Switzerland), 10(12). Sachin, Raj, R., Dhiman, S., & Shakya, L. (2022). Nanotechnological https://doi.org/10.3390/su10124707 interventions in sustainable agriculture. Indian Journal of Krimsky, S. (2021). Can glyphosate-based herbicides contribute to Biochemistry and Biophysics, 59(12). sustainable agriculture? Sustainability (Switzerland), 13(4). https://doi.org/10.56042/ijbb.v59i12.67308 https://doi.org/10.3390/su13042337 Santiteerakul, S., Sopadang, A., Tippayawong, K. Y., & Tamvimol, K. Li, L., Feng, L., Manier, H., & Manier, M. A. (2024). Life cycle (2020). The role of smart technology in sustainable agriculture: A optimization for hydrogen supply chain network design. case study of wangree plant factory. Sustainability (Switzerland), International Journal of Hydrogen Energy, 52. 12(11). https://doi.org/10.3390/su12114640 https://doi.org/10.1016/j.ijhydene.2022.03.219 Seymour, M. (2023). Expanding recognition and inclusion of animal-free Masruroh, D. (2023). Peningkatan Kualitas Lembaga Pendidikan organic agriculture in the sustainable agriculture movement. Melalui Pendekatan Lean Six Sigma. Muddib: Jurnal Frontiers in Sustainable Food Systems, 7. Pendidikan Agama Islam, 2(1), 23–28. https://doi.org/10.3389/fsufs.2023.1293261 Mittal, A., Gupta, P., Kumar, V., Al Owad, A., Mahlawat, S., & Singh, Shamkuwar, M., Kadam, V., Arte, P., & Patil, P. (2024). Smart and S. (2023). The performance improvement analysis using Six Sustainable Agriculture. Digital Agricultural Ecosystem, 17–33. Sigma DMAIC methodology: A case study on Indian https://doi.org/10.1002/9781394242962.ch2 manufacturing company. Heliyon, 9(3). Shirazaki, S., Pishvaee, M. S., & Sobati, M. A. (2024). Integrated supply https://doi.org/10.1016/j.heliyon.2023.e14625 chain network design and superstructure optimization problem: Mounika B, Bhagya Laxmi K, Sunanda M, Suneetha B, Neelaveni S, A case study of microalgae biofuel supply chain. Computers and Hari Kumar, V, Anusha, S, Kiran Kumar, S, & Bala Krishna Ch. Chemical Engineering, 180. (2024). Knowledge Evaluation on Weather Forecast and Agro- https://doi.org/10.1016/j.compchemeng.2023.108468 advisory Services to Farmers in Srikakulam District of Andhra Siebrecht, N. (2020). Sustainable agriculture and its implementation gap Pradesh, India. International Journal of Environment and - Overcoming obstacles to implementation. Sustainability Climate Change, 14(3). (Switzerland), 12(9). https://doi.org/10.3390/su12093853 https://doi.org/10.9734/ijecc/2024/v14i34042 Singh, A., & Ravi, P. (2023). Lean six-sigma (LSS) applications in Nugroho, E. D., Rahayu, D. A., Ainiyah, R., Fathurrohman, A., Ahwan, hospitals: a decade (2011–2020) bibliometric analysis. Z., Dayat, M., & ... (2023). Diversity of bird agroforestry International Journal of Productivity and Performance species in Sapen Nusantara Conservation Park of Mount Management, 72(8). https://doi.org/10.1108/IJPPM-07-2021- Arjuno, Pasuruan. Edubiotik: Jurnal Pendidikan, Biologi Dan 0432 Terapan, 8(1), 17–28. Singh, N., & Singh, M. (2025). Traditional embroidery revival for Nyamweru, J. C., Ndayitwayeko, W. M., Kessler, A., & Biemans, H. sustainability: a systematic literature review and bibliometric (2024). Fostering sustainable agriculture in Burundi: which analysis. Discover Sustainability, 6(1). competencies for change-agents should vocational https://doi.org/10.1007/s43621-025-00944-0 agriculture education prioritize? Journal of Agricultural Soosay, C. (2024). Coordination in supply chains. In The Palgrave Education and Extension, 30(3). Handbook of Supply Chain Management. https://doi.org/10.1080/1389224X.2023.2205395 https://doi.org/10.1007/978-3-031-19884-7_57 Pérez-Gosende, P., Mula, J., & Diaz-Madroñero, M. (2023). A Sriwana, I. K., Santosa, B., Tripiawan, W., & Maulanisa, N. F. (2022). conceptual framework for multi-objective facility layout ANALISIS NILAI TAMBAH UNTUK MENINGKATKAN planning by a bottom-up approach. International Journal of KEBERLANJUTAN RANTAI PASOK AGROINDUSTRI KOPI Production Management and Engineering, 11(1). MENGGUNAKAN HAYAMI. JISI: Jurnal Integrasi Sistem Industri, https://doi.org/10.4995/ijpme.2023.19006 9(2). https://doi.org/10.24853/jisi.9.2.113-122 Prayitno, G., Dinanti, D., Hidayana, I. I., & Nugraha, A. T. (2021). Suharto, D. G., Wulandari, S., & Rosyadi, S. (2024). Post-Reform Place attachment and agricultural land conversion for Democracy in Indonesia; A Systematic Literature Review and sustainable agriculture in Indonesia. Heliyon, 7(7). Bibliometric Analysis. Pakistan Journal of Life and Social Sciences https://doi.org/10.1016/j.heliyon.2021.e07546 (PJLSS), 22(1). https://doi.org/10.57239/pjlss-2024-22.1.00301 Putra, Y. W., Kristina, H. J., & Saryatmo, M. A. (2025). Penerapan Supply Chain Performance Measurement: Systematic Literature Review 10 Kurniawan et al. Operational Inefficiencies, Bottlenecks, and Poor Layout in Post-Harvest Processes as Barriers to Agro-Industry Productivity and Profitability: A Systematic Literature Review and Case Study \& Bibliometric Presentation. (2025). European Inovasi Dan Pengembangan Hasil Pengabdian Masyarakat, 2, Economic Letters. https://doi.org/10.52783/eel.v15i2.2941 228–246. Tian, Z., Wang, J. W., Li, J., & Han, B. (2021). Designing future crops: Tutuhatunewa, A. (2021). ANALISIS KINERJA RANTAI PASOK challenges and strategies for sustainable agriculture. Plant AGROINDUSTRI APEL. ALE Proceeding, 1. Journal, 105(5). https://doi.org/10.1111/tpj.15107 https://doi.org/10.30598/ale.1.2018.136-143 Tiwari, H., Singh, P. K., Naresh, R. K., M., M. S. I., S., M., Islam, A., Utama, D. M., & Abirfatin, M. (2023). Sustainable Lean Six-sigma: A new Kumar, S., Singh, K. V., Pandey, A. K., & Shukla, A. (2023). framework for improve sustainable manufacturing performance. Millets Based Integrated Farming System for Food and Cleaner Engineering and Technology, 17. Nutritional Security, Constraints and Agro-Diversification https://doi.org/10.1016/j.clet.2023.100700 Strategies to Fight Global Hidden Hunger: A Review. Wegren, S. K. (2021). Prospects for Sustainable Agriculture in Russia. International Journal of Plant & Soil Science, 35(19). European Countryside, 13(1). https://doi.org/10.2478/euco- https://doi.org/10.9734/ijpss/2023/v35i193593 2021-0011 Tombido, L., & Baihaqi, I. (2024). Perspectives on the bullwhip effect Wieliczko, B., & Floriańczyk, Z. (2022). Priorities for Research on in supply chains. In The Palgrave Handbook of Supply Chain Sustainable Agriculture: The Case of Poland. Energies, 15(1). Management. https://doi.org/10.1007/978-3-031-19884- https://doi.org/10.3390/en15010257 7_31 Yang, C., Ji, X., Cheng, C., Liao, S., Obuobi, B., & Zhang, Y. (2024). Digital Tourtelier, C., Gorman, M., & Tracy, S. (2023). Influence of gender on economy empowers sustainable agriculture: Implications for the development of sustainable agriculture in France. Journal farmers’ adoption of ecological agricultural technologies. of Rural Studies, 101. Ecological Indicators, 159. https://doi.org/10.1016/j.jrurstud.2023.103068 https://doi.org/10.1016/j.ecolind.2024.111723 Triatmo, A. W., Husen, F., & Triana, U. (2024). Harvesting Hope: Islamic and Catholic Thought Nurturing Agropreneurial Generations for Sustainable Food Security in Indonesia. Jurnal . 11