A data-driven decision support system with smart packaging in grocery store supply chains during outbreaks

Kabadurmuş, Özgür; Kayıkçı, Yaşanur; Demir, Sercan; Koc, Basar

doi:10.1016/j.seps.2022.101417

Cited by 19 publications

(8 citation statements)

References 93 publications

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“…Missing products in the packaging Machine vision defect [33] Shape template fitting algorithm [33] D. Error due to product type D/1. Perishable products TTI (time and temperature indicator) [15,[34][35][36][37] Intelligent packaging [28,34,37], packaging with good tightness and closure properties [35], D/2. Weight problem Weight measurement [38,39] Electronic length measuring (LMD) increase sensitivity, replacement [38] Results of the Systematic Literature Research…”

Section: Fault Group Fault Type Methods Of Identification/recognition...mentioning

confidence: 99%

An Innovative Framework for Quality Assurance in Logistics Packaging

Matyi,

Tamás

2023

Logistics

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Background: As a result of the effort to satisfy unique customer needs, the complexity of production and service processes is constantly increasing. In this context, the requirements for packaging systems, essential for carrying out logistic tasks, are also diversifying, and various quality defects and problems are appearing more and more frequently. Methods: The research used an inductive method. While practical problems were being solved, the need for developing the concept of a packaging inspection framework arose, the lack of which was also supported by a systematic literature review. Results: During the concept’s development, packaging errors found in the literature were identified and methods for detection and solution were systematized. A general framework was developed to identify and eliminate these errors. The applicability of the developed method was demonstrated through a complex case study, and its accuracy was verified. Conclusions: This research is important because, instead of using “island” solutions, in the future, companies will have a general framework available to them for handling all packaging-related errors according to a predefined methodology. This can reduce the time required for problem-solving and increase efficiency, which is a significant competitive factor.

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Section: Fault Group Fault Type Methods Of Identification/recognition...mentioning

confidence: 99%

An Innovative Framework for Quality Assurance in Logistics Packaging

Matyi,

Tamás

2023

Logistics

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“…[31] proposes a resilient healthcare SC network while minimizing the design and operating, environmental, and social costs. Several papers have highlighted the use of intelligent technologies in supply chain planning and execution under disruptions (e.g., [32][33][34][35]).…”

Section: Background and Brief Literature Reviewmentioning

confidence: 99%

Optimizing Process-Improvement Efforts for Supply Chain Operations under Disruptions: New Structural Results

Berk,

Ayas,

Ülkü

2023

Sustainability

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Rampant disruptions have probed the fragility of supply chains: Renewed perspectives and comprehensive operational models are needed to enhance resiliency and sustainability in business. This paper proposes a new inventory management model that explicitly integrates process improvement efforts to improve supply chain sustainability through the better use of capital (materials, assets, and technology) and labor (workforce and know-how). Under a desired service-level constraint, we study reducing setup (fixed) costs when they are expressed in terms of economic production functions of two (input) decision variables: the level of capital (e.g., process change, and technology investments) and the level of labor required. This research is motivated by lean manufacturing practices, which rely on shaping the operating environment and operating optimally within that business environment. Based on mathematical modeling and analysis, we provide closed-form optimality expressions and structural results that lend themselves to decision insights. In particular, we provide, along with illustrative numerical examples, results on the sensitivity of setup-reduction efforts to demand rates, variability, and explicit expressions for determining the required labor and capital resources. A generalization of the model for carbon emissions is also presented.

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“…Ten, in the food packaging and warehousing stage, smart packaging and anti-counterfeiting technologies are required. Tese technologies include contactless smart packaging [24], smart label and ledger using RFID, IoT, and BC [25], and fnally automated warehouse logistics that require the integration of RFID, big data, and cyber-physical system [26,27]. Finally, in the food transportation and logistics stage, cold chain optimization and on-time delivery are very important issues that need to be addressed efciently and efectively [28,29].…”

Section: Related Workmentioning

confidence: 99%

Modelling and Forecasting Fresh Agro-Food Commodity Consumption Per Capita in Malaysia Using Machine Learning

Alfred

Leikson

Boniface

et al. 2022

Mobile Information Systems

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This study focuses on identifying and analyzing spending trend profiles and developing the per capita consumption models to forecast the fresh agro-food per capita consumption in Malaysia. Previous published works have looked at statistical and machine learning methods to forecast the demand of agro-food such as ARIMA and SVM methods. However, ordinary least squares (OLS) and neural network (NN) methods have shown better results in modelling time series data. For that reason, the primary objective of this study is to model and forecast the consumption per capita (PCC) of several selected fresh agro-food commodities in Malaysia using the OLS and NN methods. The secondary objectives of the paper include investigating the performance of OLS against NNs with three different topologies, discussing the correlation between Malaysia GDP per capita and the agro-food commodity PCC, and finally assessing whether the PCC data are increasing over time or decreasing over time and whether the trend in either direction is statistically significant by using the Mann–Kendall statistical test. Based on the results of the agro-food consumption per capita (PCC) forecasting, several critical agro-food commodities are also identified in this work. The material of the study consists of the per capita consumption of thirty-three (33) agro-food items that can be categorized into rice, livestock, vegetables, fisheries, and fruits, total gross domestic product (GDP) per capita, and the total population of Malaysia between 2010 and 2017. Based on the results obtained, the neural network ( N N T 1 ) model was found to produce the lowest total MSE of 17.95, for all 33 fresh agro-food investigated in this study. Several agro-food commodities have been identified as having significant positive (e.g., rice, spinach, cabbage, celery cabbage, eggplant, cucumber, poultry, lamb, squid, tuna, star fruit, jackfruit, durian, sweet corn, and coconut) or negative (e.g., pork, mackerel, papaya, guava, mangosteen, pineapple, banana, rambutan, and watermelon) trends using the Mann–Kendall trend test. This study also demonstrated that the production of critical agro-food commodities (e.g., rice, chili, cabbage, celery cabbage, poultry (chicken/duck), beef, lamb, crab, mango, and coconut) should be improved to ensure self-sufficiency ratios (SSRs) of more than 100% to accommodate the increased projected consumption in Malaysia by the year 2025. This paper concludes that neural network methods produce better prediction, and future works include forecasting agro-food demand based on other independent variables such as weather conditions, disease outbreak, and stock market trends. There is a need to explore further the capability of ensemble models or hybrid models based on deep learning methods using multi-source data, as these have been shown to improve the performance of the base model. With these ensemble models combined with multi-source data, a more comprehensive analysis of the PCC can be obtained.

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A data-driven decision support system with smart packaging in grocery store supply chains during outbreaks

Cited by 19 publications

References 93 publications

An Innovative Framework for Quality Assurance in Logistics Packaging

An Innovative Framework for Quality Assurance in Logistics Packaging

Optimizing Process-Improvement Efforts for Supply Chain Operations under Disruptions: New Structural Results

Modelling and Forecasting Fresh Agro-Food Commodity Consumption Per Capita in Malaysia Using Machine Learning

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