Selecting Appropriate Type of Package with Machine Learning Models in Logistic Companies

There are many factors for Logistics Companies to be successful and financially profitable. These factors can be grouped under two main headings, namely, the efficiency values of the processes and the costs. One of the most important costs is the cost of packaging and shifting. When the packaged orders are delivered to the cargo companies, the packaging and shifting costs are incurred in a way that is directly proportional to the volume value of the order. In logistics companies, these costs increase as a result of placing the order in a package with a larger volume value instead of the appropriate package type. Solving the pallet loading or container loading problems with mathematical models, the packaging personnel's output of the mathematical model for each order, and the employee's placing these products in the package according to the results of the model significantly reduce the efficiency value of the processes. For this reason, in this article, it is aimed to examine and learn the historical packaging data with different machine learning models and to inform the packaging personnel about which package type should be used for the current order

Determination of Association Rules with Market Basket Analysis: Application in the Retail Sector

Market basket analysis is the process of extracting purchasing trends from records in company databases, taking into account the products that customers buy in a single transaction. In this study, a market basket analysis was conducted on a five-and-a-half year data of a large hardware company operating in the retail sector, and related product categories were identified. In determining the association rules, both the Apriori and FP-Growth algorithms were run separately and their usefulness in such a set of data was compared. In addition, the data set was divided into Data Set-1 and Data Set-2 so that the consistency of the rules was discussed by comparing the correctness of rules extracted from the first data set with rules derived from the second data set containing consecutive timed data

Causal Loop Analysis and Improvement Areas of AS 9100 Aerospace Quality Management System Implementation in Turkish Aerospace and Defence Industry Supply Chain

Abstract Implementing Aerospace Quality Management system in an organization in theory will achieve on-time delivery, product conformity and acceptable price, which will result in Customer Satisfaction. However, system dynamics has to be considered for all systems, which determines and analyses feedback effects of components in the system. This study investigates these dynamic effects arising from various aspects that organizations are facing during implementation of the aerospace quality management system in Turkish defence and aerospace industry. Results achieved, and information collected through site activity is used to develop causal loop diagram. Requirements of the AS 9100 standard are interpreted to propose improvement opportunities. Causal Loop diagram is validated by using a scientific method

Digital transformation in the defense industry: A maturity model combining SF-AHP and SF-TODIM approaches

As an inevitable process, digitalization has become a priority for many companies. The measurement of digital maturity is the first step toward adequately executing this. Although digital maturity models (DMM) have been developed for different sectors in the literature, such studies in the defense industry are lacking due to sector-specific dynamics. This study aims to close this gap and proposes a digital maturity model specific to the defense industry. In this study, a novel model was developed that combines the SF-AHP and SF-TODIM methods due to the uncertainty and hesitancy contained in the evaluation. The validity of the presented novel model has been demonstrated in a prominent defense company in Turkey. According to the results, the most notable digital maturity dimensions are the evaluation of opportunities and alignment with stakeholders. In addition, the model indicates that the company owns the required soft skills, such as leadership, organizational culture, and strategic determination for digital transformation (DT). On the other hand, essential hard skills such as technology and operational competencies are yet to be improved. Lastly, sensitivity and comparison analyses are conducted to validate and verify the obtained results’ stability and robustness

Optimization of reverse logistics network of End of Life Vehicles under fuzzy supply: A case study for Istanbul Metropolitan Area

Recycling aims at preventing rapid depletion of natural resources while transforming produced waste into value for economy. However, this process becomes a major challenge in automotive industry, which requires cooperative engagement of multiple players within a complex supply chain. In line with the essence of the topic, government agencies around the world issue directives drawing regulatory frameworks for designing recycling operations comprising various activities such as collection of end-of-life vehicles (ELVs), recovery of reusable components, shredding ELV's body, recycling valuable materials and disposal of the hazardous waste. In general, the amount of returned product in a reverse logistics network is highly uncertain, and the ELV market in Turkey is no exception to this. For that purpose, this study aims developing a fuzzy mixed integer location-allocation model for reverse logistic network of ELVs conforming to the existing directives in Turkey. Accordingly, this study uses a novel approach and assumes that ELV supply in the network is uncertain. The merit of the proposed mathematical model is proved on a real world scenario addressing the reverse logistics design problem for ELVs generated in metropolitan area of Istanbul. The network generated specifies that recycling process is not profitable under the existing circumstances with the given level of supplied ELV and the returned product records per capita in Istanbul are far beyond the EU averages. Consequently, sensitivity analyses question the reliability of the obtained results.WOS:0004593583000882-s2.0-8506018772

Waste Biomass Based Energy Supply Chain Network Design

Reducing dependence on fossil fuels, alleviating environmental impacts and ensuring sustainable economic growth are among the most promising aspects of utilizing renewable energy resources. Biomass is a major renewable energy resource that has the potential for creating sustainable energy systems that are critical in terms of social welfare. Utilization of biomass for bioenergy production is an efficient alternative for meeting rising energy demands, reducing greenhouse gas emissions and thus alleviating climate change. A supply chain for such an energy source is crucial for assisting deliverance of a competitive end product to end-user markets. Considering the existing constraints, a mixed integer linear programming (MILP) model for waste biomass based supply chain was proposed in this study for economic performance optimization. Performance of the proposed modelling approach was demonstrated with a real life application study realized in İstanbul. Moreover, sensitivity analyses were conducted which would serve as a foresight for efficient management of the supply chain as a whol

Sustainability assessment of biomass-based energy supply chain using multi-objective optimization model

In recent years, population growth and lifestyle changes have led to an increase in energy consumption worldwide. Providing energy from fossil fuels has negative consequences, such as energy supply constraints and overall greenhouse gas emissions. As the world continues to evolve, reducing dependence on fossil fuels and finding alternative energy sources becomes increasingly urgent. Renewable energy sources are the best way for all countries to reduce reliance on fossil fuels while reducing pollution. Biomass as a renewable energy source is an alternative energy source that can meet energy needs and contribute to global warming and climate change reduction. Among the many renewable energy options, biomass energy has found a wide range of application areas due to its resource diversity and easy availability from various sources all year round. The supply assurance of such energy sources is based on a sustainable and effective supply chain. Simultaneous improvement of the biomass-based supply chain's economic, environmental and social performance is a key factor for optimum network design. This study has suggested a multi-objective goal programming (MOGP) model to optimize a multi-stage biomass-based sustainable renewable energy supply chain network design. The proposed MOGP model represents decisions regarding the optimal number, locations, size of processing facilities and warehouses, and amounts of biomass and final products transported between the locations. The proposed model has been applied to a real-world case study in Istanbul. In addition, sensitivity analysis has been conducted to analyze the effects of biomass availability, processing capacity, storage capacity, electricity generation capacity, and the weight of the goals on the solutions. To realize sensitivity analysis related to the importance of goals, for the first time in the literature, this study employed a spherical fuzzy set-based analytic hierarchy method to determine the weights of goals

Elektrikli ve elektronik atıklar için tersine lojistik ağ tasarımı: İstanbul örneği

Bu çalışmada, Çevre ve Şehircilik Bakanlığı AEEE Kontrolü Yönetmeliği’ne göre İstanbul ilinde toplanması gereken Atık Elektrikli ve Elektronik Eşyalar (AEEE) için çok amaçlı karma tamsayılı programlama modeli oluşturulmuştur. Model, sürdürülebilirlik kavramının üç temel hedefinden (ekonomik, çevresel ve sosyal) yola çıkarak, yönetmeliğin gerektirdikleri ve sorumlu paydaşların yükümlülükleri baz alınarak tasarlanmıştır. Fakat yönetmeliğe rağmen yasa dışı olarak AEEE toplayan ve ayrıştıran hurdacılar mevcuttur. Bu tip atıklar insan sağlığına oldukça zararlı olabildiğinden, gerekli ekipmanları olmayan hurdacılar için risk oluşturmaktadır. Buradan yola çıkarak modelde sosyal amaç, AEEE toplayan hurdacıların, yapılacak devlet yatırımı ile istihdam edilerek sağlıklarının garanti altına alınması ve sosyal statülerinin arttırılmasıdır. Modelin diğer amacı da tersine lojistik aktivitelerin çevresel etkilerinin ve maliyetinin enküçüklenmesidir. Önerilen model epsilon kısıt yöntemi ile çözülmüş ve açılacak elektronik atık işleme tesislerine ve yatırım yapılarak AEEE geri kazanım sistemine dahil edilecek hurda depolarına karar verilmiştir

Value Stream Mapping in Lean Production and an Application in the Textile Sector

With the effect of increasing competition due to globalization, in many sectors, global brands have shifted production lines to countries with low labor costs in order to reduce their costs in the last two decades. The way to survive in the market for companies that want to continue production in their own center instead of producing in other countries is by way of reaching competitive production cost levels. Under these circumstances, firms are focusing on the idea of reducing their costs by focusing on their production systems and removing all activities that do not produce value and consume resources. One of the ideas that emerged in recent years and which will help the firm in this matter is the philosophy of Lean Manufacturing