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The impact of the COVID-19 pandemic on online grocery supply chain management: a case study in Istanbul
(Gazi Üniversitesi, 2024-03) Javadi, Sonya; Keten, Olcay; Özer, Ali İhsan; Alkan, Remziye Zeynep
The COVID-19 pandemic has already crippled normal life all over the world. Its negative impact not only changed the human health system tragically but also disrupted the global economic system. One negative result was ended up in the global food supply chain. As the lockdown times have suspended the manufacturing and logistic activities, therefore, the customers have experienced unimaginable chaos in the shopping markets. Moreover, the purchasing habit of the consumers has remarkably changed compared to pre-pandemic. To meet this new demand pattern, many grocery retailers have tried to adapt to the new normal. While before COVID-19 offline grocery purchasing was popular, after the pandemic, online service got tremendous attention in market. In this study, online grocery supply chain management during the COVID-19 in Istanbul is considered. The aim is to find out how online grocery companies will serve more efficiently during the pandemics and which factors have more effect on the customer’s satisfaction. To do so, first, three popular grocery retailers in Istanbul were selected. Then, a related survey was designed to understand the consumer experience as doing online grocery shopping in COVID-19. Unsurprisingly, a result shows that 60% of the respondents did online shopping every 3-4 days in one week, and the delivery time is the most important factor for the customers. Then, the SWOT analyses were performed accordingly, and the related strategies were summarized. Finally, several managerial implications were given to may improve the company’s online services in COVID-19 and post COVID-19 in Turkey.
Sustainability via extended warranty contracts: design for a consumer electronics retailer
(MDPI, 2024-01) Aksezer, Sezgin Çağlar
Warranty is one of the most important attributes of any product, from both manufacturer and consumer points of view. Although the retailers connect manufacturers to customers by selling goods, traditionally, they have isolated themselves from warranty-related matters such as customer complaints and maintenance costs. However, recent trends in consumer behavior toward extended warranty contracts have changed this approach. While retailers have started to generate considerable revenue from the sale of these contracts, sustainability is also achieved by longer product life cycles. This study analyzed the failure behavior of different classes of cell phone products and their related costs through a chain of consumer electronics retailer operating in Türkiye. To compete on pricing and customer service, a novel policy was designed for the retailer to honor the contracts in house rather than underwriting to a third party insurer as the industry standard. The maintenance records of 328 previous failures were analyzed to plot a failure model. Failure mode and effects analysis was carried out to identify failure classes and the respective costs for extended warranty design for cell phones. The expected warranty costs for coverage of the third, fourth, and fifth years of operation were determined. The results show that the retailer may achieve the same level of profit by increasing customer satisfaction along with the sustainability of the product through repair actions.
Cargo company recommendation study based on probabilistic linguistic term set
(Bitlis Eren Üniversitesi, 2023-12-28) Çoban, Veysel; Aksezer, Sezgin Çağlar
The global economic structure is the main reason for changes in consumption habits and consumer behavior. Developing information technologies direct producers and consumers to e-commerce. Cargo services are an important link in the chain in the fast and effective operation of e-commerce. The growth in e-commerce has a driving force in the development of cargo services and cargo companies. Cargo companies can survive in global competition by being preferred by customers and increasing their number of customers. The change in the number of customers occurs by communicating the satisfaction or dissatisfaction with the cargo company to potential customers. This study deals with the preference levels of cargo companies serving in Turkey according to customer suggestions. The data obtained from the survey evaluations are processed and recommendation ranking calculations are made for cargo companies. Probabilistic Linguistic Term Sets (PLTS) are used to eliminate customer ambiguities in survey evaluations. Alternative cargo company recommendations are ranked based on the customers' past service experiences from cargo companies. Aras Cargo, MNG Cargo, PTT Cargo, Surat Cargo, UPS Cargo, Yurtiçi Cargo companies are evaluated according to price, personnel, speed, reliability and network attributes. The maximum deviation optimization method based on the Lagrangian function is used to calculate the weights of the cargo companies' attributes. The probabilistic linguistic cosine similarity method compares cargo companies pairwise under attributes and a similarity matrix is obtained for six cargo companies. The similarity matrix defines the alternative cargo company recommendation ranking based on customers' past experiences. UPS, SURAT and MNG cargo companies stand out as the most prioritized companies according to the evaluation results. The effects of attribute weights are observed by designing six different scenarios and it is observed that the differentiating attribute weights affect the recommendation ranking. Spearman correlation coefficient evaluation based on recommendation rankings indicates a high relationship between attributes.
On computing the multivariate poisson probability distribution
(Springer, 2023-06-20) Çekyay, Bora; Frenk, Johannes Bartholomeus Gerardus; Javadi, Sonya
Within the theory of non-negative integer valued multivariate infinitely divisible distributions, the multivariate Poisson distribution plays a key role. As in the univariate case, any non-negative integer valued infinitely divisible multivariate distribution can be approximated by a multivariate distribution belonging to the compound Poisson family. The multivariate Poisson distribution is an important member of this family. In recent years, the multivariate Poisson distributions also has gained practical importance, since they serve as models to describe counting data having a positive covariance structure. However, due to the computational complexity of computing the multivariate Poisson probability mass function (pmf) and its corresponding cumulative distribution function (cdf), their use within these counting models is limited. Since most of the theoretical properties of the multivariate Poisson probability distribution seem already to be known, the main focus of this paper is on proposing more efficient algorithms to compute this pmf. Using a well known property of a Poisson multivariate distributed random vector, we propose in this paper a direct approach to calculate this pmf based on finding all solutions of a system of linear Diophantine equations. This new approach complements an already existing procedure depending on the use of recurrence relations existing for the pmf. We compare our new approach with this already existing approach applied to a slightly different set of recurrence relations which are easier to evaluate. A proof of this new set of recurrence relations is also given. As a result, several algorithms are proposed where some of them are based on the new approach and some use the recurrence relations. To test these algorithms, we provide an extensive analysis in the computational section. Based on the experiments in this section, we conclude that the approach finding all solutions of a set of linear Diophantine equations is computationally more efficient than the approach using the recurrence relations to evaluate the pmf of a multivariate Poisson distributed random vector.
Elections and stock market returns: evidence from Borsa Istanbul
(Marmara Üniversitesi, 2023-06-22) Kayaçetin, Nuri Volkan
Stock prices may display predictable patterns around major political events, particularly in emerging market economies where political risk is a key component of asset risk premiums. One distinct event that would be expected to result in an abrupt increase in political risk is elections. Motivated by this notion, we study the returns for a set of indicator and sectoral indices of Borsa Istanbul stocks and the U.S. Dollar–Turkish Lira exchange rate around political elections held in Turkey over 2001–2020. Our tests reveal an accumulation of economically and statistically significant positive abnormal returns for all Borsa Istanbul stock indices and negative abnormal returns for the U.S. Dollar–Turkish Lira exchange rate over a window that starts as early as a month before the election date and extends for two weeks into the post-election period, with the effect being particularly strong in the week that immediately follows the election. Consistent with a political risk-based story, volatility of index returns starts increasing over the same period and plateaus out at a level that is roughly one-and-a-half to two-folds greater than its pre-election period average.
Maintenance policy analysis of the regenerative air heater system using factored POMDPs
(Elsevier Ltd, 2022-03) Kıvanç, İpek; Özgür Ünlüakın, Demet; Bilgiç, Taner
Maintenance optimization of multi-component systems is a difficult problem. Partially Observable Markov Decision Processes (POMDPs) are powerful tools for such problems under uncertainty in stochastic environments. In this study, the main POMDP solution approaches and solvers are surveyed. Then, based on experimental models with different complexities in the size of the system space, selected POMDP solvers using different representation patterns for modeling and different procedures for updating the value function while solving are compared. Furthermore, to show that factored representations are advantageous in modeling and solving the maintenance problem of multi-component systems where there exist also stochastic dependencies among the components, the maintenance problem of the one-line regenerative air heater system available in thermal power plants is modeled and solved with factored POMDPs. In-depth sensitivity analyses are performed on the obtained policy. The results show that factored POMDPs enable compact modeling, efficient policy generation and practical policy analysis for the tackled problem. Furthermore, they also motivate the use of factored POMDPs in the generation and analysis of maintenance policies for similar multi-component systems.
Challenges in the CO2 emissions of the Turkish power sector: Evidence from a two-level decomposition approach
(Elsevier Ltd, 2021-06) Işık, Mine; Ari, İzzet; Sarıca, Kemal
Decarbonization of the energy system is urgent to avert the disruptions in the climate. Considering its share, the low carbon transition of the power sector is pivotal. Growing electricity demand poses unique challenges for Turkey to enact deep decarbonization. It is vital to uncover the contributing causes of emissions to provide strategic oversight for carbon management activities. This study investigates key drivers of CO2 emissions from the power sector using the Logarithmic Mean Divisia Index decomposition method. While efficiency improvement contributes to sustainable yet minor mitigation, changes in the fossil-fuel share indicate a cycling but significant overall impact.
Evaluation of proactive maintenance policies on a stochastically dependent hidden multi-component system using DBNs
(Elsevier Ltd, 2021-07) Özgür Ünlüakın, Demet; Türkali, Busenur
In complex systems with stochastically dependent components which are not observed directly, determining an effective maintenance policy is a difficult task. In this paper, a dynamic Bayesian network based maintenance decision framework is proposed to evaluate proactive maintenance policies for such systems. Two preventive and one predictive maintenance strategies from a cost perspective are designed for multi-component dependable systems which aim to reduce maintenance cost while increasing system reliability at the same time. Tabu procedure is employed to avoid repetitive similar actions. The performances of the policies are compared with a reactive maintenance strategy and also with each other using different strategy parameters on a real life system confronted in thermal power plants for six different scenarios. The scenarios are designed considering different structures of system dependability and reactive cost. The results show that the threshold based maintenance which is the predictive strategy gives the minimum cost and maintenance number in almost all scenarios.
Scheduling and simulation of maritime traffic in congested waterways: An application to the Strait of Istanbul
(Cambridge University Press, 2021-05) Özlem, Şirin; Or, İlhan; Altan, Yiǧit Can
The aim of this study is to develop a simulation model which is capable of mimicking actual vessel arrival patterns and vessel entrance decisions (which are made based on expert opinions generally) on congested, narrow waterways. The model is tested on the transit traffic pattern in the Strait of Istanbul. Based on a heuristic scheduling algorithm, this model decides entrance times and vessel types on the strait. The model, with different policies for day and night traffic, is run for a period of seven years with 20 replications for each year. The performance measures of the model are: average interarrival times, number of vessels passed and entrance times for each successive vessel pair in both traffic directions. The model results are congruent with the actual results of performance measures. Therefore, it may be deduced that the proposed algorithm can be a guide for operators regarding scheduling decisions in congested, narrow waterways.
Cost-effective fault diagnosis of a multi-component dynamic system under corrective maintenance
(Elsevier Ltd, 2021-04) Özgür Ünlüakın, Demet; Türkali, Busenur; Aksezer, Sezgin Çağlar
Maintenance planning and execution are challenging tasks for every system with complex structure. Interdependent nature of the components that builds up the system may have significant effect on system integrity. While preventive maintenance actions can be carried out in a more planned fashion, corrective actions are more time sensitive as they directly affect the availability of the system. This study proposes a cost-effective dynamic Bayesian network modeling scheme to be used in the planning of corrective maintenance actions on systems having hidden components which have stochastic and structural dependencies. In such context, the regenerative air heater system which is a key element of a power plant is taken into consideration. The proposed maintenance framework offers several methods, each aiming to balance the cost with the probability effect using a normalization procedure. The methodologies are extensively simulated for sensitivity analysis under various downtime cost values. Fault effect methods with worst state probability efficiency measures give the least total cost for all downtime cost values and their distinction becomes significant as this value increases. Further statistical analysis concludes that considerable gains on maintenance costs can be achieved by the proposed approach.
Türk hazır giyim sanayi için veri madenciliği tabanlı bir kalıcı indirim yönetim sistemi prototipi
Driving forces of Turkey's transportation sector CO2 emissions: An LMDI approach
(Elsevier Ltd, 2020-08-01) Işık, Mine; Sarıca, Kemal; Ari, İzzet
The transportation sector is one of the main contributors to global greenhouse gas (GHG) emissions. As the efforts towards emission mitigation increase, the expectation from the sector arises equally. In this analysis, the transportation sector of Turkey is studied to shed light on the future based on historical realizations. In this respect, the Logarithmic Mean Divisia Index (LMDI) method is used to assess and reveal the influential factors on CO2 emissions in the sector between 2000 and 2017. The emission intensity of the sector and fuel switching shows promising trends from 2000 through 2010, whereas growing preference for SUVs challenges emission reductions between 2010 and 2017. The results indicate that i) The transportation sector CO2 emissions are mainly driven upwards by economic growth, followed by population and emission intensity effects from 2000 to 2017 ii) The overall impact of transportation intensity shows significant reduction potential iii) Fuel switching incentives and fleet efficiency have a positive effect on emission mitigation from 2000 through 2010. However, this gain is reduced due to the rising popularity of SUVs in the rest of the analysis period. In this respect, CO2 emission mitigation in the transportation sector necessitates 1) careful planning of demand management for freight transportation including master designs production/manufacturing sites, material flows, and demand points coupled with economic activities 2) passenger transportation measures to reduce passenger car travel including zoning for public transit corridors, improved public transportation system 3) well-structured incentives on energy-efficient cars and clean energy technologies such as electric vehicles to convince individuals. Analysis can be generalized on a global scale due to the similar dynamics inherent in the sector.
A stochastic risk-averse framework for blood donation appointment scheduling under uncertain donor arrivals
(Springer, 2020-12) Yalçındağ, Semih; Baş Güre, Seda; Carello, Giuliana; Lanzarone, Ettore
Blood is a key resource in all health care systems, usually drawn from voluntary donors. We focus on the operations management in blood collection centers, which is a key step to guarantee an adequate blood supply and a good quality of service to donors, by addressing the so-called Blood Donation Appointment Scheduling problem. Its goal is to employ appointment scheduling to balance the production of blood units between days, in order to provide a reasonably constant supply to transfusion centers and hospitals, and reduce non-alignments between physicians' working times and donor arrivals at the collection center. We consider a two-phase solution framework taken from the literature, in which a deterministic linear programming model preallocates time slots to different blood types and a prioritization policy assigns the preallocated slots to the donors when they make a reservation. However, the problem is stochastic in nature and requires consideration of the uncertain arrivals of non-booked donors. In this work, to include the uncertain arrivals, we propose three stochastic counterparts of the preallocation model based on a risk-neutral objective and two risk-averse objectives, respectively, where the Conditional Value-at-Risk is considered as the risk measure in the last two methods. The resulting stochastic frameworks have been tested considering the historical data of one of the largest Italian collection centers, the Milan Department of the "Associazione Volontari Italiani Sangue" (AVIS). Results show the effectiveness of the stochastic models, especially the mean-risk one, and the need to include the uncertainty of arrivals in order to better balance the production of blood units.
A DBN based reactive maintenance model for a complex system in thermal power plants
(Elsevier Sci Ltd, 2019-10) Özgür Ünlüakın, Demet; Türkali, Busenur; Karacaörenli, Ayşe; Aksezer, Sezgin Çağlar
Thermal power plants consist of several complex systems having many interacting hidden components. Any unexpected failure may lead to prolonged downtime and serious lost profits. Therefore, implementing an effective maintenance policy is crucial for this sector. Although preventive maintenance has become a more popular strategy, it does not completely prevent the need for corrective maintenance. Our aim in this study is to tackle the corrective maintenance implementation problem of a multi-component partially observable dynamic system based on a regenerative air heater in a thermal power plant. We propose eight methods having different efficiency measures with respect to time, effect and probability criteria to minimize the total number of maintenance activities in a given planning horizon. Performances of these methods are evaluated under corrective maintenance strategy using dynamic Bayesian networks. The results show that fault effect methods with best working state probability measure perform better than the others considering both the total amount of maintenance activities and also the solution time. We also point out how the methods can be implemented in real-life and how the results can be used for requirements planning. Furthermore, the proposed methods can be used for the corrective maintenance of all systems having hidden interacting components.
Assessing the efficiency of hospitals operating under a unique owner: a DEA application in the presence of missing data
(Inderscience Publishers, 2010-05) Aksezer, Sezgin Çağlar; Benneyan, James C.
Originally developed in the late 1970s to assess the efficiency of comparable operating units, Data Envelopment Analysis (DEA) has since been used in a variety of contexts. Although incomplete data sets are often encountered in practice, the best approach in such situations is unclear in general. This paper explores methods such as multiple imputation, bootstrapping and smart dummy variable replacement, borrowed from similar missing data problems in regression analysis. Each missing data method is tested on a library of DEA problems that are gathered from the DEA literature. These problems are selected in such a way as to represent a thorough cross-section of problem sizes (small, medium, large) and types (type of DEA model, number of decision-making units, number of inputs, number of outputs, etc.). The results are illustrated by comparing the solutions of complete data sets against the simulated versions of the same data sets with missing data. The sensitivity of each method on the efficiency scores and ranking of the decision-making units is presented.
Dynamic frontier estimation for monitoring team performances: A case on Turkish first division football league
(Emerald Group Publishing Limited, 2019-06-10) Yılmaz, Melike; Aksezer, Sezgin Çağlar; Atan, Sabri Tankut
Purpose: This paper aims to investigate how predictions of football league standings and efficiency measures of teams, obtained through frontier estimation technique, evolve compared to actual results. Design/methodology/approach: The study is based on data from the Turkish first division football league. Historical data for five seasons, from 2011 to 2016, are used to compare weekly estimates to de facto results. Data envelopment analysis efficiency measures are used to estimate team performances. After each week, a data envelopment analysis is run using available data until then, and final team standings are estimated via computed efficiencies. Estimations are improved by using a data envelopment analysis model that incorporates expert knowledge about football. Findings: Results indicate that deductions can be made about the league’s future progress. Model incorporating expert knowledge tends to estimate the performance better. Although the prediction accuracy starts out low in early stages, it improves as the season advances. Scatter of individual teams’ performances show fluxional behaviour, which attracts studying the impact of uncontrollable factors such as refereeing. Originality/value: While all previous studies focus on season performance, this study handles the problem as a combination of weekly performance and how it converges to reality. By tracking weekly performance, managers get a chance to confront their weak performance indicators and achieve higher ranking by improving on these inefficiencies.
Mobilya sektöründe pnömatik zımbalama ve vidalama işlerinin ergonomik risk değerlendirmesi
(Çukurova Üniversitesi Mühendislik Fakültesi, 2017) Alıcı, Hale; Atıcı Ulusu, Hilal; Gündüz, Tülin
Uygun olmayan çalışma duruşları kas iskelet sistemi rahatsızlıklarına neden olduğu gibi, üretimdeki verimin de düşmesine yol açmaktadır. Dolayısıyla ergonomi disiplininin öncelikli amacı, çalışma koşullarını iyileştirerek, iş görenin çalışma ve yaşam kalitesini yükseltmek ve verimliliği arttırmaktır. Kas iskelet sistemi rahatsızlıklarının önlenmesi amacıyla iş yerlerinde ergonomik risk değerlendirme yöntemleri uygulanmakta ve yapılan düzenlemelerle iş yükü azaltılmaktadır. Bu çalışmada, sıklıkla tekrarlanan statik ve dinamik duruşlara ve üst ekstremite pozisyonlarına göre seçilen REBA, OWAS, OCRA, QEC ve ManTRA yöntemleri mobilya imalatı yapılan bir atölyede uygulanmış, ergonomik açıdan risk oluşturabilecek pnömatik zımbalama ve pnömatik vidalama işlerinin risk değerlendirmesi yapılmıştır. Yapılan değerlendirmeler sonucunda, pnömatik zımbalama ve pnömatik vidalama işlerinde el, bilek, dirsek ve omuz gibi üst vücut bölgelerinin yoğun kullanıldığı ve teknik hareket sıklığının fazla olduğu durumlar için en uygun ergonomik risk değerlendirme yönteminin OCRA yöntemi olduğu sonucuna varılmıştır. OCRA yöntemi ile bir çevrim süresinin istasyonlara ayrılarak, her teknik hareketin tek tek analize dahil edilmesi detaylı bir değerlendirme yapılmasını sağlamıştır.
Limanlarda kullanılan iş makinelerinde risk analizi çalışması
(Süleyman Demirel Üniversitesi Mühendislik Fakültesi, 2017) Güller, Alp; Gündüz, Tülin
Limanlar genellikle iş yerleri arasında çok önemli bir alanı kapsamaktadır. İçeriğinde ne olduğu kendilerince bilinmeyen yükler ile uğraşan çalışanların, geniş bir yelpazede makinelerle birlikte çalışarak görev yaptığı ve çoğu zaman aynı dili konuşmayan insanların bir şekilde anlaştığı özel ortamlardır. Limanlardaki çalışma gündüz ve gece boyunca ve her türlü hava koşulunda gerçekleşmektedir. Gelen ve giden yükleri yakalamak için ya da bir iskele boşaltmak için hızlı çalışmak, bir şekilde geminin kargosunu boşaltmak için çalışanlarda genellikle baskılar oluşturmaktadır. Limanlarda bu faktörler, çalışmak için yüksek riskler ve sürekli değişen koşullar içermektedir. Şirketlerin, bu riskleri ve sürekli değişen çalışma koşullarını düzgün yönetmek için uygun sağlık ve güvenlik önlemlerini uygulamaları gerekmektedir. Bu çalışmada, limanlarda kullanılan makinelerde meydana gelen iş kazaları ve önleme yöntemlerinin incelenmesi amaçlanmıştır. Öncelikli olarak liman sektöründe kullanılan iş makineleri, limanlarda iş güvenliğiyle alakalı kanunlar, yönetmelikler, uluslararası sözleşmeler ve daha önce yapılmış olan bilimsel araştırmalar incelenmiştir. Yapılan incelemelerle birlikte, limanlarla ilgili risk analizi uygulaması yapılmıştır. Risk analizi sonucu elde edilen veriler bir araya getirilerek iş kazalarını engellemeye yönelik alınması gereken önlemler belirlenmiştir.
Parametrik ve parametrik olmayan verimlilik değerlendirmesi ve karşılaştırılması: Türkiye elektrik santralleri örneği
(Bursa Uludağ Üniversitesi, 2017) Sarıca, Kemal
Çalışma boyunca Türkiye’deki çeşitli enerji santrallerinin operasyonel ve uzun vadeli yatırım performansları Stokastik Sınır Analiz (SSA) ve Veri Zarflama Analizi (VZA) kullanılarak karşılaştırıldı. Veri kümesi, özel ve kamu mülkiyetindeki 65 termal, hidroelektrik ve rüzgâr enerji santrallerinden oluşturuldu. Operasyonel ve yatırım performansını yansıtan verimlilik endeksleri ortaya konup incelendi. Analizde ölçek, sabit ve değişken, güvence bölgesi, gevşek tabanlı ölçüm, sistem karşılaştırma ve bilateral tip DEA modelleri ile Cobb-Douglas ve Translog üretim fonksiyonlarını kullanan stokastik sınır analizi kullanıldı. Ölçek getirisinin analizine yönelik VZA ve SSA modellerinin ortaya koyduğu tüm indisler kullanılarak değerlendirmeler yapıldı. Kamu-özel, termal-yenilenebilir karşılaştırmalarının yanı sıra doğal gaz-kömür-petrol santralleri verimlilik performans değerlerine göre karşılaştırıldı. VZA ve SSA metotlarından elde edilen sonuçlar karşılaştırıldı. İlginç verimlilik endeksi ve çeşitli giriş/çıkış faktörleri arasında ilişkiler ortaya kondu ve değerlendirildi. Doğal gazla çalışan elektrik santralleri, yatırım verimliliği açısından kömürle çalışan santrallerden daha iyi performans gösterse de, değişken getiri oranlarına göre operasyonel performansı için tersi geçerlidir.
Otomotiv kablo imalatında ergonomik risk analizi
(Bursa Uludağ Üniversitesi, 2017) Ulutaş, İlker Boğaç; Gündüz, Tülin
Çalışma yaşamında "kas iskelet sistemi hastalıkları" (KİSH) önemli bir sağlık sorunudur. Bu çalışmanın amacı tehlikeli sınıftaki bir işyerinde işlerin ergonomik risklere göre değerlendirilmesidir. Çalışmada, kablo imalatı yapılan bir fabrikada KİSH ile ilişkili problemler tespit edilmiştir. Belirlenen iki özel iş istasyonunda, hızlı maruziyet değerlendirme (HMD) ve REBA metotları uygulanmıştır. Bu analizlerin sonrasında, fiziksel risk etmenlerinin iyileştirilmesi için yeni uygulamalar geliştirilmiştir. Yapılan düzenlemeler sonrası tekrar analizler yapılarak elde edilen sonuçların etkinliği değerlendirilmiştir. Sonuç olarak, otomotiv kablo imalatı sektöründe montaj aşamasındaki kas iskelet sistemi hastalıklarına maruz kalma riski azaltılmıştır.

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