Analysis on Supply Chain Risk Factors of Prefabricated Buildings Using AHP-DEMATEL-ISM Model

Given the numerous participants in the supply chain of prefabricated buildings and the great difficulty in improving risk management and control level, influencing factors through the literature review method were identified. Then, 7 first-level indexes and 23 second-level indexes were extracted. An influence index system for supply chain risks of prefabricated buildings was established. Comprehensively considering the importance and correlation of various influencing factors, the AHP-DEMATEL (Analytic Hierarchy Process and Decision-making Trial and Evaluation Laboratory) combined model was constructed, which solved the one-sided problem of the weight result of a single model. Then, the ISM (Interpretative Structural Modelling) model could be used to show the characteristics of the structural relationship of influencing factors hierarchically, and the fundamental supply chain risk factors were more accurately and clearly explored using the AHP-DEMATEL-ISM model. Results show that: (1) Logistics transportation distance, damage to prefabricated components during transportation, and unreasonable control of assembly period are the fundamental factors affecting the risk of prefabricated buildings, among which logistics transportation distance and damage to prefabricated components during transportation are the resulting factors, and the unreasonable control of the assembly period is the causal factor, but the factor weight is low because of the difficulty in short-term improvement. (2) Component production technology and equipment, transportation distance, and punctuality of product supply account for a high weight in the supply chain risk assessment index system of prefabricated buildings. (3) A total of 11 factors, such as inconformity of product design and standard, immature design technology level, component production technology and equipment, and quality of purchased materials, affect the supply chain risk of prefabricated buildings and are also causal factors with high weights. Conclusions obtained in the study provide a theoretical basis for the supply chain risk control of prefabricated buildings to a certain extent and also present a new perspective for the supply chain risk assessment of prefabricated buildings

Hybrid fuzzy analytical hierarchy process with fuzzy inference system on ranking stem approach towards blended learning in mathematics

In the era of Education 4.0, blended learning has been selected as one of the transformational pedagogies for the teaching and learning process that integrate Science, Technology, Engineering, and Mathematics (STEM), a new norm that needs to be adopted by Malaysia. Since the COVID-19 pandemic, the issue has been highlighted at most levels of study in the education field. However, limited knowledge of the implementation of 21st Century learning skills with Web 2.0 among teachers has made the students demotivated for their mathematics classroom. Moreover, dynamic changes in the standard curriculum have made the situation more challenging for teachers in selecting the appropriate STEM approach to ensure students are fully engaged. Inspired by the problem, this research used fuzzy multi-criteria decision-making (MCDM) concepts. A hybrid fuzzy MCDM model proposes a four stages process to rank and find the best implementation STEM approach in the mathematics classroom. The model is constructed by integrating the Fuzzy Analytical Hierarchy Process (FAHP) to determine the weights of STEM criteria and sub-criteria and the Fuzzy Inference System (FIS) to compute the best STEM approach in the mathematics classroom. The procedure involves exploring the issue associated with the selection problems, deriving decision criteria important weights, and ranking various alternatives with applied intuitive multiple centroids as a defuzzification method. The results showed hands-on activities as the best STEM approach while requisite knowledge is the important criterion with the greatest value of weights. Thus, the proposed model helps provide a clear picture for teachers in the implementation of STEM approach in Mathematics based on a comprehensive view and also lay a new foundation knowledge in fuzzy MCDM view, particularly in STEM education. Also, it helps the Ministry of Education (MoE) to achieve one of the initiatives in Wave 3 of the Malaysia Education Blueprint (2021-2025), which is to share the best practice in the classroom to cultivate a peer-led culture of professional excellence among teachers as the basis for improving the implementation and achievement of STEM at the national level

Assessing Risks Awareness in Operating Rooms among Post-Graduate Students: A Pilot Study

Background: In this study, we promote a global approach to occupational risk perception in order to improve occupational health and safety training programs. The study investigates the occupational risk perception of operating room healthcare workers using an Analytic Hierarchy Process approach. Methods: A pilot study was carried out through a cross-sectional survey in a university hospital in Southern Italy. An ad hoc questionnaire was administered to enrolled medical post-graduate students working in the operating room. Results: Fifty medical specialists from seven fields (anaesthetists, digestive system surgeons, general surgeons, maxillofacial surgeons, thoracic surgeons, urologists, and gynaecologists) were questioned about perceived occupational risk by themselves. Biological, ionizing radiation, and chemical risks were the most commonly perceived in order of priority (w = 0.300, 0.219, 0.210). Concerning the biological risk, gynaecologists unexpected perceived this risk as less critical (w = 0.2820) than anaesthesiologists (w = 0.3354), which have the lowest perception of the risk of ionizing radiation (w = 0.1657). Conclusions: Prioritization methods could improve risk perception in healthcare settings and help detect training needs and perform sustainable training programs

Bulanık Çok-Amaçlı Doğrusal Programlama ve Aralık Tip-2 Bulanık AHP Yöntemi İle Yeşil Tedarikçi Seçimi

Yeşil Tedarikçi Seçimi YTS son yıllarda şirketler, araştırmacılar ve müşteriler tarafından, yasal düzenlemeler, artan müşteri bilinci, sivil toplum kuruluşları, kamusal ve sosyal sorumluluklar nedeniyle artan bir ilgiyle karşı karşıyadır. Tedarikçi seçimi tedarik zinciri yönetiminde rol oynayan en önemli faktörlerden biridir. Tedarikçilerin çevresel performansının iyileştirilmesi yeşil tedarik zincirlerinin geliştirilmesi için kritik öneme sahiptir. Tedarikçiler, herhangi bir işletmede üretim için gerekli olan hammaddeleri tedarik ettikleri için yeşil tedarik zinciri yönetimi performansını geliştirmede büyük bir öneme sahiptirler. Bu nedenle her geçen gün daha fazla işletme yeşil satın alma, yeşil paketleme ve tersine lojistik gibi iş performansını ve rekabet gücünü artırmaya yönelik çeşitli yeşil girişimlere yatırım yapmaktadırlar. Bununla birlikte, tedarikçi seçiminde fiyat, kalite, teslimat vb. geleneksel kriterler dikkate alınmakta tedarikçilerin yeşil performanslarını ölçmeye yönelik kriterler göz ardı edilmektedir. Firmaların performanslarını ve rekabet gücünü artırıcı amaçlarına ulaşabilmeleri için karar vericiler, YTS problemlerini çözmek için en iyi yöntemi uygulamalı ve en doğru kriterleri seçmelidirler. Genel olarak, yeşil tedarikçi değerlendirme ve seçim problemleri belirsizlik içermekte ve bulanık küme teorisi, çeşitli kriterlere göre tedarikçilerin değerlendirilmesi için dilsel değişkenleri kullanarak karar vericilerin tercihlerini ve görüşlerini anlamlı sonuçlara dönüştürmeye yardımcı olmaktadır. Bilgi eksikliği, sınırlı sayıda niceliksel bilgi, şirketlerin özel bağlamları ve değişen tedarikçi geçmişleri nedeniyle YTS değerlendirme ve seçim problemleri zorlu bir süreçtir. Bu çalışmada aralık tip-2 Bulanık Analitik Hiyerarşi Prosesi BAHP yöntemi ve Bulanık Çok-Amaçlı Doğrusal Programlama BÇADP modeli kullanılarak yeşil tedarikçilerin performanslarının değerlendirilmesi için entegre bir yöntem önerilmiştir. Aralık tip-2 BAHP yöntemi karar vericilerin görüşlerindeki belirsizliği yansıtmada tip-1 bulanık kümelere göre daha uygundur ve ilk aşamada aralık tip-2 BAHP yöntemi kullanılarak YTS’nde ele alınan kriterlerin ağırlıkları elde edilmiştir. İkinci aşamada ise Maliyet, geç teslimat, salınımı, kirlilik üretimi ve çevre dostu malzeme kullanımı gibi amaçları içeren yeni bir BÇADP modeli önerilmiştir. Daha sonra BAHP yönteminden elde edilen ağırlıklar BÇADP modelinde kullanılarak optimal çözüm elde edilmiş ve tedarikçilerin değerlendirmeleri yapılmıştır. Önerilen yöntemin uygulanabilirliği bir örnek üzerinde gösterilmiştir

MODIFIED AHP TO SELECT NEW SUPPLIERS IN THE INDONESIAN STEEL PIPE INDUSTRY

The analytical hierarchy process (AHP) is not as effective and efficient as the pairwise comparison (PWC) matrix. The aim of this research is to tackle the weaknesses of the AHP and then applied them to a real-life case of new supplier selection in the Indonesian steel pipe industry. Some criteria are identified that are relevant in the Indonesian steel pipe companies to select new suppliers. A total score is calculated for each supplier and this ranking is used to identify the best one. In this research, the decision maker created the sorting of the criteria used in supplier selection. The matrix of PWC was constructed based on the sorting. Then, the weight of each criterion was calculated using AHP. The result of the method was an improvement over previous methods, because the value of the consistency ratio (CR) was zero, indicating a high degree of validity. This modified method was an improvement on the AHP, with a consistent solution without the need to repeat the calculation

Fusing incomplete preference rankings in design for manufacturing applications through the ZM II-technique

The authors recently presented a technique (denominated “ZM”) to fuse multiple (subjective) preference rankings of some objects of interest - in manufacturing applications - into a common unidimensional ratio scale (Franceschini, Maisano 2019). Although this technique can be applied to a variety of decision-making problems in the Manufacturing field, it is limited by a response mode requiring the formulation of complete preference rankings, i.e. rankings that include all objects. Unfortunately, this model is unsuitable for some practical contexts – such as decision-making problems characterized by a relatively large number of objects, field surveys, etc. – where respondents can barely identify the more/less preferred objects, without realistically being able to construct complete preference rankings. The purpose of this paper is to develop a new technique (denominated “ZMII”) which also “tolerates” incomplete preference rankings, e.g., rankings with the more/less preferred objects only. This technique borrows the underlying postulates from the Thurstone’s Law of Comparative Judgment and uses the Generalized Least Squares method to obtain a ratio scaling of the objects of interest, with a relevant uncertainty estimation. Preliminary results show the effectiveness of the new technique even for relatively incomplete preference rankings. Description is supported by an application example concerning the design of a coach-bus seat

Prioritization of petroleum supply chains’ disruption management strategies using combined framework of BSC approach, fuzzy AHP and fuzzy Choquet integral operator

Industries in every sector have observed tangible losses from a broad range of disruptions during recent years. Factors such as globalization and outsourcing have made supply chains more sophisticated and this makes disruption management more necessary. Any disruption in each part of supply chain makes the whole supply chain face derangement and at last, ultimate customers realize the shaped disadvantages. Since avoidance of disruption occurrence is not always possible, application of different strategies with the aid of minimization of negative effects seems necessary. That is why in this paper, different strategies for disruption management in petroleum products supply chain and suitable criteria for prioritizing them are recognized via Balanced Score Card approach measures. After that, by application of fuzzy Analytical Hierarchy Process and intuitionistic fuzzy Choquet integral operator, their priorities are specified in order to make a guideline for managers to set proper plans and manage such disruptions more accurately

Serial-integrated multi-criteria decision-making technique for resilient supplier selection in the manufacturing industry

A supply chain is an entire system of producing and delivering a product or service, from the very beginning stage of sourcing raw material to the final stage of delivering a product or service to end-users. Several global risks and disruptions brought massive and devastating impacts on the world economy including the Small and Medium Enterprises (SMEs). Since the supplier is one of the important elements in a supply chain, economic resilience can be implemented by selecting a resilient supplier. However, the literature shows that previous supplier selections only focused on traditional, green and sustainable suppliers’ criteria but resilience was rare to be discussed. Thus, the first objective of the study is to identify the generic criteria for selecting resilient suppliers. At the same time, there are problems in dealing with uncertainties and incomplete information while selecting suppliers. The second objective is to develop a new integrated Multi-Criteria Decision-Making (MCDM) model that considers incomplete data and uncertainties in selecting resilient suppliers. In this study, the proposed criteria were quality, lead time, cost, flexibility, visibility, responsiveness and financial stability. A serial-integrated MCDM technique was proposed by combining Grey Relational Analysis (GRA) from the grey theory and the Best Worst Method-Technique for Order Preference by Similarity to an Ideal Solution (BMW-TOPSIS) technique in serial to assess the suppliers and select the best alternative. The proposed criteria and technique were applied in the metal manufacturing company (Case 1) and the food manufacturing company (Case 2) which were facing economic problems to demonstrate its effectiveness. The result was generated using MATLAB. The result for Case 1 shows that Financial Stability has the largest weight and Supplier 1 is the best supplier for the company. For Case 2, Cost shows the largest weight, and the best supplier is Supplier 4. Then, the result was verified through manual calculation and validated with Analytic Hierarchy Process-VlseKriterijumska Optimizacija I Kompromisno Resenje (AHP-VIKOR). Through the identification of the generic resilience criteria and the suitable MCDM model, the managers can focus on resilience with the consideration of uncertainties and incomplete information to improve the supplier selection process. This can help to raise the supply chain performance of the companies

Sustainable supplier selection and order allocation for multinational enterprises considering supply disruption in COVID-19 era

The unprecedented outbreak of COVID-19 has left many multinational enterprises facing extremely severe supply disruptions. Besides considering triple-bottom-line requirements, managers now also have to consider supply disruption due to the pandemic more seriously. However, existing research does not take these two key objectives into account simultaneously. To bridge this research gap, based on the characteristics of COVID-19 and similar global emergency events, this paper proposes a model that aims to solve the problem of sustainable supplier selection and order allocation considering supply disruption in the COVID-19 era. It does so by using a multi-stage multi-objective optimization model applied to the different stages of development and spread of the pandemic. Then, a novel nRa-NSGA-II algorithm is proposed to solve the high-dimensional multi-objective optimization model. The applicability and effectiveness of the proposed model is illustrated in a well-known multinational producer of shortwave therapeutic instruments

A Conceptual Framework to Manage Resilience and Increase Sustainability in the Supply Chain

[EN] The challenges of global economies foster supply chains to have to increase their processes of collaboration and dependence between their nodes, generating an increase in the level of vulnerability to possible impacts and interruptions in their operations that may affect their sustainability. This has developed an emerging area of interest in supply chain management, considering resilience management as a strategic capability of companies, and causing an increase in this area of research. Additionally, supply chains should deal with the three dimensions of sustainability (economic, environmental, and social dimensions) by incorporating the three types of objectives in their strategy. Thus, there is a need to integrate both resilience and sustainability in supply chain management to increase competitiveness. In this paper, a systematic literature review is undertaken to analyze resilience management and its connection to increase supply chain sustainability. 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