Suchergebnisse

PurposeLocating disaster response centers is one of the key elements of efficient relief operations. The location and infrastructure of the candidate facilities usually conform to the required criteria at different levels. This study aims to identify the criteria for the main and local distribution center location problem separately and prioritize each candidate distribution center using a hybrid multiple criteria decision-making approach.Design/methodology/approachThe proposed model incorporates analytic hierarchy process (AHP) and Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS) under interval type-2 fuzzy sets (IT2FSs) to overcome the uncertainty of experts` judgments and expressions in the evaluations of candidate distribution centers. In the proposed approach, weights of the criteria are determined using type-2 fuzzy AHP and the candidate distribution centers are prioritized using type-2 fuzzy TOPSIS.FindingsTransportation, cost, infrastructure and security are determined as the main criteria for the main distribution center location criteria. Cost, warehouse facilities and security are the main criteria for local distribution center location selection. Prioritization enables decision-makers to assess each alternative accordingly to be able to select the best locations/facilities for efficient disaster response operations.Originality/valueThis study proposes new multi-criteria decision support models for prioritizing disaster response distribution centers. IT2FSs are used to be able to reflect both the complexity and vagueness of disaster environment and expert opinions. Different support models are suggested for main and local distribution centers considering their different missions. The proposed methodology is applied in Istanbul city, Turkey, where a high-magnitude earthquake is expected.

AbstractThe purpose of this study is to define a novel hierarchical group decision‐making (HGDM) problem. For this problem, a practical solution approach is proposed for information technology (IT) project evaluation and prioritization. HGDM is a decision‐making problem with a large number of decision makers (DMs) or experts organized in a hierarchical structure. For this problem, a practical solution approach based on pairwise comparisons is developed. For evaluating the projects in organizations, specifically for the IT projects, a hierarchy of many DMs make project proposals and assess proposed projects using various sets of criteria. The proposed HGDM approach is applied to the evaluation and prioritization of IT projects. A problem with 22 DMs and experts in a three‐level hierarchy, 29 criteria and 15 projects is solved using the proposed HGDM approach. The HGDM approach can deal with more complex real‐life problems such as problems where more than 500 projects, 100 DMs and experts, and 100 criteria exist. The originality of the study is the introduction of HGDM in the group decision‐making environment.

AbstractAn occupational health and safety management system (OHSMS) is a set of people, resources, and policies interacting in an organized way to reduce damage and losses generated in the workplace. Although there are various OHSMSs in the shipping industry, the International Safety Management (ISM) Code which is managed by the International Maritime Organization is mandatory for all shipping companies. Occupational Health and Safety Assessment Series (OHSAS) 18,001:2007 is a good alternative to strengthen the implementation performance of the ISM Code. An integrated ISM‐OHSAS safety system can potentially construct a more powerful and practical OHSMS by redesigning safety procedures in ships as a workplace. This study aims to build a more comprehensive OHSMS for assessing and improving the safety at sea by coordinating the constituents of the ISM Code and OHSAS. The criteria sets of both systems are analysed using a Decision Making Trial and Evaluation Laboratory approach to reveal the relations between each other. The result of the proposed approach that represents the connections among important safety constituents may be very useful especially for shipping companies for designing their safety management processes.

In general, studies are carried out to determine the location and to resolve trade-offs in the management of forests according to ecosystem services. The government of Turkey also has been advancing this type of analysis in the practical management of forests. The creation of ecosystem services (ES) suitability map for forests through a participatory approach can provide forest managers valuable information that informs ecosystem-based management plans. The objective of this paper is to formulate and solve the problem of assigning management actions to forest stands in order to optimally provide ecosystem services that are consistent with, and based on Sustainable Development Goals (SDG). We outline a model for a participatory process that has seven steps: (1) determine the possible ES that can be supported on the landscape, (2) create a suitability map for each management unit (stand of trees), (3) define SDG for each ES, (4) create the stakeholder groups, (5) determine the importance of each SDG, (6) determine the contribution of ES to each SDG, and (7) assign ES to each management unit in an optimal manner. We used pairwise comparisons and the Delphi method to determine stakeholder preferences. This information guided the assignment of management actions to management units when optimizing ES outcomes. This approach was applied to a case study centered on the Belgrad Forest, located in northwest Turkey. The percent of land assigned to ES was respectively, water regulation (71%), cultural heritage (17%), education (9%), water supply (2%), and carbon (1%). Through this process, for this case study area, there were no assignments for recreation and aesthetic quality services. As a result, the Belgrade Forest was zoned into management classes unlike the current situation. The pairwise comparisons and the Delphi method can help formalize public participation in the decision-making process. Results from these can inform a resource allocation optimization model through the development of coefficients and constraints. © 2020 The Authors ; We would like to thank the all expert and participants of the Delphi study for their availability.

PurposeIn the automotive industry, the high process complexity becomes an important issue because of the increased number of product and process variants demanded by the customers. To avoid quality defects in assembly and losses in such a complex manufacturing environment, new predictive support systems are required. This study aims to develop a multiple attribute decision support system (DSS) for the prediction and quantification of the risk of failures on the workstations of a leading Turkish automotive manufacturing company.Design/methodology/approachInitially, the factors affecting the failures in workstations and the attributes to evaluate the factors are identified. Subsequently, the relations among the attributes are specified and priorities of them are calculated. Finally, the risk of failures is calculated and tested in a pilot study and validated with real production data.FindingsTo the best of authors' knowledge, this is a unique study that computes the risk scores on the workstations via DSS. The DSS has various advantages for improvements of the manufacturing quality: the risk of failures can be detectable and comparable, the effect of changes in the design of new workstations can be observed. Stations that have medium or high complexity scores demonstrated strong correlation with failure rates. A sensitivity analysis is conducted to predict the effect of improvement actions on the riskiness of the workstations.Originality/valueHigh level of production complexity becomes a crucial issue for companies that use various production processes. Considering this fact, it is a requirement for companies to observe and monitor the risk factors, especially in the assembly lines to be able to eliminate failures derived from complexity. Accordingly, to measure risk scores of the workstations in the assembly lines, a decision support for companies aids executives to manage the complexity level in a reliable and effective way. In this study, the authors develop such a DSS for TOFAS, a leading Turkish automotive company. The proposed DSS is verified and applied through a pilot study on a specific basic production unit. A sensitivity analysis is also conducted to see the effects of potential improvements on the risk scores. Additionally, the trend of risk scores for the stations can also give valuable information for tracing the changes in the time horizon. The proposed DSS also enables an opportunity for the executives in their decision of design processes of new production lines by allocating limited resources in an appropriate way based on the risk scores of possible workstations. The proposed DSS is the first and unique proactive failure prevention model developed in a Fiat Chrysler Automobiles (FCA) plant across the world. TOFAS executives also plan to introduce and enlarge the usage of the model to other FCA plants. It may also be possible to apply the model to other assembly lines in any sector. Another plan of the executives of TOFAS is developing a software, which manages each parameter, to constitute data to the DSS to run this system more instantly and effectively. Moreover, they can take integration actions of the software with world-class manufacturing problem management system that is currently in use in TOFAS.