Prioritizing warehouse performance measures in contemporary supply chains

Purpose: Due to the importance of efficiency and responsiveness measures rather than just efficiency measures, this research recognizes both measures when considering overall performance of warehouse operations. Thus, the purpose of this study is to prioritize overall performance measures associated with warehouse operations in manufacturing, third-party logistics (3PL) service provider, and retail industry supply chains. Design/methodology/approach: The study uses an integrated approach that involves the Q-sort method to group measures into four categories. Fuzzy analytical hierarchy process (FAHP) was then used to prioritize individual performance measures within each category and integer liner programming model was used to validate prioritized categories, using the judgement of multiple decision makers across three industries. Findings: The result shows that the financial category is a dominating performance category in managing warehouse operations across all three industries selected. Within the financial category, cost of insurance accounted for 25% of total weight of the category, and is considered to be a powerful measure. The financial category is verified by multiple decision makers across three industries, as the most important performance category. Research Limitations/implications: As part of adopting the proposed methodology in practice, it needs to be guided by overall methodology appropriate for industry-specific contexts. Originality/value: Key novel aspects of this study are to categorize warehouse operations measures and analyze their perspectives in different industries, understand dominant categories of warehouse operations measures in the contemporary supply chain and finally to explore to what extent current practices lead to achieving efficiency and responsiveness in the selected industries

A Modified FMEA Approach to Enhance Reliability of Lean Systems

Purpose - The purpose of this thesis is to encourage the integration of Lean principles with reliability models to sustain Lean efforts on long term basis. This thesis presents a modified FMEA that will allow Lean practitioners to understand and improve the reliability of Lean systems. The modified FMEA approach is developed based on the four critical resources required to sustain Lean systems: personnel, equipment, material and schedule. Design/methodology/approach – A three phased methodology approach is presented to enhance the reliability of Lean systems. The first phase compares actual business and operational conditions with conditions assumed in Lean implementation. The second phase maps potential deviations of business and operational conditions to their root cause. The third phase utilizes a modified Failure Mode and Effects Analysis (FMEA) to prioritize issues that the organization must address. Findings – A literature search shows that practical methodologies to improve the reliability of Lean systems are non existent. Research Limitations/Implications –The knowledge database involves tedious calculations and hence it needs to be automated. Originality/Value • Defined Lean system reliability • Developed conceptual model to enhance the Lean system reliability • Developed knowledge base in the form of detailed hierarchical root trees for the four critical resources that support our Lean system reliability • Developed Risk Assessment Value (RAV) based on the concept of effectiveness of detection using Lean controls when Lean designer implements Lean change. • Developed modified FMEA for the four critical resources • Developed RPLS tool to prioritize Lean failures • Developed case study to analyze RPN and RAV approac

Materials handling equipment selection using integrated fuzzy AHP and VIKOR methods

By combining the methods for determining the relative weights of the criteria and standard methods of ranking of alternatives, one makes optimal decisions about a certain issue, regardless of the nature of the parameters that describe it. Selection of materials handling equipment for typical conditions and working environment is one of the problems of multi-criteria analysis, i.e. the selection procedure is not sufficiently structured, dependent on broad areas of knowledge, and requires the application of efficient and effective tool for decision making. The proposed methodology of equipment selection is a combination of positive experiences in the application of known methods of decision-making and their modifications (Fuzzy AHP and VIKOR). In this case, process of the forming of system alternatives and defining criteria are illustrated in a numerical example of the equipment (device) selection within the transport and handling mechanization (trucks - forklift)

Materials handling equipment selection using integrated fuzzy AHP and VIKOR methods

By combining the methods for determining the relative weights of the criteria and standard methods of ranking of alternatives, one makes optimal decisions about a certain issue, regardless of the nature of the parameters that describe it. Selection of materials handling equipment for typical conditions and working environment is one of the problems of multi-criteria analysis, i.e. the selection procedure is not sufficiently structured, dependent on broad areas of knowledge, and requires the application of efficient and effective tool for decision making. The proposed methodology of equipment selection is a combination of positive experiences in the application of known methods of decision-making and their modifications (Fuzzy AHP and VIKOR). In this case, process of the forming of system alternatives and defining criteria are illustrated in a numerical example of the equipment (device) selection within the transport and handling mechanization (trucks - forklift)

Un enfoque de toma de decisiones multicriterio aplicado a la estrategia de transformación digital de las organizaciones por medio de la inteligencia artificial responsable en la nube de las organizaciones. Estudio de caso en el sector de salud

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Estudios Estadísticos, leída el 08-02-2023Organisations are committed to understanding both the needs of their customers and the capabilities and plans of their competitors and partners, through the processes of acquiring and evaluating market information in a systematic and anticipatory manner. On the other hand, most organisations in the last few years have defined that one of their main strategic objectives for the next few years is to become a truly data-driven organisation in the current Big Data and Artificial Intelligence (AI) context (Moreno et al., 2019). They are willing to invest heavily in Data and AI Strategy and build enterprise data and AI platforms that will enable this Market-Oriented vision (Moreno et al., 2019). In this thesis, it is presented a Multicriteria Decision Making (MCDM) model (Saaty, 1988), an AI Digital Cloud Transformation Strategy and a cloud conceptual architecture to help AI leaders and organisations with their Responsible AI journey, capable of helping global organisations to move from the use of data from descriptive to prescriptive and leveraging existing cloud services to deliver true Market-Oriented in a much shorter time (compared with traditional approaches)...Las organizaciones se comprometen a comprender tanto las necesidades de sus clientes como las capacidades y planes de sus competidores y socios, a través de procesos de adquisición y evaluación de información de mercado de manera sistemática y anticipatoria. Por otro lado, la mayoría de las organizaciones en los últimos años han definido que uno de sus principales objetivos estratégicos para los próximos años es convertirse en una organización verdaderamente orientada a los datos (data-driven) en el contexto actual de Big Data e Inteligencia Artificial (IA) (Moreno et al. al., 2019). Están dispuestos a invertir fuertemente en datos y estrategia de inteligencia artificial y construir plataformas de datos empresariales e inteligencia artificial que permitan esta visión orientada al mercado (Moreno et al., 2019). En esta tesis, se presenta un modelo de toma de decisiones multicriterio (MCDM) (Saaty, 1988), una estrategia de transformación digital de IA de la nube y una arquitectura conceptual de nube para ayudar a los líderes y organizaciones de IA en su viaje de IA responsable, capaz de ayudar a las organizaciones globales a pasar del uso de datos descriptivos a prescriptivos y aprovechar los servicios en la nube existentes para ofrecer una verdadera orientación al mercado en un tiempo mucho más corto (en comparación con los enfoques tradicionales)...Fac. de Estudios EstadísticosTRUEunpu

AN EMPIRICAL ANALYSIS OF AUTOMOTIVE MANUFACTURERS SUPPLY CHAIN PERFORMANCE IN CHINA

The research develops a framework for the evaluation of automotive supply chain performance in China. In addition, the research presents indications from a study of Chinese automotive companies with regards to their evaluation and attempts to propose some alternatives for future improvement

New Fundamental Technologies in Data Mining

The progress of data mining technology and large public popularity establish a need for a comprehensive text on the subject. The series of books entitled by "Data Mining" address the need by presenting in-depth description of novel mining algorithms and many useful applications. In addition to understanding each section deeply, the two books present useful hints and strategies to solving problems in the following chapters. The contributing authors have highlighted many future research directions that will foster multi-disciplinary collaborations and hence will lead to significant development in the field of data mining

Risk Management In Supply Chain Integration Using A Business Intelligence Optimization Approach

Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business IntelligenceThe goal of this proposal is to develop a theoretical model that will assist organizations in building and adapting their supply chains to a new, better, and more robust model, using technology and tools that were not available just a few years ago. The coronavirus pandemic has uncovered resilient weaknesses in countries and organizations, and we hope to use Data Analytics and Business Intelligence approaches to turn those weak spots into strengths and competitive advantage through this study. Having this in mind, this study aims to identify the association between supply chain risk management (SCRM) and business intelligence architectures. Thus, this study aims to fill the gap of information and studies in this area by providing relevant inputs that may be used on other studies in this field

A decision model to prioritise logistics performance indicators

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonPerformance measurement is an important concern that has recently attracted much attention in the logistics area from both practitioners and academics. The performance measurement of logistics companies is based upon diverse performance indicators. However, to date, limited attention has been paid to the performance measurement of logistics companies and, also, performance measurement processes have become more complex for logistics companies due to the existence of numerous performance indicators. In this regard, the way in which decision makers in logistics companies deal with some vaguenesses, such as deciding on the most important indicators holistically and determining interrelationships between performance indicators, has remained an issue that needs to be resolved. This study, therefore, aims to offer a comprehensive decision model for identifying the key logistics performance indicators and determining the interrelationships among these indicators from logisticians’ perspective. In line with this purpose, the research first presents a stakeholder-based Balanced Scorecard (BSC) model which provides a balanced view by including financial and non-financial performance indicators and a comprehensive approach as a response to the major shortcoming of the generic BSC regarding the negligence of various stakeholders. Then, a large number of performance indicators used in logistics are systematically examined under the proposed model, and the key indicators are selected through an online survey conducted in the Turkish logistics industry. Subsequently, since the performance measurement indicators are not independent of each other, it is critical to understand the causal relationships among different indicators. In such cases, group decision making techniques are capable of modelling such complexities. After a systematic comparison of these techniques, a realistic and easy-to-follow multi-criteria decision making technique, the Analytic Network Process (ANP), is revealed as a suitably powerful method to determine the interrelationships among the indicators. Additionally, a case study approach based on the data obtained from three logistics companies is used to illustrate both the applicability of the model and the practicality of the ANP application. Furthermore, the sensitivity of the results about the case companies is also analysed with several relevant ‘what-if’ scenarios. Thus, real-life practices of three case companies are investigated with the proposed approach. Consequently, this research proposes the BSC-ANP integration which provides a novel way and in-depth understanding to evaluate logistics performance indicators for the competitiveness of logistics companies. Thus, in order to address the aforementioned vaguenesses, the proposed model in this study identifies key performance indicators with the consideration of various stakeholders in the logistics industry to decide on the most important indicators, and evaluates the interrelationships among the indicators by using the ANP. The results of the study show that the educated employee (15.61%) is the most important indicator for the competitiveness of logistics companies and four prominent indicators (educated employee, managerial skills, cost, and profitability) need to be primarily considered by logistics companies. In this way, with this integration, not only the performance indicators in logistics, but also different stakeholders of logistics companies are assessed by the ANP method. This means that the results of this research are not only useful for helping logistics companies to decide which indicators should be focused on to become more competitive, but also can be used as a reference model by different stakeholders in their decision-making processes in order to select the best logistics provider. Keywords: Performance measurement; logistics performance indicators; balanced scorecard (BSC); analytic network process (ANP); multi-criteria decision making (MCDM); stakeholder