Giuseppe Aiello, Julio Benítez, Silvia Carpitella, Antonella Certa, Mario Enea, Joaquín Izquierdo and Marco La Cascia
This study aims to propose a decision support system (DSS) for maintenance management of a service system, namely, a street cleaning service vehicle. Referring to the information…
Abstract
Purpose
This study aims to propose a decision support system (DSS) for maintenance management of a service system, namely, a street cleaning service vehicle. Referring to the information flow management, the blockchain technology is integrated in the proposed DSS to assure data transparency and security.
Design/methodology/approach
The DSS is designed to efficiently handle the data acquired by the network of sensors installed on selected system components and to support the maintenance management. The DSS supports the decision makers to select a subset of indicators (KPIs) by means of the DEcision-MAaking Trial and Evaluation Laboratory method and to monitor the efficiency of performed preventive maintenance actions by using the mathematical model.
Findings
The proposed maintenance model allows real-time decisions on interventions on each component based on the number of alerts given by sensors and taking into account the annual cost budget constraint.
Research limitations/implications
The present paper aims to highlight the implications of the blockchain technology in the maintenance field, in particular to manage maintenance actions’ data related to service systems.
Practical implications
The proposed approach represents a support in planning, executing and monitoring interventions by assuring the security of the managed data through a blockchain database. The implications regard the monitoring of the efficiency of preventive maintenance actions on the analysed components.
Originality/value
A combined approach based on a multi-criteria decision method and a novel mathematical programming model is herein proposed to provide a DSS supporting the management of predictive maintenance policy.
Details
Keywords
Miguel Angel Ortíz-Barrios, Stephany Lucia Madrid-Sierra, Antonella Petrillo and Luis E. Quezada
Food manufacturing supply chain systems are the most relevant wheels of the world economy since they provide essential products supporting daily life. Nevertheless, various supply…
Abstract
Purpose
Food manufacturing supply chain systems are the most relevant wheels of the world economy since they provide essential products supporting daily life. Nevertheless, various supply inefficiencies have been reported to compromise food safety in different regions. Sustainable supplier management and digitalization practices have become cornerstone activities in addressing these shortcomings. Therefore, this paper proposes an integrated method for sustainability management in digital manufacturing supply chain systems (DMSCS) from the food industry.
Design/methodology/approach
The Intuitionistic Fuzzy Analytic Hierarchy Process (IF-AHP) was used to weigh the criteria and subcriteria under uncertainty. Second, the Intuitionistic Fuzzy Decision-Making Trial and Evaluation Laboratory (IF-DEMATEL) was applied to determine the main DMSCS sustainability drivers whilst incorporating the expert's hesitancy. Finally, the Combined Compromise Solution (CoCoSo) was implemented to pinpoint the weaknesses hindering DMSCS sustainability. A case study from the pork supply chain was presented to validate this method.
Findings
The most important criterion for DMSCS sustainability management is “location” while “manufacturing capacity” is the most significant dispatcher.
Originality/value
This paper presents a novel approach integrating IF-AHP, IF-DEMATEL, and CoCoSo methods for sustainability management of DMSCS pillaring the food industry.
Details
Keywords
Seyyed Habibollah Mirghafoori, Hossein Sayyadi Tooranloo and Sepideh Saghafi
In this way, the aim of this study is to expand and evelop the application of this technique in FMEA to rank failure modes of ESQ of academic libraries in an intuitionistic fuzzy…
Abstract
Purpose
In this way, the aim of this study is to expand and evelop the application of this technique in FMEA to rank failure modes of ESQ of academic libraries in an intuitionistic fuzzy environment. Assessment of electronic service quality (ESQ) of libraries is significantly important according to their major roles. It should be noted that the ESQ has a significant impact on customer satisfaction, which improves organizational performance. Accordingly, low ESQ means waste of organizational resources and poor user satisfaction. So, there is a dire need to reflect reasons inducing failure modes in academic library ESQ. Thus, investigation of failure modes affecting academic library ESQ is highly important. One solution in this area is utilization of the intuitionistic fuzzy (IF) failure mode and effects analysis (FMEA) as one of the widely used methods for prediction and identification of failure modes.
Design/methodology/approach
The present study in terms of objective is applied and in terms of the type of method is descriptive-analytical. The research sample included four experts of Yazd academic Libraries (Iran). To collect data, three types of questionnaires were distributed among experts. The purpose of the first questionnaire was to identify and reach an agreement on e-library failure modes. Type II questionnaire was used to determine the importance of identified risk factors and Type III questionnaire was used to prioritize the factors.
Findings
Results indicate that the difficulty of using websites, lack of provided information feedback to users and lack of links on the website to users' are the main priorities for improving ESQ in the studied academic libraries.
Originality/value
In this approach, the Intuitionistic fuzzy Elimination Et Choix Traduisant la REalité and technique for order of preference by similarity to ideal solution method were used to rank failure modes in academic library ESQ within the FMEA framework.]