Maintenance Maturity Level Identification using MABAC Method: An Adaptation of TPM Pillars in a Public Service Sector

Having systematic maintenance practices does sustain the lifecycle of the facilities. Hence, engineers have always been seeking for practical approaches toward providing better maintenance scheme. Such attempts have resulted in the appearance of numerous maintenance management models including the most commonly accepted one, that is, the total productive maintenance (TPM). Although the concept of TPM and its corresponding pillars have extensively been investigated in the recent literature of Maintenance Engineering and Management, the majority of the previous research attempts, including the multi-criteria decision making (MCDM) applications, have handled them within the context of the manufacturing sector; and almost none of them have been applied in the services sector. This paper proposes the multi-attributive border approximation area comparison (MABAC) method, a newly developed MCDM technique, as a tool upon which eight TPM pillars are evaluated in order to identify the maintenance maturity level in a public service sector. The investigations indicate that the proposed model equips maintenance engineers with an insight into the mechanism upon which TPM pillars can operate effectively. The results of the proposed model indicate that the investigated institution is generally not matured enough to be up to the desired level of TPM performance

Maintenance Maturity Level Identification using MABAC Method: An Adaptation of TPM Pillars in a Public Service Sector

914-917Having systematic maintenance practices does sustain the lifecycle of the facilities. Hence, engineers have always been seeking for practical approaches toward providing better maintenance scheme. Such attempts have resulted in the appearance of numerous maintenance management models including the most commonly accepted one, that is, the total productive maintenance (TPM). Although the concept of TPM and its corresponding pillars have extensively been investigated in the recent literature of Maintenance Engineering and Management, the majority of the previous research attempts, including the multi-criteria decision making (MCDM) applications, have handled them within the context of the manufacturing sector; and almost none of them have been applied in the services sector. This paper proposes the multi-attributive border approximation area comparison (MABAC) method, a newly developed MCDM technique, as a tool upon which eight TPM pillars are evaluated in order to identify the maintenance maturity level in a public service sector. The investigations indicate that the proposed model equips maintenance engineers with an insight into the mechanism upon which TPM pillars can operate effectively. The results of the proposed model indicate that the investigated institution is generally not matured enough to be up to the desired level of TPM performance

Monitoring the performance of petrochemical organizations in Saudi Arabia using data envelopment analysis

The petrochemical industry plays a crucial role in the economy of the Kingdom of Saudi Arabia. Therefore, the effectiveness and efficiency of this industry is of high importance. Data envelopment analysis (DEA) is found to be more acceptable in measuring the effectiveness of various industries when used in conjunction with non-parametric methods such as multiple regression, analytical hierarchy process (AHP), multidimensional scaling (MDS), and other multiple criteria decision making (MCDM) approaches. In this study, ten petrochemical companies in the Kingdom of Saudi Arabia are evaluated using Banker, Charnes and Cooper (BCC)/Charnes, Cooper, and Rhodes (CCR) models of DEA to compute the technical and super-efficiencies for ranking according to their relative performances. Data were collected from the Saudi Stock Exchange on key financial performance measures, five of which were chosen as inputs and five as outputs. Five DEA models were developed using different input–output combinations. The efficiency plots obtained from DEA were compared with the Euclidean distance scatter plot obtained from MDS. The dimensionality of MDS plots was derived from the DEA output. It was found that the two-dimensional positioning of the companies was congruent in both plots, thus validating the DEA results

Elicitation of the factors affecting electricity distribution efficiency using the fuzzy AHP method

Efficient and uninterrupted energy supply plays a crucial role in the quality of modern daily life, while it is obvious that the efficiency and performance of energy supply companies has a significant impact on energy supply itself and on determining and finetuning the future roadmap of the sector. In this study, the performance and efficiency of energy supply companies with respect to productivity is investigated with reference to a case study of an electricity distribution company in Turkey. The factors affecting the company’s performance and their corresponding weight have been determined and obtained using the analytical hierarchy process (AHP) and the Fuzzy AHP methods, two well-known multi-criteria decision-making methods, which are widely used in the literature. The results help demonstrate that the criteria obtained to evaluate the company’s energy supply performance play a crucial role in developing strategies, policies and action plans to achieve continuous improvement and consistent development

A study of combined oral anti-diabetic drugs during Ramadan

Background. The safety and efficacy of combination tablets of metformin plus sulfonylurea or plus dipeptidyl peptidase-4 inhibitors have not been studied previously. This study aimed to compare the efficacy and safety of Gliconorm versus Sitavia plus among patients with type 2 diabetes mellitus who fast Ramadan. Methods. This was an open-label study conducted from 1 May 2018 till 1 July 2018. People with type 2 diabetes mellitus who were drug-naïve or on metformin only, with HbA1c < 10 % were included. The participants were divided into two groups. The first group was given Gliconorm (glibenclamide 5 mg + metformin 1000 mg), while the second group was given Sitavia plus (sitagliptin 50 mg + metformin 1000 mg) imme-diately after Iftar. Glycated hemoglobin (HbA1c) was measured before and after Ramadan. Several home recordings of blood glucose were collected. In addition, patients were asked to report any hypoglycemic or severe hyperglycemic episodes. Results. A total of 34 participants (18 women) (19 in the first group and 15 in the second group) were involved the study. The mean age was 49.6 ± 9.3 years. HbA1c reduced from 8.7 % (72 mmol/mol) to 7.6 % (60 mmol/mol) and from 8.7% (72 mmol/mol) to 7.7 % (61 mmol/mol) in the first and second group, respectively (p < 0.0001). Only one patient in the first group experienced one episode of hypoglycemia and hyperglycemia. Conclusion. Both medications seem to be safe and effective during Ramadan fasting.

Spectrum of Pituitary disorders: A retrospective study from Basrah, Iraq [version 2; referees: 2 approved]

Background: Pituitary disorders spectrum includes a wide variety of diseases.This study aimed at a comprehensive description of such disorders for patients from  Faiha Specialized Diabetes, Endocrine and Metabolism Center (FDEMC) in Basrah (Southern Iraq). Methods: Retrospective data analysis of FDEMC for the period from January 2012 through June 2017. We included all patients with pituitary disorders who have MRI pituitary. Results: The pituitary disorders were more common among women. Those with macroadenoma were older than those with microadenoma with nearly equal gender prevalence of macroadenoma. Pituitary adenoma constituted the bulk of pituitary disorders in this registry (67.2%). Growth hormone secreting adenoma were the commonest adenoma seen in 41.0% followed by clinically non-functioning pituitary adenoma(NFPA)in 31.4% and prolactinoma in 26.9%. About 64.8% of pituitary adenoma was macroadenoma. Macroadenoma was seen in 73.4 % of growth hormone secreting adenoma, 61.2% in NFPA and 62.0% of prolactinoma (of them six were giant prolactinoma) Conclusion: Pituitary adenoma constituted the bulk of pituitary disorders in Basrah, growth hormone secreting adenoma is the commonest adenoma followed by NFPA and prolactinoma due to referral bias. A change  in  practice of pituitary adenoma treatment is needed

DEA-Based PROMETHEE II Distribution-Center Productivity Model: Evaluation and Location Strategies Formulation

The current era of industrial economics necessitates warehouse and logistic distribution centers (DCs) to contribute productively toward an organization’s success. Playing such a critical productive role implies that logistics activities must be practiced effectively and efficiently. However, the indistinguishability between effectiveness and efficiency leads to a somewhat shallow interpretation, and consequently, a diluted evaluation. Hence, this paper aims to develop a productivity evaluation model for nine DCs belonging to an international automotive vehicles and spare parts company. The developed model was set up based on two multi-criteria decision making (MCDM) approaches: the Preference Ranking Organization Method for Enrichment of Evaluations II (PROMETHEE II) and data envelopment analysis (DEA). PROMETHEE II was employed to evaluate the effectiveness, while the DEA was utilized in order to measure the efficiency of the investigated DCs. The resulting hybrid model collectively creates what can conceptually and practically be considered a productivity evaluation model. The results also provide six different strategies through which distribution center locations can be evaluated in order to implement potential future initiatives

Measuring the Environmental Maturity of the Supply Chain Finance: A Big Data-Based Multi-Criteria Perspective

This paper presents a strategic roadmap to handle the issue of resource allocation among the green supply chain management (GSCM) practices. This complex issue for supply chain stakeholders highlights the need for the application of supply chain finance (SCF). This paper proposes the five Vs of big data (value, volume, velocity, variety, and veracity) as a platform for determining the role of GSCM practices in improving SCF implementation. The fuzzy analytic network process (ANP) was employed to prioritize the five Vs by their roles in SCF. The fuzzy technique for order preference by similarity to ideal solution (TOPSIS) was then applied to evaluate GSCM practices on the basis of the five Vs. In addition, interpretive structural modeling (ISM) was used to visualize the optimum implementation of the GSCM practices. The outcome is a hybrid self-assessment model that measures the environmental maturity of SCF by the coherent application of three multicriteria decision-making techniques. The development of the Basic Readiness Index (BRI), Relative Readiness Index (RRI), and Strategic Matrix Tool (SMT) creates the potential for further improvements through the integration of the RRI scores and ISM results. This hybrid model presents a practical tool for decision-makers

An Innovative Job Evaluation Approach Using the VIKOR Algorithm

Fairness is a key issue that requires the attention of human resource management practitioners. Having a robust methodical procedure for identifying the value of job positions in an enterprise is essential. Consequently, there is a need for a job evaluation system that ensures fair compensation for each position. A poorly defined job evaluation system creates the dilemma of mismatches between employees and their competencies for their responsibilities and, accordingly, their wages. This results in employee dissatisfaction, which ultimately exacerbates attrition, which is costly because of the loss of talented employees. This paper proposes a VIKOR algorithm as an innovative approach to job evaluations. Engineering-related positions in an international aviation company were analyzed to illustrate the appropriateness of the proposed approach for managing the job evaluation dilemma. The results indicate that 29 job grades would be appropriate for this firm. In addition, the proposed algorithm was found to be superior to other multiple-criteria decision-making techniques at managing the job evaluation dilemma