A study of the efficacy of a reliability management system - with suggestions for improved data collection and decision making.

Master's thesis in Risk ManagementProduct reliability is very important especially in the perspective of new product development. Making highly reliable drilling and well equipment is expensive and time-consuming process. But ignoring the product reliability could prove even more costly. Thus the manufacturers need to decide on the best reliability performance that succeeds to create a proper balance between time, cost and reliability factors to ensure the desired results. A reliability management system is a tool that the manufacturers can use to manage this process to produce reliable equipment. However, if this system is not well structured and lacks some important features, it can affect the outcomes of reliability analysis and decision making. A lot of research has been done on creating a good reliability and maintenance database to improve systems reliability in the petroleum industry. Offshore & Onshore Reliability Data (OREDA) and ISO 12224 are part of such research projects. The main objective of this research is to analyze the existing reliability management system (RMS) in Petroleum Technology Company (PTC) in terms of its structure, features, functionality, and the quality of data being recorded in RMS and how it affects decision making. The research was motivated by following issues 1) Reliability Management System of PTC is not automated in terms of extracting data from other sources within company, 2) PTC is missing a specified platform for failure reporting of their equipment, 3) the activities related to data collection and management are not well-organized hence demanding more effort. To analyze these issues, a literature study is performed to review the existing standards in the industry. ISO14224 and OREDA define a very structured database to get easy access to reliability and maintenance data. OREDA database has well-defined taxonomy, boundaries and database structure. Also, it has a well-organized procedure in place to collect and store reliability data. Quality assessment of the data being collected is done through predefined procedures guideline. OREDA have a very consistent list of codes to store language in coding form in the reliability and maintenance database. By reviewing the existing standard in the industry, a few shortcomings have been identified both in the RMS and PTC failure reporting procedures. It is observed that data from the sources is collected by the responsible person but the collection method is usually not tested and planned. Data collection sources, methods and procedures within company or outside the company lack well-defined criteria and data quality assurance processes. Currently, the company is using Field Service Reports (FSR) and company’s other databases as data sources for RMS. A company cannot access client’s system that contains equipment utilization and process-related information. This can lead to missing information or ambiguous data because the data-entry responsible person needs to make assumptions sometimes to complete the missing operational and environmental data. The RMS database structure lacks well-defined taxonomy, design parameters, and adequate failure mode classification. The Failure modes is an important aspect of the high-quality database since it can help in identifying the need for changes to maintenance periodicities, or the need for additional checks. The Offshore & Onshore Reliability Data (OREDA) project participating companies e.g. Statoil can calculate failure rates for selected data populations of within well-defined boundaries of manufacturer, design and operational parameters. These features are missing in RMS database. It is recommended that PTC consider developing a failure reporting database to handle their failure event data in an organized way. For this purpose, failure reporting, analysis, and corrective action system (FRACAS) technique is suggested. FRACAS data from FRACAS database can be used effectively to verify failure modes and failure causes in the failure mode effect and criticality analysis (FMECA). Failure review board in the FRACAS process includes personnel from mix disciplines (design, manufacturing, systems, quality, and reliability engineering) as well as leadership (technical or managerial leads), to make sure that a well-rounded the discussion is performed for particular failure related issues. The Failure Review Board (FRB) analyzes the failures in terms of time, money required corrective actions. And finally, management makes the decisions on basis of identified corrective action. As data quality has a high impact on the outcomes of reliability analysis through reliability management system. To have a good data quality, data collecting procedures and process management should be well-organized. It is crucial to performed data quality assessment on collected data. A data mining technique is discussed as a part of suggestion to improve data quality in RMS database. Once data is stored in RMS database a data mining method; data quality mining can help to assess the quality of data in a database. This is done by applying a data mining (DM) tool to look at interesting patterns of data with the purpose of quality assessment. Various data mining model is available in the market but PTC needs to select DM model which suits best their business objectives. RMS database is hard-wired so it is difficult to change its features and database structure. However, if PTC emphasize on improving failure reporting procedures and data quality in data sources locating within the company, it will directly and positively affect the data quality in RMS and the results of data analysis in RMS. This, in turn, can improve their decision-making the process regarding new product development and redesigning the existing products

Carrier Status of Methicillin-Resistant Staphylococcus Aureus (MRSA)

To investigate nasal carriage of Methicillin-Resistant Staphylococcus aureus (MRSA) among dental healthcare workers (HCWs) , as the carriers could be the potential risk factor for the transmission of nosocomial infection when exposed to hospital setting during clinical posting. Methods: One hundred HCWs including postgraduate trainees, house physicians, staff nurses and technicians participated in the study. Nasal specimens were obtained by using cotton swabs moistened in sterile saline. The nasal specimens collected were processed as per (CLSI, 2008). Specimens were inoculated on blood agar to look for β-hemolysis of Staphylococcus aureus. Nutrient agar was used for the direct colony identification of Staphylococcus aureus. Mannitol salt agar (MSA) and DNAse were used as selective media for the isolation of Staphylococcus aureus and incubated at 35˚C for 48 hrs.Resistance to methicillin was detected with cefoxitin(30 μg) through Disk Diffusion Test and interpreted according to (CLSI, 2009). A diameter of ≥22 mm was considered as susceptible and ≤21 mm as resistant as per (CLSI, 2010).Results: Out of 100 nasal swabs collected, 71 nasal swabs were from the dental surgeons and 29 were from the nursing staff, 35 (35%) showed a growth of Staphylococcus aureus. Among those who were positive for Staphylococcus aureus 62.85%were positive for MRSA. Overall 22 (22%) out of a 100 individuals came out to be positive for MRSA.Conclusion: Health care workers (HCWs) were the potential colonizers of methicillin resistant Staphylococcus aureus and may serve as reservoirs or disseminators of MRSA

The Mediating Role of Emotional Exhaustion in the Relationship between Abusive Supervision and Employee Cyberloafing Behaviour.

Cyberloafing is becoming a common problem in every organization that directly affects organizational productivity. In this study we are going to study the influence of abusive supervision on cyberloafing, further, we are studying the mediating effect of emotional exhaustion generated due to abusive supervision behaviour, motivating employees towards cyberloafing. The data were collected from 150 employees working in Saif Textile Mills Ltd & Kohat Textile Mills Ltd, Pakistan through questionnaires. The study sample was drawn using a convenience sampling technique. This study used SPSS 25 and process Hayes (2013) model 4 for data analysis and for model fitness we used CFA (AMOS 22). The data findings demonstrate that abusive supervision significantly and positively affects cyberloafing and also emotional exhaustion mediates this relation significantly. Therefore we conclude that abusive supervision is the main factor for employees to be exhausted and ultimately move towards cyberloafing. Based on these finding managers plays a vital role to maintain organization environment friendly

IMPACT OF SALES PROMOTION ON CONSUMER BUYING BEHAVIOR: A CASE OF MODERN TRADE, PAKISTAN

Rapidly changing market conditions and the competitiveness of market players is forcing the “all what you need one roof retail concept” businesses to look for various tactics to attract as well as retain customers through a number of sale promotion strategies. For that matter, this study tests the impact of various sale promotion strategies and its impact of consumer buying behavior. In order to do so, a quantitative research strategy has been followed, where the sample of 297 was collected by selecting walk-in customers at 25 supermarkets/hypermarkets in Lahore (Pakistan). Novelty of this study is the fact that, Modern Trade (MT) segment is being targeted only, MT refers to those retail stores who have an area of at least 1 Kannal (5445 sqft), have their own electronic billing system and trolley system. MT is further categorized in to Local Modern Trade (LMT) and International Modern Trade (IMT). Analysis through correlation and regression  modeling help to conclude that buy one get one free, price discounts and coupons are positively related with consumer buying behavior, whereas, free samples and bonus packs are not significantly related with the dependent variable

IMPACT OF SALES PROMOTION ON CONSUMER BUYING BEHAVIOR: A CASE OF MODERN TRADE, PAKISTAN

Rapidly changing market conditions and the competitiveness of market players is forcing the “all what you need one roof retail concept” businesses to look for various tactics to attract as well as retain customers through a number of sale promotion strategies. For that matter, this study tests the impact of various sale promotion strategies and its impact of consumer buying behavior. In order to do so, a quantitative research strategy has been followed, where the sample of 297 was collected by selecting walk-in customers at 25 supermarkets/hypermarkets in Lahore (Pakistan). Novelty of this study is the fact that, Modern Trade (MT) segment is being targeted only, MT refers to those retail stores who have an area of at least 1 Kannal (5445 sqft), have their own electronic billing system and trolley system. MT is further categorized in to Local Modern Trade (LMT) and International Modern Trade (IMT). Analysis through correlation and regression  modeling help to conclude that buy one get one free, price discounts and coupons are positively related with consumer buying behavior, whereas, free samples and bonus packs are not significantly related with the dependent variable

Exploring the role of risk and corruption on bank stability : evidence from Pakistan

Purpose – This paper aims to explore the impact of liquidity risk, credit risk, funding risk and corruption on bank stability of the banking system in Pakistan. Design/methodology/approach – The empirical analysis is confined to 24 retail banks, which include 5 Islamic and 19 conventional banks during the period of 2007-2015. Findings – The findings of this study suggest that bank size, liquidity risk, funding risk and corruption exert a positive impact on bank stability. Additionally, the authors find a negative relationship between credit risk and bank stability. Originality/value – As per the knowledge of the authors, the present research is the first attempt that discusses the issues of bank stability related to risk and corruption faced by the banking system

Person–Job Misfit: Perceived Overqualification and Counterproductive Work Behavior

Grounding on person–job fit theory, we examined perceived overqualification relation with counterproductive work behavior (CWB) by identifying job boredom as a mediator and job crafting as a moderator. Hierarchical linear regression and Hayes’ PROCESS macro-method were used to assess hypotheses in a three-wave survey of 317 textile sector employees. The findings show that perceived overqualification is positively related with CWBs. This study further examined the mediating function of job boredom and the moderating impact of job crafting in the association between perceived overqualification and CWB. The findings suggest that job crafting moderates the positive relation between perceived overqualification and job boredom and the indirect connection between perceived overqualification and CWB via job boredom. The model was tested using 3-wave data; however, since the data were attained from a single source, questions of common method bias cannot be ruled out. Managers should look for changes in employee attitudes and promptly modify employees’ positions when they indicate that they have more experience, abilities, and talents required for their roles in their organizations

The impact of disease control measures on the spread of COVID-19 in the province of Sindh, Pakistan

The province of Sindh reported the first COVID-19 case in Pakistan on 26(th) February 2020. The Government of Sindh has employed numerous control measures to limit its spread. However, for low-and middle-income countries such as Pakistan, the management protocols for controlling a pandemic are not always as definitive as they would be in other developed nations. Given the dire socio-economic conditions of Sindh, continuation of province-wise lockdowns may inadvertently cause a potential economic breakdown. By using a data driven SEIR modelling framework, this paper describes the evolution of the epidemic projections because of government control measures. The data from reported COVID-19 prevalence and google mobility is used to parameterize the model at different time points. These time points correspond to the government’s call for advice on the prerequisite actions required to curtail the spread of COVID-19 in Sindh. Our model predicted the epidemic peak to occur by 18(th) June 2020 with approximately 3500 reported cases at that peak, this projection correlated with the actual recorded peak during the first wave of the disease in Sindh. The impact of the governmental control actions and religious ceremonies on the epidemic profile during this first wave of COVID-19 are clearly reflected in the model outcomes through variations in the epidemic peaks. We also report these variations by displaying the trajectory of the epidemics had the control measures been guided differently; the epidemic peak may have occurred as early as the end of May 2020 with approximately 5000 reported cases per day had there been no control measures and as late as August 2020 with only around 2000 cases at the peak had the lockdown continued, nearly flattening the epidemic curve