Data Mining for CNC Machine Adjustment Decision in Hard Disk Drive Arm Manufacturing: Empirical Study

Selection of a construction material is one of the important tasks in any construction project as it is influenced by many factors like cost, durability, eco friendliness, maintenance, availability, strengths, efficiency, etc. Initially, there is a trend where they used to consider only cost and efficiency factors in the selection of a construction material. Project executives face the difficulty to arrive at a reasonable decision considering all the other influencing factors. Different varieties of construction materials are available in the market with diverse properties; hence it becomes difficult to choose a particular type of material considering all parameters having importance. Here, we are using a simple methodology to make a selection of material on multiple attribute decision making (MADM) approach in place of the existing practice. MADM is making preference decisions (selecting, ranking, screening, prioritization, classification) over the available alternatives that are characterized by attributes. In order to select a material, a simple optimization method, Simple Additive Weighting (SAW) is used. This is also called as weighted sum method. It is the simplest and still the widest used MADM method.. By using SAW method the most suitable material can be determined. The result of this method is highly dependent on the weightages of attributes and may vary from time to time. This study will be useful as a decision making tool and for increasing the confidence in selecting the materials in big projects.

Decision-makers frequently use the MADM (Multiple Attribute Decision Making) method to assist in solving decision-making issues. This approach can use a variety of algorithms, including Simple Additive Weighting (SAW) and Weighted Product (WP). The challenge in this research is determining which of the SAW and WP approaches is more pertinent or acceptable for solving scenarios involving scholarship recipient selection. Five factors were taken into consideration when deciding who would receive a scholarship: academic achievement index (GPA), parents' income, past accomplishments, participation in student organizations, and the number of parents' dependents. A sensitivity test, which involves altering the weight of each test method's criterion and then comparing the percentage change between the two ways, is one method that can be used to gauge the effectiveness of the MADM method. The SAW method implementation results show that alternative nine (MHS9) has the highest preference value, which is 0.95. The WP method implementation results show that alternative nine (MHS9) has the highest preference value, which is 0.12. The total change in the findings of the sensitivity test for the SAW method is 7.64%, compared to 2.06% for the WP method. Thus, it can be inferred that the SAW approach is thought to be pertinent for addressing the issue of choosing scholarship applicants.

Water is the basis of life, the foundation of nature, and the pillar of social, economic, and cultural development of societies. So, the supply of safe and consumable water has always been a concern. On the other hand, a major challenge of modern societies is the lack of precipitation and frequent droughts. Thus, the present paper assesses the principles of water governance in the Sistan region with respect to the development of water exploitation systems with an environmental approach and presents an integrated multi-attribute decision-making model with a water governance approach in the Sistan region. The simple additive weighting (SAW) method that is used here is one of the multiple attribute decision making (MADM) methods. The indicators of water governance principles were derived from the opinions of 30 water experts, faculty members, and water users in the Sistan region by the SAW method, and weights were assigned to them to form MADM matrices. According to the results, six indicators were derived as the indicators determining the principles of water governance. ‘Traditional users’ was selected as the strongest system and ‘irrigation and drainage networks exploitation companies’ as the weakest system. Also, according to the results of water experts, the first rank was assigned to ‘irrigation and drainage networks exploitation companies’ (A2) with the final crisp score of 6.818 followed by ‘water user cooperatives’ (A4) with the final crisp score of 6.515 in the second rank and ‘private firms’ (A6) with the final crisp score of 6.308 in the third rank.

Determining the “best” operationally responsive spacelift system is a classic case of competing objectives. Cost versus respon siveness in the simplest terms, with the effects of performance requirements also requiring consideration. This paper examines the application of multiple attribute decision making (MADM) techniq ues to alternative designs for Operationally R esponsive Spacelift (ORS) systems . Five different types of MADM techniques are app lied to this problem. They are D ominance, Maximin , Simple Additive Weighting, TOPSIS, and the Median Ranking M ethod. After apply ing MADM techniques, no clearly preferred ORS configuration c ould be identified from among the options that were considered .

Many decision making problems of business and management are formulated in terms of Multiple Attribute Decision Making (MADM): given a set of alternatives evaluated with multiple criteria, find the alternative which according to the Decision Maker (DM), has the most preferred combination of criteria values (attributes), or rank alternatives from the most preferred one to the least preferred one. The MADM methods incorporate mechanisms of building preference models based on information obtained from the DM. In a wide variety of such methods, the DM is supposed to provide information in terms of weights of criteria, usually understood as criteria’s priorities. These weights serve as parameters of the method-pecific preference models. The DM can define weights directly, or by using special weight elicitation techniques such as AHP, MAVT and others. Our concerns are that when using weight-based methods, the DM cannot ensure the correctness of the preference model. First, different weight-based methods use different kinds of preference models, which prioritize criteria based on weights in different manners. Second, interpretation of weights in some MADM methods is far from intuitive. Thus, a situation may occur when an inexperienced DM thinks of weights differently than they actually work in the method, and expresses the preference information incorrectly. In this paper we demonstrate the differences between how weights are interpreted in several methods: simple additive weighting, TOPSIS, VIKOR and PROMETHEE. We do it by comparing rankings produced with methods based on randomly generated data. We demonstrate that differences of interpreting weights significantly contribute to differences in produced rankings. A solution to this problem could be twofold: first, increasing awareness of differences between method-specific weight-based prioritizing mechanisms, and second, providing interpretations of weights for popular methods in the language understandable by the DMs.

An approach using defuzzifying methods is proposed for the fuzzy multiple attribute decision-making (MADM) problems. The computing effectiveness of the proposed defuzzifying methods combined with the simple additive weighting (SAW) method and the technique for order preference by similarity to ideal solution (TOPSIS) method are evaluated based on a comparison to the improved fuzzy weighted average (IFWA) followed by a ranking method. Both SAW and TOPSIS methods are two of classic MADM methods. The purpose of this application is to make the method easier to program and data easier to manipulate. This results in a more practical method for fuzzy decisions. A numerical example and experiment are discussed to demonstrate the implementation of the methods in different input conditions.

Spectrum decision is an important functionality of a cognitive radio terminal, which allows the selection of the appropriate frequency band from the available underutilized spectrum. Spectrum decision conducts itself in accordance to the communication requirements of the secondary (or cognitive) users in the forthcoming Cognitive Radio Networks (CRNs). Selecting the best spectrum for a given transmission involves making preference decisions over the set of available alternatives of frequency bands, which are indeed characterized by different attributes. Therefore, spectrum decision can be modeled as a multiple attribute decision making (MADM) problem. In this paper, we evaluate the performance of MADM decision algorithms such as Simple Additive Weighting (SAW), Technique for Order Preferences by Similarity to Ideal Solution (TOPSIS) and the Compromise Ranking Method VIKOR for spectrum decision. The study, however, is conducted using real spectrum occupancy measurements to evaluate the performance of the aforementioned algorithms in a practical scenario. Some important attributes of underutilized spectrum are proposed for consideration in the decisions. Results show that SAW algorithm performs well for the preferred spectrum attributes in the selected scenarios, while offering a good performance also in other parameters.

The rapid development of information technology makes internet access an important requirement in many aspects. The COVID-19 pandemic has also become the basis for the increasing use of internet access, especially in the education sector. Restrictions activities outside the house, causing the productivity of students to decline. Therefore, in order to remain active and productive, students are required to follow an online learning system. This will make the use of internet quota even greater. The number of cellular providers that provide internet services sometimes makes users confused in determining which provider is better to use. In this study, the Multiple-Attribute Decision Making (MADM) - Simple Additive Weighting (SAW) methods used to identify the decision support system in determining the type of cellular provider that is the most popular among students, especially in the Griya Martubung Area. This decision support system can certainly meet the needs of internet quotas and budgets. The results show that the most popular providers are Three, followed by Telkomsel, XL Axiata, Smartfren and Indosat.

Development of irrigation networks is a crucial element in increasing the efficiency and effectiveness of water distribution for agriculture. This research aims to determine priorities for developing irrigation networks in the Bedadung Irrigation Area, Jember Regency, using the Multiple Attribute Decision Making (MADM) method. This method consider various criteria influencing decision-making, such as physical condition of the channel, land area, water requirements, and level of infrastructure damage. This research involved collecting primary and secondary data through field surveys, interviews with interpreters, as well as reviewing technical and administrative documents related to irrigation networks. Data was analyzed using several MADM techniques, such as Simple Additive Weighting (SAW), Weighted Product (WP), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to obtain the weight of each criterion and determine development priorities. The results show that the main priority for developing irrigation networks in the Bedadung Irrigation Area is repairing primary, secondary, and tertiary canals that are badly damaged, followed by increasing canal capacity to meet water needs in the dry season. Implementation of the results of this research is expected to increase the efficiency of irrigation water distribution, reduce water losses, and increase agricultural productivity.

This experimental study investigated the physical model of a 180-degree river bend to introduce a new measure called as winged bandal-like (WBL) structure for river bed sediment management. The new structure is a combination of bandal-like (BL) and triangular vane structures. Nine different alternatives of the WBL structure, including three dimensionless vane effective lengths and three different vane angles, were tested in non-submerged and clear water conditions. A total of 18 attributes were then defined in accordance with the resulting river bed scouring and deposition. The multiple-attribute decision-making, simple additive weighting, and TOPSIS methods were employed to rank the alternatives. Baseline tests were also carried out for the BL and the impermeable spur dike (ISD) structures under similar flow conditions. Results revealed that the maximum scour depth, as the main cause of failure around the considered WBL structure, decreased by 31% compared to the scour around the ISD. The maximum deposition height behind the considered WBL structure showed an increase of 47% and 96% in comparison with ISD and BL structures, respectively. In the WBL structure, a longer, better-shaped sedimentary stack was developed along and close to the outer bank.

Tracking customer preferences is an important aspect of business success. Having information on hand about most favorite food is a key success for everyone who takes apart in the culinary business. Exact sales data on certain food is hardly available to the public. Restaurant owner tends to keep their data for their own business strategy. Therefore, generating a food trend in a certain community is hardly possible using food sales data. This paper discussed extracting food general trend from social media, with the case study on Twitter data with a certain regional area of interest. Social media provides a tremendous amount of data including people choice of food when they visit the certain place. However, the available data is unstructured in human language. The challenge is twofold: to grasp the meaning and extract the relevant information to the food trends. We proposed a bag of words technique to gather relevant information in the Indonesian language for feature extracting purpose. While K-mean Clustering and Simple Additive Weighting (SAW) algorithm are proposed to draw up the food rank. In order to measure the accuracy, we compare our result with the sales data of some restaurants in Yogyakarta. We test the algorithm using 4 weeks of data, the result is compared against the available data and an accuracy of 72.75 % is achieved.

There are many different uses for the data that comes from a measurement. With the advent of new testing methodologies, data has become finely granular—allowing for precise analysis of the properties and performance of materials, geometries, and even simulations. Raw measurement data can be retained and compared directly to the output of complex acoustic models for development, improvement, evaluation, and eventually a form of calibration. Advances in technology are rapidly removing the limitations of computational power needed to create accurate models of acoustic phenomena in a timely and efficient manner. This allows a progression from limited particle simulations on single workstations, to large scale wave-based simulations using cloud-based GPU computing clusters. Performance will be evaluated, comparing their output to laboratory measurements, with the goal of creating better tools for acoustic design, prediction, experimentation, and development.There are many different uses for the data that comes from a measurement. With the advent of new testing methodologies, data has become finely granular—allowing for precise analysis of the properties and performance of materials, geometries, and even simulations. Raw measurement data can be retained and compared directly to the output of complex acoustic models for development, improvement, evaluation, and eventually a form of calibration. Advances in technology are rapidly removing the limitations of computational power needed to create accurate models of acoustic phenomena in a timely and efficient manner. This allows a progression from limited particle simulations on single workstations, to large scale wave-based simulations using cloud-based GPU computing clusters. Performance will be evaluated, comparing their output to laboratory measurements, with the goal of creating better tools for acoustic design, prediction, experimentation, and development.

This study presents the development and implementation of a Patient Management System (PMS) at Noura Aesthetic Clinic using the Fuzzy Multiple Attribute Decision Making (FMADM) method with Simple Additive Weighting (SAW). The aim is to enhance the decision-making process for patient treatment prioritization and management. The PMS integrates various patient attributes, including medical history, treatment urgency, and resource availability, into a comprehensive decision-making framework. By employing the FMADM method, the system addresses the inherent uncertainties and subjectivities in patient data, ensuring more accurate and reliable prioritization. The SAW technique further refines this process by assigning weighted scores to each attribute, facilitating a straightforward and effective comparison. This combination allows for a balanced assessment of multiple factors, promoting optimal resource allocation and improving overall patient care. The implementation at Noura Aesthetic Clinic demonstrated significant improvements in operational efficiency and patient satisfaction. The system's adaptability to diverse clinical settings and its user-friendly interface make it a valuable tool for healthcare providers. This study underscores the potential of advanced decision-making methodologies in transforming patient management practices, paving the way for more informed and equitable healthcare delivery.

Stock investment is an attractive option for modern society to enhance long-term asset value, despite significant risks, especially for novice investors who often face limited understanding of fundamental stock analysis. Such analysis involves various complex financial indicators. This study combines the Fuzzy Multiple Attribute Decision Making (FMADM) method and the Simple Additive Weighting (SAW) method to assist investors in selecting the best stocks in the banking sector. FMADM is applied to address data uncertainty using a fuzzy approach, while SAW calculates the final score based on criteria weights and performance. The research data were obtained from company financial reports for the 2019–2023 period, focusing on seven key criteria: Return on Assets (ROA), Return on Equity (ROE), Earnings Per Share (EPS), Net Profit Margin (NPM), Price-to-Book Value (PBV), Debt-to-Equity Ratio (DER), and Dividend Yield (DY). The study aims to develop a decision support system to simplify the investment analysis process while reducing the risk of decision-making errors for investors. The findings indicate that alternative A35/Bank BTPN Syariah (BTPS) ranked first with a final score of 0.7120, followed by A42/Bank Mega (MEGA) in second place with a score of 0.7074, and A08/Bank Central Asia (BBCA) in third place with a score of 0.6988. This system provides a practical solution for more structured and efficient investment decisions.

Historically, in dipmeter analysis, depositional patterns are delineated for environmental, structural, and stratigraphic interpretations. The proposed method is a more fundamental approach, which uses raw data measurements from the dipmeter sonde to aid the geologist or log analyst in describing subsurface structures on a stratigraphic scale. Raw data are available at the well site, require only a basic understanding of sedimentary features and facies, and can be combined with computed results. A case study illustrates the reconstruction of sedimentary features from a raw data log recorded by a six-arm dipmeter. The dipmeter is a wireline tool with a series of evenly spaced focused electrodes applied to the circumference of the borehole wall. The raw data are presented as curves representing the electrode response and tool orientation. In outcrop, the geologist can often see an entire sedimentary feature in 3 dimensions relative to its depositional environment. Therefore, a large range of features can be resolved. However, in the borehole environment the perspective is reduced to the borehole diameter, thus reducing the range of recognizable features. In this study, a table was assembled that identifies the features distinguished by the proposed method as a function of borehole diameter. End_of_Record - Last_Page 163-------