User Specifications Research Articles

Online Inspection of Packed Cases

This paper presents a novel approach to automate the inspection process of packed agricultural cases using Artificial Intelligence (AI) and image processing techniques. The current manual inspection system, which assesses only 10% of packed cases based on subjective expert judgment, faces limitations such as inefficiency, subjectivity, and an inability to scale. The proposed solution leverages AI models and advanced image processing algorithms to perform real-time, automated inspections of packed cases. The system assesses quality based on predefined parameters like color, ripeness, and uniformity, as per customer specifications. This approach offers numerous benefits, including increased accuracy, scalability, cost reduction, and enhanced customer satisfaction. Keywords— Artificial Intelligence (AI), Image Processing, Online Inspection, Quality Control Automation, Agricultural Products, Real-Time Feedback, Machine Learning, Objectivity in Inspection, Automated Quality Assessment, Case Inspection.

Estimating the Generalizations of Process Capability Index Cpmk$C_{pmk}$ in the Presence of Outliers

ABSTRACTProcess capability indices (PCIs) play a fundamental role in assessing and quantifying the capability of manufacturing processes to meet customer specifications. To date, the majority of PCIs that are now in use have been examined through the use of novel generalizations of PCIs with symmetric tolerances to check the performance of an industrial manufacturing process. In this paper, we proposed new estimations of some indices with asymmetric tolerances in the presence of outliers. New robust and parametric estimators of some PCIs are introduced to estimate and compare these indices for each normal distribution with the presence of different outliers. Meanwhile, this paper discusses how well the proposed method can be used for non‐normal data. For illustration purpose, the application example is presented.

Advancing Multi-Level Production Defect Detection Using Quality Tools and Maintenance Optimisation

This study aims to advance the detection of production defects at three levels - part, material, and machine - through the application of a few quality tools with a view to proposing solutions. The research focuses on identifying and addressing the most prevalent and critical anomalies observed in the workshop. Despite existing quality control measures, production often falls short of meeting customer specifications due to machine malfunctions, inadequate operator vigilance, and inefficiencies in the maintenance processes. These challenges underscore the need for a systematic approach to visualise and address production system issues. By applying targeted quality tools, this paper seeks to optimize maintenance strategies and improve overall production performance, contributing to enhanced operational efficiency and product quality.© The Author(s) 2024. Published by RITHA Publishing. This article is distributed under the terms of the license CC-BY 4.0., which permits any further distribution in any medium, provided the original work is properly cited maintaining attribution to the author(s) and the title of the work, journal citation and URL DOI.

Improved of Process Production Disc Car Whell Type PSD3K (City Car Type)

This research accelerates the production process with the aim of increasing productivity from Manufacturers engaged in the manufacture of automotive parts currently experiencing an increase in sales orders on the other hand facing problems in productivity due to cracked side dies in rim production to 1400 pcs. The cracking of the side die is due to thermal shock that occurs to accelerate the production process, as a result of which cracks occur in the side die. With the concept of conducting research in the field of direct production then analyzing the characteristics of mold materials, die characteristics, process characteristics, characteristics of finished products before and after changes by testing the results of the laboratory of measuring instruments and conducting trials of variations in machine setting parameters, variations in the production process and products produced. The experiment involved changing the standard temperature from 520 °C–545 °C to 532 °C–538 °C and reducing the immersion time from a minimum of 270–540 seconds to 332 seconds. It reduces the soaking time from 69 seconds to 46 seconds and the aging time from 190 seconds to 180 seconds, increasing the casting productivity from 194,870 Pcs/28 days to 213,311 Pcs/28 days from seven machines, thus meeting the customer's requirement of 200,000 Pcs/28 days without cracking side die. Durability testing on five product samples in accordance with TSD5605G standards confirms that the quality meets customer specifications. The results of this study prove that SKD6 matrial is much stronger than FCD550 against thermal shock. Keywords: thermal shock, die disc car wheel, manufacturing, automotive parts, casting productivity

A Comparison of an Australian First Nations Primary Healthcare Data Specification with Potentially Preventable Hospitalisations.

Potentially Preventable Hospitalisations (PPH) is a widely used indicator of the effectiveness of non-hospital care. Specified using the International Classification of Diseases (ICD) coding, PPH comprises a suite of health conditions that could have potentially been prevented with appropriate care. The most recent edition of the National Guide to a Preventative Health Assessment for First Nations People documents the health conditions of interest to providers of primary care, many of which are not represented in PPH. Given the National Guide has been developed specifically with First Nations in mind, the aim of this research is twofold. The first aim is to formally posit the question of whether a summative measure of hospitalisations aligned diagnostically to the National Guide has value either as an alternative or complement to PPH in the context of First Nations primary health information. The second aim is to develop and present a prototype ICD-10 data specification for such a measure, referred to as the First Nations primary healthcare (FNPHC) data specification, and examine the age-standardised hospitalisation rates for FNPHC and PPH for correlations and/or differences. Age-standardised hospitalisation rates from 2016-17 to 2019-20 using both classifications were examined to assess the usefulness and relevance of summative measures of hospitalisations for informing primary care. Rates of FNPHC for principal diagnoses were between 1.5 and 2.5 times higher than those of PPH and approximately between 6 and 12 times higher for additional diagnoses. There was a strong correlation with PPH when rates were compared across all observations: jurisdictions with higher rates of PPH tended to have higher rates of hospitalisations according to the custom specification. Findings support its application as a summary measure for First Nations primary care providers. Given the policy landscape in Australia that aims to close the gap, it is imperative that measures of primary health take advantage of the concepts and application of First Nations data sovereignty and governance. The validity and cultural appropriateness of the First Nations primary health data specification needs to be further researched.

A Review Paper on the Crucial Factors that Influencing RMC Delivery Operation

The delivery process of ready-mix concrete (RMC) is a critical component in construction projects, influencing the quality, efficiency, and timeliness of concrete placement. This abstract explores the various factors that impact the RMC delivery process, ranging from logistical considerations to concrete properties and customer requirements. Key factors affecting RMC delivery include the distance to the construction site, traffic conditions, weather, regulatory constraints, batching plant operations, order volume, customer specifications, concrete mix design, truck capacity, and communication channels among stakeholders. Each of these factors can significantly influence the success of RMC delivery, posing challenges and opportunities for optimization.

Achieving customer specifications through process improvement using six sigma: case study of nutrisoil - Portugal

Os limites de tolerância mostram-se determinantes na gestão de um processo produtivo pois determinam a satisfação do consumidor. O uso das ferramentas do Controlo Estatístico de Qualidade permite uma melhoria do processo e o índice cpk possibilita a sua medição. Em especial, a adoção pelas empresas, da filosofia do Seis- Sigma tem-se mostrado determinante na redução da variação de um processo ou de um produto, permitindo satisfazer as especificações do consumidor, eliminar defeitos, reduzir os custos de operação, em suma aumentar a rentabilidade. A empresa NutriSoil em Portugal, comercializa sacos de fertilizante e tem vindo a ter problemas na secção de enchimento devido ao excesso de peso dos sacos em relação ao aposto nas especificações. Com a implementação da filosofia dos Seis-Sigma, a NutriSoil conseguiu uma melhoria do índice cpk, com a consequente melhoria da satisfação dos consumidores, e poupanças altamente significativas nos custos o que lhe permitiu aumentar a competitividade.

Enhancing side die resistance to thermal shock in automotive casting: a comparative study of FCD550 and SKD6 materials

Enhancement of side die resistance to thermal shock in mold disc car applications was achieved by substituting FCD550 material with SKD6 material. The primary issue addressed is the cracking of side dies due to thermal shock induced by an accelerated production process, leading to production halts and failure to meet large customer orders. The study aims to identify a material that can better withstand thermal shock than FCD550, thereby improving the durability of side dies and the overall productivity of the manufacturing process. The research involved direct production experiments, analyzing the materials FCD550 and SKD6, evaluating die characteristics, and assessing finished product attributes before and after material changes. Laboratory tests and machine-setting trials were conducted, varying production processes and assessing the results. The findings indicate that SKD6 is significantly more resistant to thermal shock than FCD550 in mold disc car applications. The study compared the strength of side die materials using data sheets and adjusted setting parameters under existing cooling conditions. Experimentation involved altering the standard temperature from 520 °C–545 °C to 532 °C–538 °C and reducing the soaking time from a minimum of 270–540 seconds to 332 seconds. This reduced soaking time from 69 seconds to 46 seconds and aging time from 190 seconds to 180 seconds, increasing casting productivity from 194,870 pieces/28 days to 213,311 pieces/28 days across seven machines, thereby fulfilling the customer’s requirement of 200,000 pieces/28 days without side die cracks. Durability testing on five product samples according to TSD5605G standards confirmed the quality as meeting customer specifications

Multi-objective design optimization of hermetically sealed core-type distribution transformer considering current harmonics of power grid using NSGA III

In this paper, the design optimization of hermetically sealed oil-immersed distribution transformers is studied. For the first time in the design of this type of transformer, harmonics of the power grid affecting the transformer design, along with all design variables, are included, and their boundaries suitable for the production line are determined. The design probability (search space) for a total of 21 design variables is 1.32×1025. The Brute Force method is not a time-efficient approach to finding the optimal result in this search space. Due to the mixed integer nonlinear programming (MINLP) nature of the transformer design problem, heuristic optimization algorithms are selected because of their shorter solution time and near-optimal results. Considering the principle of the “No Free Lunch” theorem, extensive evaluations were conducted on various heuristic algorithms to identify the most effective ones for addressing the transformer design problem. The most successful algorithms for solving the problem were identified after thorough evaluation, considering three distinct scenarios within a multi-objective optimization framework. These algorithms are namely MOEA/D, MOGWO, MOWOA, and NSGA III. In this study, an optimization tool is developed for the design optimization of hermetically sealed distribution transformers, covering a range from 50 kVA to 3150 kVA and encompassing all design variables. The developed optimization program is fully compatible with the production line and can be easily adjusted to meet all national and international standards, such as IEC and IEEE, as well as customer specifications.

Supply Chain Performance in the Manufacturing Sector: The Role of Lead-Time Management Strategies

The objective of this research was to evaluate the effectiveness of lead-time management strategies in influencing the operational efficiency of manufacturing enterprises. While prior studies have recognized lead time as a crucial factor impacting supply chain performance, scant attention has been paid to the specific contribution of lead-time management strategies in this context. Hence, this study aimed to bridge this gap. By employing a descriptive survey research design, data were collected from a sample of 153 manufacturing firms selected through purposive sampling. The primary data collection instrument was a structured questionnaire, and statistical analyses were conducted using SPSS software. The findings indicate that early involvement of suppliers in product design and dissemination of accurate customer specifications significantly reduces lead time. Process automation and efficient transport management, including route planning and vehicle scheduling, were found to enhance supply chain performance. Consequently, the study concludes that early supplier involvement, process automation, and effective transport management positively impact supply chain performance. Based on these findings, it is recommended that manufacturing companies prioritize initiatives aimed at reducing lead time, such as minimizing waiting times, engaging suppliers early in the process, automating processes, and improving transport management in order to enhance overall supply chain performance.

Projectized Community of Practice: A Case Study of Globally Distributed Information Technology Organization

The execution of globally distributed information technology service projects (GDITP) by globally distributed teams, while inherently complex, offers the advantages of swift implementation and seamless service delivery to global clients. The numerous challenges including the intangibility of customer specifications, the iterative nature of information technology (IT) activities and coordination difficulties arising from diverse teams contribute to complexity in managing these projects. Moreover, the organizational complexity is compounded by competing power centres, turning project delivery into a politically contested process. In traditional projects such as construction or customized manufacturing, overcoming aforementioned challenges through strong top-down leadership is typical in many time-bound projects. However, in the realm of IT projects, which are inherently people-centric, enforcing a command-and-control environment is challenging. Communities-of-practice (CoP) offer an alternative structure that engages highly skilled employees in a collaborative community, navigating the challenges posed by IT projects. Our study explores this innovative approach, focusing on a product firm effectively leveraging CoPs to successfully execute global service projects. Delving into the functioning of CoPs, our research illustrates how they scale up using both formal and informal networks to meet diverse global customer requirements. Despite operating globally, CoPs exhibit emergent collective mindfulness, adapting tools, processes and products to the demands of the projects. The study also details how the organization manages complexity while adhering to product architecture and a uniform project framework.

Powder characterisation and the impact on part performance in electron beam melted Ti6Al4V

Metallic powder for Additive Manufacturing (AM) typically varies between different batches, while being supplied to achieve the same customer specification. In order to reduce this variation and minimise waste, batches are often mixed together in both their virgin and used form. However, the properties of bulk components must have limited variance in order to be reliably used in an industrial setting. This manuscript is focused on the analysis of Grade 5 Ti6Al4V powders (3 virgin, plus 2 blends) and the associated mechanical properties of Electron Beam Melted (EBM) AM specimens. Measurements were performed in accordance with the principles defined in the MMPDS Handbook, ESDU database, and ASTM F2924. The tensile, and fatigue properties of the EBM specimens were found to be superior when compared with Ti6Al4V properties within these standards. This demonstrated that these powders are suitable for a wide range of commercial applications, and that these blended powders (including used powders) are able to achieve these requirements. Additionally, the results provide a systematic route for powder verification and highlight the importance of adhering to standardised principles and specifications to ensure quality and reliability in metallic AM materials.

Development of a tool for predicting oxides scales and tensile properties of Stelmor-cooled wire rod

In industrial practice, it is known that the wire rod coils need to be descaled before drawing. Acid pickling by hydrochloric or sulphuric acidic solutions is the most common method. However, mechanical descaling could be preferred. According to this choice, the oxides type and morphology shall be different. The oxides nature can be controlled by the Stelmor parameters, that is, the temperature at the laying head and the cooling rate on the Stelmor conveyor. International standards and customer specifications prescribe precise requirements not only for the scale features, but also for the material mechanical resistance and deformability. So, a complicated plant set-up is needed to satisfy all the requirements. This research work is aimed at developing processing maps for the correct selection of the Stelmor parameters able to guarantee the required mechanical strength and surface scale suitable for acid pickling or mechanical descaling.

Web-Based Measuring Instrument Calibration Scheduling Information System

The production method has prioritized guaranteeing excellent manufacturing quality in response to the increasing competitiveness in the clothing industry. Utilizing a fabric roll meter measuring instrument dramatically enhances the overall quality of the product by guaranteeing precise measurements. Roll meter fabric measuring equipment in the garment industry evaluates product accuracy based on customer specifications, ensuring exceptional quality. Effective regulation is essential for the management and upkeep of cloth roll meter measuring instruments. Therefore, it is necessary to develop a system that can evaluate the level of urgency for calibrating various equipment and identify those that need recalibration despite having already been calibrated. This project created a web-based system for scheduling the calibration of fabric roll meters. The system was designed using the PHP programming language and MySQL for database management. Use cases delineate how the user interacts with the system, whereas an activity diagram represents the sequence of user activities. Furthermore, a sequence diagram illustrates the user's participation in chronological order. The information system implements maintenance schedules, oversees the calibration of fabric roll meter measuring instruments, stores calibration certificates, and effectively handles calibration data to guarantee precision and efficiency.

A Study On Stress Management Among Employees Towards Alloy Industries With Reference To Coimbatore

In order to boost strength or corrosion resistance, two or more metallic components are mixed to form an alloy, which is a type of metal. A metallic material composed of two or more elements is called an alloy, sometimes known as a compound or a solution. Although the non-metal carbon is an essential part of steel, the constituents of alloys are normally metals. Alloys are often created by melting the mixture of components. According to customer specifications and drawings, Alloys Industries manufactures and exports a variety of machined and un-machined castings made of Carbon Steel, Stainless Steel, Low Alloy Steel, Heat Resistant Steel, Martensitic Stainless Steel (CA6NM), Precipitated Hardened Steel (CB7Cu-1), Nickel Alloy, and Duplex Stainless Steel. The phrase "stress managements" is broad and includes training, facilitation, and education about the effects that stress has on an individual or group. The study of stress management fosters and encourages the development of coping mechanisms. Employees' physiology and psyche are stressed out by organisational elements such management-labor relations, working conditions, resource distribution, the role of trade unions, employee behaviours, etc. The working practises and policies of an organisation are among its most important influencing variables. This study examined the occupational stress experienced by Alloy Industries in Coimbatore, employees in great detail.

A data-driven robust optimization in viable supply chain network design by considering Open Innovation and Blockchain Technology

The research proposes a new method for Viable Supply Chain Network Design (VSCND) that incorporates Open Innovation (OI) and Blockchain Technology (BCT). A robust stochastic optimization and Conditional Value at Risk (CVaR) in the cost function is utilized to develop the model. This model's objective function incorporates the expected value, maximum cost, and CVaR cost. The OI and BCT platforms are suggested for an antifragile policy against disruption. In addition, CO2 emissions and energy consumption are proposed as sustainability requirements. Eventually, minimum demand satisfaction and resilience facilities by incorporating capacity based on specific scenarios are added to the model for an agile strategy. This research entails several parties, including vendors supplying the primary components and manufacturers creating products based on customer preferences. OI and BCT platforms aim to receive demand based on customer specifications and facilitate rapid transactions between components. Risk-averse decision-makers utilize a polyhedral Data-Driven Robust Optimization (DDRO) approach to manage uncertainty and flexible sets. Incorporating OI and BCT as antifragility instruments resulted in a 0.2% cost reduction for VSCNDOIBCT compared to when OI and BCT were not considered. This research suggests that integrating OI and BCT positively affects SC performance overall. The decreasing rate, DDRO coefficient, agility rate, demand variation, and problem size were subjected to a sensitivity analysis.

Calculation of Mutual Inductance between Two Planar Coils with Custom Specifications and Positions Using a Machine Learning Approach

Wireless power transmission systems enable the transfer of electricity between grids without the use of physical wires. Different methods are employed for wireless power transfer, each suited to different distances. Inductive coupling, the subject of this study, is typically used for shorter distances. The effectiveness of inductive coupling systems is evaluated using a parameter called mutual inductance. In the present study, an attempt is made to provide a model for calculating mutual inductance in wireless power transfer systems using a machine learning approach. To achieve this goal, finite element simulations are employed, and 64 datasets are generated from mutual inductance calculations in various scenarios. These datasets are used to train machine learning regression algorithms, including linear regression, support vector regression, decision tree regression, and artificial neural networks. The evaluation results, using performance metrics such as R-squared, mean absolute error, and root mean square error, confirm that among these four algorithms, the artificial neural network exhibits higher computational accuracy with an R-squared value of 0.950 for predicting test data.

Optimisation of Capacitated Planned Preventive Maintenance in Multiple Production Lines Using Optimisation-in-the-Loop Simulation

In a mass customisation manufacturing system, the production schedule is tailored to the customer's specifications. However, the production system must be accompanied by an effective maintenance program to ensure that the production lines operate as intended. The purpose of this study is to optimise planned preventive maintenance across multiple production lines. An optimised Weibull distribution is proposed to model the machine's Mean Time Between Failures (MTBF), and the total expected maintenance cost is calculated using this distribution, taking into account the probability of the machines remaining operational and failing. Because the optimised Weibull distribution is a continuous distribution, in order to simulate the continuous time domain, it will be divided into several sub-systems and optimised using Bayesian optimisation during simulation. The maintenance scheduling is carried out by considering available time capacity after production scheduling was arranged. The study's findings indicate that the proposed method successfully optimised the planned maintenance schedule without interfering production activity with total cost for the proposed maintenance planning as low as IDR 50.017,75/maintenance unit time.

Car Purchase Based on Customer Specifications using Big Data Analysis: A Review

-This paper presents an in-depth and technical analysis of car purchases based on customer specifications, highlighting the crucial role of big data and data mining technology in the automobile manufacturing industry. By employing web crawlers and advanced algorithms, we extract valuable insights from customer reviews and sales data to optimize production and enhance customer satisfaction. The paper explores various data mining techniques and their impact on analyzing customer specifications, leading to tailored recommendations and improved market competitiveness. Key Words: big data, data mining, car purchase, customer specifications, web crawlers.

What factors impact the adoption of postharvest loss-reduction technologies in mangosteen supply chain?

As one of Indonesia's high-value export fruit commodities, mangosteen has the highest postharvest loss (PHL) value, which significantly affects the economy. This study investigates the determinants of technology adoption to reduce PHL and the challenges faced by supply chain actors in West Java Province, Indonesia. A structural equation model was employed to analyze the data gathered from farmers and middlemen. Additionally, in-depth interviews were conducted with exporters and modern market managers to obtain relevant information. The study found that capabilities, infrastructure, and financial access were the critical factors for farmers, whereas infrastructure and risk perceptions were identified as crucial for middlemen. The determinants of exporters’ adoption are customer specifications, food safety standards, and technology availability. Retailers, on the other hand, closely associated quality consistency requirements, buyer preferences, and risk considerations with technology adoption. This study proposes initiatives and policies to promote the adoption of technologies to reduce PHL in the mangosteen supply chain.