Narrow Results

In this work, three passive techniques (ferrofluid, porous zone, curved surfaces) have been merged with one active technique (electric force) to enhance the convective rate. The permeable enclosure contains two curved walls and two straight walls which are not stationary. The concentration of ferrofluid within the domain is constant and associated formulations for properties of ferrofluid have been applied in modeling in which no slip velocity exists among particles. With define, measure, analyze, improve and control (DMAIC), the vorticity equation for partial equations which contain the source terms of electrohydrodynamic (EHD) and permeability, final equations have been achieved and for finding the solution combination of two basic techniques were utilized. Low deviation with a prior article in the validation procedure indicated a good agreement. Nu can augment around 0.49% if platelet particles were applied rather than sphere. Utilizing radiation in simulation makes Nu augment around 82.27%. Elevating Da in the absence and appearance of EHD leads to an augment of Nu around 145.01% and 393.38%. Appearance of EHD enhances the Nu about 96.04%.

The process of selecting requirements for a release of a software product is challenging as the decision-making is based on uncertain predictions of customer value and development cost. This paper presents a method aimed at supporting software product development organisations in the identification of process improvement proposals to increase requirements selection quality. The method is based on an in-depth analysis of requirements selection decision outcomes after the release has been launched to the users. The method is validated in two separate case studies involving real requirements and industrial requirements engineering experts. The conclusions from the two case studies are that the method seems valuable in situations with complex release planning decisions, such as in market-driven projects. It also appears essential that participants with different viewpoints attend the root cause discussion. Requirements interdependencies seem to play a big role in release planning decision-making. In addition, successful projects can also be a source of learning.

The automotive industry is facing a tremendous growth in the engineering of software-intensive systems, giving rise to various challenges. To prevent problems related to the fit of new software technologies in vehicles and the manufacturing processes, a well functioning interaction between the functions for product development and manufacturing is crucial. This is complicated by the fact that the changeable nature of software development causes unprecedented needs for collaboration and coordination between these two functions. This paper reports on a process assessment that focuses on the interface between the functions for product development and manufacturing in the development and design of software-intensive automotive systems. The main purpose of the study was to identify the key issues for improvement in the area assessed. The assessment was performed at two Swedish automotive companies where data were collected from documents and in interviews with practitioners. Nine key improvement issues were established ranging from challenges in requirements engineering to the need for knowledge transfer between manufacturing and product development. In addition, to increase the understandability of the results and map possible avenues for solution and future research, the paper provides an extensive analysis of each improvement issue in relation to the state-of-the-art.

Software development with its unique characteristics having knowledge-intensive and human-oriented aspects and complex domains, challenges organizations. The timely outcomes with high quality and desired cost that directly affect customer satisfaction have an important place in many organizations, including banks. In the last decade, as an emerging technique for business processes management, process mining has been applied in many domains, including manufacturing, supply chain, government, healthcare, and software engineering. There are limited number of studies on process mining techniques carried out for the software process, especially in the banking sector. A lack of tool infrastructure enabling to run the entire software development process and the challenges in integrating processed data from separated varying tools and assets complicate the use of process mining for software processes. This paper aims to identify the improvement points in the software development process of the Kuveyt Turk Participation Bank in Turkey through the surfacing actions. The findings and results are gathered by the application of process mining techniques of bupaR, and evaluation is provided by experts in the bank. After that, the relevant process improvements are identified. The results of this paper show that using process mining provides the organization with beneficial results, in particular, and a comprehensive view of the end-to-end Software Development Life Cycle (SDLC) processes.

With the rapid development of information technology, enterprise digitalization, and Internet + application, the digitalization and improvement of the used car trading business and its management process improvement are facing many challenges. This paper attempts to use the CMMI process improvement model to analyze the factors affecting the digital construction, business process optimization, and digital management process improvement of the used car market through research on the digital management process and the related theories of CMMI, such as talent training, application of information technology, immature business development, irregular business process, and industry policy restriction. The FAHP analysis method is used to establish a comparison matrix to explore the construction of an evaluation system model for the improvement of the digital management process of the used car trading market based on the CMMI model.

Knowing when a process has changed would simplify the search for and identification of the special cause. In this paper, we compare the maximum likelihood estimator (MLE) of the process change point (that is, when the process changed) to built-in change point estimators from binomial CUSUM and EWMA control charts. We conclude that it is better to use the maximum likelihood change point estimator when a CUSUM or EWMA control chart signals a change in the process fraction nonconforming. The results show that the MLE provides process engineers with an accurate and useful estimate of the last subgroup from the unchanged process.

Statistical process control charts are intended to assist operators in detecting process changes. If a process change does occur, the control chart should detect the change quickly. If the operator is provided with an estimate as to when the process changed, the search to find the special cause can be more easily facilitated. We investigate a process-monitoring tool for Poisson count data that quickly responds to process mean count rate changes regardless of the magnitude of the change, while supplying useful diagnostic information. A likelihood ratio approach was used to develop a control chart for a permanent step change in a Poisson process rate parameter. The average run length (ARL) performance of this chart is compared to that of several Poisson cumulative sum (CUSUM) control charts. Our performance results show that the proposed chart performs better than any one CUSUM chart over a wide range of potential shift magnitudes. The proposed chart also provides maximum likelihood estimates of the time and the magnitude of the process shift. These crucial change point diagnostics can greatly enhance the special cause investigation.

In recent years, software development has become more large-scaled, complicated, and diversified. At the same time, customer requirement of high quality and shortened delivery has increased. Therefore, we have to manage process quality and control product quality in the early-stage of software development in order to produce highly quality software products during the limited period. In this paper, we conduct multivariate linear analyses by using process monitoring data, derive effective process factors affecting the final product quality, and discuss the significant process factors with respect to software management measures of quality, cost, and delivery (QCD). Then, we discuss project management on the significant process factors affecting QCD and show its effect on QCD.

In this article, agent based process management model is proposed, which is for the process management of knowledge worker and service workers in order to establish the basis for the new knowledge management system. In this article, we applied several methods from 6-Sigma and personal software process for personal process definition, process execution and process measurement. This study attempts to improve the process execution accuracy through process visualisation and standardisation and to accumulate the base data to improve the process through measuring the process execution. We proposed guidelines and detail procedures for developing three advisor agents for guiding the process definition, process execution and process measurement. We showed the simple case study applied our guidelines.

Ultrasonic tube forming is an innovative and promising technology that could replace the conventional thermoforming process for plastic automotive tubes. This process allows for the forming of extruded tubes four times faster, with a substantial increase in energy efficiency. This research focuses on the experimental study of this innovative process and its comparison to the conventional thermoforming in a hot air table. A prototype has been designed and assembled to study the main process variables that are significant to the forming result. A complete design of experiments (DOE) has been applied to quantify the effect of each process parameter, thereby obtaining a mathematical model that allows for the prediction of the curvature angle for a specific parameter combination. It has been concluded that the application of ultrasonic cycles, with short cooling cycles in between, is the best option, in comparison to a continuous application. The amplitude of vibration, ultrasonic time for the cycle, and number of cycles have proven to be the most significant variables of the process. Furthermore, the cooling time between cycles and the position of the squares for the initial bending angle are also important parameters that can be set up to refine the result. Quality control tests related to material degradation and geometry have been passed successfully, showing a high stability of the results. Consequently, this new process has a promising place in the future of plastic tube forming.

Catalysts containing manganese as the primary active component have emerged as promising candidates for ultra-low temperature NH₃-SCR applications. To enhance the catalytic activity of these catalysts, a series of Mn-FeO_X catalysts were prepared using the co-precipitation method. This study focuses on investigating the appropriate calcination process for catalyst preparation using different precipitants, namely NaOH, NH₃-H₂O and Na₂CO₃. The results revealed that catalysts prepared with Na₂CO₃ as the preferred precipitant and calcined at 330∘C exhibited exceptional NOx removal efficiency, exceeding 90% at a temperature of 60∘C and GHSV $=$ 30,000h${}^{-1}$, which demonstrated this catalyst’s remarkable low-temperature reduction capability. Detailed characterization demonstrated that the MnO_X catalysts synthesized through this process possessed an amorphous structure, superior pore structure and the highest Fe${}^{3+}$ content. These findings offer valuable insights for optimizing the preparation conditions of Mn-FeO_X catalysts in ultra-low temperature denitrification applications.

One of the most valuable assets of an organization is its organizational data. The analysis and mining of this potential hidden treasure can lead to much added-value for the organization. Process mining is an emerging area that can be useful in helping organizations understand the status quo, check for compliance and plan for improving their processes. The aim of process mining is to extract knowledge from event logs of today’s organizational information systems. Process mining includes three main types: discovering process models from event logs, conformance checking and organizational mining. In this paper, we briefly introduce process mining and review some of its most important techniques. Also, we investigate some of the applications of process mining in industry and present some of the most important challenges that are faced in this area.

“Knowledge” is one of the main results of software engineering, software projects and software process improvement. During software engineering projects, developers learn to apply certain technologies and how to solve particular development problems. During the process of software improvement developers and managers learn how effective and efficient their development processes are, and how to improve these processes. As “learning” is so important in software practice, it is logical to examine it more closely. What is learning? How does learning take place? Is it possible to improve the conditions of learning?

This chapter presents an overview of learning theories and the application of these theories in the software-engineering domain. It is not our intention to be complete; our objective is to show how established learning theories can help to facilitate learning in software development practice.

In order for automotive parts enterprises to stand out in a competitive market and capture a greater market share, they must both improve quality and reduce production cost. Lean Six Sigma management applies the speed of Lean and the quality of Six Sigma to solve these enterprises' problem. By analyzing the Lean Six Sigma management model, this paper improves the specific process of Lean Six Sigma. Further, the Lean Six Sigma management theory is applied to improve and optimize the problem of low efficiency on ABS connector production line in an automotive parts enterprise. This leads to the net result of an improved production line OEE (Overall Equipment Effectiveness) and a shortened Lead Time, in conjunction with large cost savings.

One of the most valuable assets of an organization is its organizational data. The analysis and mining of this potential hidden treasure can lead to much added-value for the organization. Process mining is an emerging area that can be useful in helping organizations understand the status quo, check for compliance and plan for improving their processes. The aim of process mining is to extract knowledge from event logs of today’s organizational information systems. Process mining includes three main types: discovering process models from event logs, conformance checking and organizational mining. In this paper, we briefly introduce process mining and review some of its most important techniques. Also, we investigate some of the applications of process mining in industry and present some of the most important challenges that are faced in this area.

Due to the advantages of the centralized procurement of materials in the AEC industry, the number of emerging logistics enterprises has been on a rise in recent years in China. According to the manner of payments in construction projects, such logistics enterprises play the role of purchasing the construction materials for projects under construction by advancing funds. However, redundant processes in construction logistics enterprises result in massive funds being piled up and lower efficiency, which usually weakens the advantages of the centralized procurement. Therefore, this chapter presents a case study on the process improvement to identify the appropriate method to eliminate the valueless process in centralized procurement and improve the productivity in the construction logistics enterprise. Six Sigma is an advanced self-control process that aims to produce or deliver near-perfect products and services, which is implemented in this chapter by integrating DMAIC approach and flow chart. Taking account of the distinct properties between the AEC industry and the manufacturing industry, this chapter first constructs the configuration of construction logistics under centralized procurement, which facilitates the process differently from that existing in most previous researches. The current process in a construction logistics enterprise is represented in the flow chart format. Then according to the flow chart in practice, the process improvement is achieved by using DMAIC approach containing five basic steps. Finally, a case study is used to verify the performance of the improved process by comparing it with the existing process. The entire process time and the actual work time have been reduced by 52% and 53%, respectively, in this case.