Optimum profit model based on order quantity, product price, and process quality level

When all of the one-sided specification indices of each quality characteristic reach the requirements of the process quality level, they can ensure that the process capability of the product meets the requirements of the process quality level. This study constructs a fuzzy membership function based on the upper confidence limit of the index, derives the fuzzy critical value, and then labels the fuzzy critical value on the axis of the visualized radar chart as well as connects adjacent critical points to shape a regular polygonal critical region. Next, this study calculates the observed value of the index to estimate and mark it on the axis for forming a visualized fuzzy radar evaluation chart. Obviously, this fuzzy evaluation model not only reduces the testing cost but also makes the quality level quickly meet the requirements of the specifications. Further, the radar chart can reduce the risk of misjudgment attributable to sampling errors and help improve the accuracy of evaluation by a confidence-upper-limit-based fuzzy evaluation model. Therefore, this easy-to-use visualized fuzzy radar evaluation chart is used as an evaluation interface, which has good and convenient management performance to identify and improve critical-to-quality quickly. Improving the quality of the process before the product is completed will also have the advantage of reducing social losses and environmental damage costs.

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On the Entropic Order Quantity Model Based on the Conformable Calculus

Progress in Fractional Differentiation and Applications ◽

10.18576/pfda/070405 ◽

2021 ◽

Vol 7 (4) ◽

pp. 263-273

Keyword(s):

Order Quantity ◽

Model Based ◽

Conformable Calculus

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The Business Model Analysis of Service-Oriented Enterprise

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.701-702.1257 ◽

2014 ◽

Vol 701-702 ◽

pp. 1257-1262

Author(s):

Li Wang ◽

Jing Zhang

Keyword(s):

Business Model ◽

Resource Integration ◽

Value Proposition ◽

Network Resources ◽

Customer Demand ◽

Profit Model ◽

Related Literature ◽

Value Network ◽

Model Based ◽

Service Oriented

In this paper, we proposed value proposition, value network, resources, services and profit model as business model elements of Service-oriented Enterprise from the perspective of system by combing the related literature about business model elements. Based on this, we put forward four kinds of building ideas: business model based on customer demand, business model based on resource integration, business model based on service content, business model based on profit model and then explained by cases. Finally, the application of environmental of business model was compared. This study is help to guide other service-oriented enterprises to construct business model effectively.

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Productivity Increase – Model-based optimisation of NC-controlled milling processes to reduce machining time and improve process quality

IFAC-PapersOnLine ◽

10.1016/j.ifacol.2019.11.463 ◽

2019 ◽

Vol 52 (13) ◽

pp. 1803-1807 ◽

Cited By ~ 2

Author(s):

C. Brecher ◽

M. Wiesch ◽

F. Wellmann

Keyword(s):

Process Quality ◽

Machining Time ◽

Model Based ◽

Productivity Increase

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The Fuzzy Process Quality Evaluation Model for the STB Quality Characteristic of Machining

Applied Sciences ◽

10.3390/app10228272 ◽

2020 ◽

Vol 10 (22) ◽

pp. 8272

Author(s):

Win-Jet Luo ◽

Kuen-Suan Chen ◽

Chun-Min Yu ◽

Ting-Hsin Hsu

Keyword(s):

Machine Tool ◽

Evaluation Model ◽

Quality Characteristics ◽

Process Quality ◽

Quality Characteristic ◽

Quality Level ◽

Sampling Errors ◽

Statistical Process ◽

Accuracy And Precision ◽

Fuzzy Process

Whether it is important components of a machine tool itself or various important components processed by the machine tool, many vital quality characteristics mostly belong to the smaller-the-better type. When the process quality levels of these quality characteristics do not attain to the criteria, friction loss may increase during the machine operation, affecting not only the process precision and accuracy but also the lifetime of the product. Therefore, this study applied a smaller-the-better six-sigma quality index simultaneously demonstrating process quality level and process yield. Besides, in coping with statistical process control data, a one-tail confidence-interval-based fuzzy testing method was developed to evaluate process quality. Because this approach is built on the basis of confidence intervals, it can reduce the possibility of misjudgment resulting from sampling errors as well as integrate past experience to enhance the accuracy and precision of the assessment, and then it can grasp the timeliness of improvement.

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