Accurate Calculation of Process Capability Indices Considering the Skewed Distribution

Two simple, easy and correct process capability indices are presented in this paper which is based on the investigation of the actual management situation of manufacture process in the medium or small enterprise of our country, and the applicability analysis for the evaluating methods of process capability. The coincidental degree of distribution center between the product quality and the spec tolerance is considered in the method, and the parameter of actual standard deviation is used. So the indices have higher accuracy and reflect the essential aspect of the problem.

Modified Multivariate Process Capability Index Using Principal Component Analysis

The existing research of process capability indices of multiple quality characteristics mainly focuses on nonconforming of process output, the concept development of tmivariate process capability indices, quality loss function and various comprehensive evaluation methods. The multivariate complexity increases the computation difficulty of multivariate process capability indices（MPCI）, which makes them hard to be used in practice. In this paper, a new PCA-based MPCI approach is proposed to assess the production capability of the processes that involve multiple product quality characteristics. This approach first transforms the original quality variables into standardized normal variables. MPCI measures are then provided based on the Taam index. Moreover, the statistical properties of these MPCIs, such as confidence intervals and lower confidence bound, are given to let the practitioners understand the capability indices as random variables instead of deterministic variables. A real manufacturing data set and a synthetic data set are used to demonstrate the effectiveness of the proposed method. An implementation procedure is also provided for quality engineers to apply our MPCI approach in their manufacturing processes. The case studies demonstrate the effectiveness and feasibility of this new kind of MPCI, which is easier to be used in production practice. The proposed research provides a novel approach of MPCI calculation.

Combining the People Power and the Process Power to Achieve Six Sigma Process Capability——A Case Study

Achieving Six-Sigma process capability starts with l istening to the Voice of the Customers, and it becomes a reality by combining th e People Power and the Process Power of the organisation. This paper presents a Six-Sigma implementation case study carried out in a magnet manufacturing compa ny, which produces bearing magnets to be used in energy meters. If the thickness of the produced bearing magnets is between 2.35 mm and 2.50 mm, they will be ac cepted by the customers. All the time the company could not produce the bearing magnets within the specified thickness range, as their process distribution was flat with 2.20 mm as lower control limit and 2.60 mm as upper control limit. This resulted in a huge loss in the form of non-conformities, loss of time and goodwill. The process capability of the company then was around 0.40. Organisat ion restructuring was carried out to reap the benefit of the People Power of the organisation. Statistically designed experiments (Taguchi Method based Design o f Experiments), Online quality control tools (Statistical Process Control To ols) were effectively used to complete the DMAIC (Define, Measure, Analyse, Impr ove and Control) cycle to reap the benefit of the Process Power of the organisat ion. Presently the company enjoys a process capability of 1.75, a way towards Si x-Sigma Process Capability.

Integrated Process Capability Analysis

Process Capability Analysis (PCA) is a powerful too l to assess the ability of a process for manufacturing product that meets specific ations. The larger process capability index implies the higher process yield, a nd the larger process capability index also indicates the lower process expected loss. Chen et al. (2001) has applied indices C pu, C pl, and C pk for evaluating the process capability for a multi-process product wi th smaller-the-better, larger-the-better, and nominal-the-best specificati ons respectively. However, C pk cannot reasonably reflect the process expected loss. In this paper, index C pn is selected to replace C pk. Indices C pu, C pl, and C pn are used to evalu ate the entire process capability for a multi-process product with smaller-the -better, larger-the-better, and nominal-the-best specifications respectivel y. An integrated process capability index for a multi-process product is propo sed. The relationship between process capability index and the process yield is introduced. A multi-process capability analysis chart (MPCAC), reasonably rev ealing the status of process capability for the entire product, is constructed f or practical application. An evaluating procedure of the process capability for the entire product is also provided.

Process Capability Analysis of a Centre Lathe Turning Process

A process capability study is performed for the turning process on a general purpose center lathe in order to verify the process performance and machine ability to perform within specified tolerance limit. The process and machine capability indices were measured to determine the process and machine adequacy for industrial application. The tolerance limits were obtained from the given nominal size of the shaft, using the basic hole system and 90 sample shafts were turned on the lathe machine to specification for varying spindle speed and feed rate of the lathe. Three (3) samples were randomly selected for the turning process of a combination of the spindle speed and feed rate as a subgroup size for a total subgroup of thirty (30). The diameters (representing the quality characteristics) were used to generate control charts and capability histogram for the process. The process is within statistical control but found incapable of meeting up to specification because the capability index (Cp) measured was less than 1 and the machine capability for industrial application is not adequate.

PROCESS CAPABILITY ANALYSIS AND ESTIMATION SCHEME FOR AUTOCORRELATED DATA

Autocorrelation is prevalent in continuous production processes, such as the processes in the chemical and pharmaceutical industries. With the development of measurement technology and data acquisition technology, sampling frequency is getting higher and the existence of autocorrelation cannot be ignored. This paper analyzes five estimation schemes of process capability for autocorrelated data. Comparisons among these schemes are discussed for small sample and large sample. In conclusion, this paper gives a procedure of process capability analysis for autocorrelated data.

A multivariate process capability index model system

This paper presents a systematic multivariate process capability index （MPCI） method, which may provide references for assuring and improving process quality levels while achieving an overall evaluation of process quality. The system method includes a spatial MPCI model for multivariate normal distribution data, MPCI model based on factor weight for multivariate no-normal distribution application, and MPCI model based on yield foryield application. At last, examples for calculating MPCI are given, and the experimental results show that this systematic method is effective and practical.

A multivariate process capability index with a spatial coefficient

After analyzing the multivariate Cpm method （Chan et al. 1991）, this paper presents a spatial multivariate process capability index （PCI） method, which can solve a multivariate off-centered case and may provide references for assuring and improving process quality level while achieving an overall evaluation of process quality. Examples for calculating multivariate PCI are given and the experimental results show that the systematic method presented is effective and actual.

Two Processes Comparison by Using Capability Indices C_(pm)

In recent years, there has been mounting interest i n measuring process performance in manufacturing industry. Based on analyzing the process capability indices, a production department can trace and improve a poor process to enhance quality levels and satisfy customers. The process capabilit y analysis can also serve as an important reference for making decisions for imp roving the global quality of all products. Since C p and C pk are failed to account for process centering, the index C pm is developed. The index C pm takes the process centering into consideration and is su itable for the processes with nominal-the-best type. There are other indices l ike C pu and C pl, and those indices are used for unilateral s pecification processes. Chou (1994) developed a procedure using estimators of C p, C pu and C pl for practitioners to determine whether two p rocesses are equal capability or not. For bilateral specifications processes, i ndex C p is failed to measure process yield and process centering. Thus, th e index C pm is used to develop a similar procedure for practitioners t o determine whether two processes are equal capability or not. The decisions mad e using the procedure to select the better supplier are, of course, more reliabl e.

Precise Thermoplastic Processing of Graphene Oxide Layered Solid by Polymer Intercalation

The processing capability is vital for the wide applications of materials to forge structures as-demand.Graphene-based macroscopic materials have shown excellent mechanical and functional properties.However,different from usual polymers and metals,graphene solids exhibit limited deformability and processibility for precise forming.Here,we present a precise thermoplastic forming of graphene materials by polymer intercalation from graphene oxide(GO)precursor.The intercalated polymer enables the thermoplasticity of GO solids by thermally activated motion of polymer chains.We detect a critical minimum containing of intercalated polymer that can expand the interlayer spacing exceeding 1.4 nm to activate thermoplasticity,which becomes the criteria for thermal plastic forming of GO solids.By thermoplastic forming,the flat GO-composite films are forged to Gaussian curved shapes and imprinted to have surface relief patterns with size precision down to 360 nm.The plastic-formed structures maintain the structural integration with outstanding electrical(3.07×10^(5) S m^(−1))and thermal conductivity(745.65 W m^(−1) K^(−1))after removal of polymers.The thermoplastic strategy greatly extends the forming capability of GO materials and other layered materials and promises versatile structural designs for more broad applications.

Research on Factors Affecting Boiler Feedwater Quality and Its Improvement

Nowadays, with the rapid progress and development of the Chinese society, people’s material level has been continuously improved, and the demand for electricity has also been increasing year by year. For thermal power plants, it is of great importance to strictly control the feedwater quality and to conduct real-time tracking and supervision, as well as to ensure the safety of the production process. In this paper, we take the boiler feedwater quality in the production process as the research object. First of all, the cause-and-effect diagram is used to find out the reasons for the deviation of feedwater quality;Secondly, each index of feedwater is analyzed by multiple linear regression method to find out the key variables affecting the change of its pH value, so as to develop and implement improvement measures;Finally, the pH value is compared and verified by control chart and process capability analysis, and relevant improvement suggestions and countermeasures are proposed.

An Adjust Duty Cycle Method for Optimized Congestion Avoidance and Reducing Delay for WSNs

With the expansion of the application range and network scale of wireless sensor networks in recent years,WSNs often generate data surges and delay queues during the transmission process,causing network paralysis,even resulting in local or global congestion.In this paper,a dynamically Adjusted Duty Cycle for Optimized Congestion based on a real-time Queue Length(ADCOC)scheme is proposed.In order to improve the resource utilization rate of network nodes,we carried out optimization analysis based on the theory and applied it to the adjustment of the node’s duty cycle strategy.Using this strategy to ensure that the network lifetime remains the same,can minimize system delay and maximize energy efficiency.Firstly,the problems of the existing RED algorithm are analyzed.We introduce the improved SIG-RED algorithm into the ADCOC mechanism.As the data traffic changes,the RED protocol cannot automatically adjust the duty cycle.A scheduler is added to the buffer area manager,referring to a weighted index of network congestion,which can quickly determine the status of network congestion.The value of the weighting coefficient W is adjusted by the Bayesian method.The scheduler preferably transmits severely urgent data,alleviating the memory load.Then we combined improved data fusion technology and information gain methods to adjust the duty cycle dynamically.By simulating the algorithm,it shows that it has faster convergence speed and smaller queue jitter.Finally,we combine the adjusted congestion weight and the duty cycle growth value to adjust the data processing rate capability in the real-time network by dynamically adjusting it to adapt to bursts of data streams.Thus,the frequency of congestion is reduced to ensure that the system has higher processing efficiency and good adaptability.

Data-driven engineering framework with AI algorithm of Ginkgo Folium tablets manufacturing

Smart manufacturing still remains critical challenges for pharmaceutical manufacturing.Here,an original data-driven engineering framework was proposed to tackle the challenges.Firstly,from sporadic indicators to five kinds of systematic quality characteristics,nearly 2,000,000 real-world data points were successively characterized from Ginkgo Folium tablet manufacturing.Then,from simplex to the multivariate system,the digital process capability diagnosis strategy was proposed by multivariate C_(pk)integrated Bootstrap-t.The C_(pk)of Ginkgo Folium extracts,granules,and tablets were discovered,which was 0.59,0.42,and 0.78,respectively,indicating a relatively weak process capability,especially in granulating.Furthermore,the quality traceability was discovered from unit to end-to-end analysis,which decreased from 2.17 to 1.73.This further proved that attention should be paid to granulating to improve the quality characteristic.In conclusion,this paper provided a data-driven engineering strategy empowering industrial innovation to face the challenge of smart pharmaceutical manufacturing.

ABORT-like detector to combat active deceptive jamming in a network of LFM radars

This paper studies an electronic counter-counter measures（ECCM） scheme combating against deceptive electronic counter measure（ECM） techniques. An adaptive detector exploiting generalized likelihood ratio test（GRLT） criterion is applied to detect the presence of deceptive jamming in fractional Fourier transform（Fr FT） domain. First, the generating mechanism of spurious frequencies is analyzed based on the Volterra serial. The proposed nonlinear distortion model based on power amplifier behavior is robust in distortion analysis when the memory effect is considered.Second, a modified adaptive beamformer orthogonal rejection test（ABORT） like detector in closed form is built. The proposed detector can discriminate the echo and deceptive jamming adaptively by exploiting primary data and secondary data. This ECCM scheme is capable of guaranteeing the performance without the restriction of orthogonality, which is essential for the ABORT detectors. The expansion to radar network is discussed as a special case at the final part of this paper. Numerical simulations demonstrate the effectiveness of the proposed method.