Optimization of steel bar manufacturing process using six sigma

Optimization of a manufacturing process results in higher productivity and reduced wastes. Production parameters of a local steel bar manufacturing industry of Pakistan is optimized by using six Sigma-Define, measure, analyze, improve, and control- methodology. Production data is collected and analyzed. After analysis, experimental design result is used to identify significant factors affecting process performance. The significant factors are controlled to optimized level using two-level factorial design method. A regression model is developed that helps in the estimation of response under multi variable input values. Model is tested, verified, and validated by using industrial data collected at a local steel bar manufacturing industry of Peshawar(Khyber Pakhtunkhwa, Pakistan). The sigma level of the manufacturing process is improved to 4.01 from 3.58. The novelty of the research is the identification of the significant factors along with the optimum levels that affects the process yield, and the methodology to optimize the steel bar manufacturing process.     

Amphiphilic comb-like pentablock copolymers of Pluronic L64 and poly(ethylene glycol)methyl ether methacrylate: synthesis by ATRP,self-assembly,and clouding behavior

Well-defined amphiphilic comb-like pentablock copolymers based on Pluronic L64 (PEO₁₃-b-PPO₃₀-b-PEO₁₃) and poly(ethylene glycol)methyl ether methacrylate (PEGMA) have been successfully synthesized via atom transfer radical polymerization (ATRP). The L64 is transformed into ATRP macroinitiator and chain extended with PEGMA under typical ATRP conditions to achieve comb-like pentablock copolymers of various compositions. Due to their amphiphilic nature, the block copolymers could form self-assembled structures in aqueous solutions as confirmed by dynamic light scattering. At higher PEGMA content in the synthesized copolymer, however, the critical aggregation concentration (CAC) is less pronounced that could be attributed to the increased hydrophilicity and steric hindrance of PEG side chains of the PEGMA, thus preventing the formation of well-defined micellar aggregates, and probably leads to open-shell aggregation mechanism. The lower critical solution temperature (LCST) of the synthesized block copolymers is found higher than the neat L64 and increased with increasing the PEGMA content. Further, tuning the clouding behavior could be achieved with inorganic additives (KBr and K₂SO₄). The influence of SO₄^2? and Br^1? on LCST is according to their position in Hofmeister series. Interestingly, the effect of additives is more pronounced above the CAC of the copolymer, suggesting that the nanoaggregates in solution induce the macrophase separation.     

CdS impregnated cellulose nanocrystals/PVDF composite flexible and freestanding films: Impedance spectroscopic studies

Nanocrystalline CdS impregnated cellulose nanocrystals (CdS‐Cellulose) were embedded in polyvinylidene fluoride (PVDF) matrix and free‐standing flexible films of CdS‐cellulose/PVDF nanocomposite were made by sol‐gel technique. Effect of CdS loadings in cellulose embedded in the host matrix (PVDF) on the impedance properties was studied critically for the above samples. Dielectric constants were studied as a function of frequencies (1–100 kHz) at room temperatures. The dielectric constant increased significantly in CdS‐cellulose/PVDF nanocomposite than that for pristine PVDF film. The higher values of dielectric constant as well as dielectric loss were obtained at lower frequencies. This may be caused due to contributions arising out of space charge, dipole, and electronic polarizations. At higher frequencies, only dipole and electronic polarization were seen to contribute significantly. The nature of the Cole‐Cole plots could be seen to deviate significantly from one impedance semicircular arc before diverging after a frequency of 3,158, 2,147, and 1,925 Hz for CdS‐cellulose/PVDF nanocomposite with increased loading of CdS. POLYM. ENG. SCI., 58:1419–1427, 2018. © 2017 Society of Plastics Engineers     

Reduction of Errors in Hydrological Drought Monitoring – A Novel Statistical Framework for Spatio-Temporal Assessment of Drought

Water Resources Management - Continuous and accurate drought monitoring has an important role in early warning drought mitigation policies. This study aims to provide an accurate standardized...     

Reliability improvement in distribution systems employing an integrated voltage sag mitigation method using binary gravitational search algorithm

A method for improving the level of reliability of distribution systems is presented by employing an integrated voltage sag mitigation method that comprises a two-staged strategy, namely, distribution network reconfiguration （DNR） followed by DSTATCOM placement. Initially, an optimal DNR is applied to reduce the propagated voltage sags during the test period. The second stage involves optimal placement of the DSTATCOM to assist the already reconfigured network. The gravitational search algorithm is used in the process of optimal DNR and in placing DSTATCOM. Reliability assessment is performed using the well-known indices. The simulation results show that the proposed method is efficient and feasible for improving the level of system reliability.     

Daily Forecasting of Dam Water Levels: Comparing a Support Vector Machine (SVM) Model With Adaptive Neuro Fuzzy Inference System (ANFIS)

Reservoir planning and management are critical to the development of the hydrological field and necessary to Integrated Water Resources Management. The growth of forecasting models has resulted in an excellent model known as the Support Vector Machine (SVM). This model uses linearly separable patterns based on an optimal hyperplane, which are extended to non-linearly separable patterns by transforming the raw data to map into a new space. SVM can find a global optimal solution equipped with Kernel functions. These Kernel functions have high flexibility in the forecasting computation, enabling data to be mapped at a higher and infinite-dimensional space in an implicit manner. This paper presents a new solution to the expert system, using SVM to forecast the daily dam water level of the Klang gate. Four categories are identified to determine the best model: the input scenario, the type of SVM regression, the number of V-fold cross-validation and the time lag. The best input scenario employs both the rainfall R(t-i) and the dam water level L(t-i). Type 2 SVM regression is selected as the best regression type, and 5-fold cross-validation produces the most accurate results. The results are compared with those obtained using ANFIS: all the RMSE, MAE and MAPE values prove that SVM is a superior model to ANFIS. Finally, all the results are combined to determine the best time lag, resulting in R(t-2) L(t-2) for the best model with only 1.64 % error.     

Development of cBN reinforced Ti6Al4V MMCs through laser sintering and process optimization

In this work, a systematic study and optimization on direct metal laser sintering (DMLS) of a cBN reinforced Ti6Al4V metal matrix composite (MMC) has been carried out using the response surface methodology (RSM). Variable process parameters such as volume % of cBN (5–15%), laser power (50–60?W), scanning speed (3500–4500?mm/min), and constant parameters such as laser spot diameter (0.2?mm), hatching gap (0.2?mm), and layer thickness (0.4) were considered for the experiments. The RSM was employed to establish a regression equation to predict different output parameters of the sintered samples such as the wear rate, relative density, and microhardness. Based on the developed model, the influence of process parameters on the wear rate, density, and microhardness were accomplished with optimized results. Hence, the result, thus, obtained showed the maximum hardness and density of 519 HV_0.2 and 4.23?g/cm³, respectively, and the minimum wear of 26.49?µm in a testing time duration of 10 minutes. X-Ray Diffraction (XRD) analysis of the fabricated MMC confirms the presence of different phases such as cBN, AlN, TiN, TiB₂, and TiO₂ as a consequence of a series of chemical reactions among cBN and different elements of Ti6Al4V in an argon atmosphere.     

Simultaneous Use of Runs Rules and Auxiliary Information With Exponentially Weighted Moving Average Control Charts

Quality has become a key determinant of success in all aspects of industry. Exponentially weighted moving average control chart is an important tool of statistical process control used to monitor and improve quality of industrial processes. To enhance the performance of control charts, there are many strategies including the choice of an efficient plotting statistic, the choice of an efficient sampling design, the application of runs rules, and the use auxiliary information among many others. In this study, we propose nine different signaling schemes to enhance the performance of an exponentially weighted moving average control chart for location parameter, which is based on the exploitation of auxiliary information. Performance evaluation of the proposed schemes is carried out in terms of average run length. Comparisons of proposals are made with the classical as well as the auxiliary based exponentially weighted moving average and cumulative sum charts, which indicate that the proposed schemes perform better than the comparative counterparts under discussion. Copyright © 2016 John Wiley & Sons, Ltd.