Process Control Methods Research Articles

Spatiotemporal dynamics of temperature and precipitation with reference to COVID-19 pandemic lockdown: perspective from Indian subcontinent.

This study exclusively focuses on spatial and temporal change of temperature and precipitation before and after COVID-19 lockdown and also examines the extent of their variation and the spatial relationship between them. Our main objective is to analyze the spatiotemporal changes of two climatic variables in Indian subcontinent for the period of 2015–2020. Monthly precipitation and temperature data are collected from NOAA and NASA for January to May month across the four zones (northeast, northwest, central, and peninsular zone) of India. To conduct a zone-wise statistical analysis, we have adopted statistical process control (SPC) methods like exponentially weighted moving average (EWMA) control charts, individual charts (I- Chart) to detect the shift in temperature and precipitation over the study period and Pearson correlation coefficient applied to measure the spatial association between the two variables. The findings revealed that temperature parameter has experienced a lot of positive and negative trends in the span of 6 years and detected a weak to moderate negative correlation in many parts of the country in April 2020 after 2016. This study also identified a weak negative correlation mainly in NE zone in 2020 after 2017. This research provides vital scientific contribution to the effects of monthly temperature and precipitation before and after COVID-19 pandemic lockdown.Graphic abstract

Quality Control Design on Customized Mica Packaging Craft Product

Quality is one of differentiation strategies that can be addressed to achieve competitive advantage. Many alternatives can be selected to achieve this purpose. One of them is to maintain good quality of the products. A craft souvenir enterprise in Semarang controls the operation system of every product it produces to meet a good quality. This is very important since it produces customized products in which each product is designed according to customer order. A case study was conducted on the mica packaging craft product. Observations for 3 months with weekly production period show that the proportion of defective products is still relatively high compared to that is set by the enterprise (3.6% against 3%). By using the Statistical Process Control method and follow-up using the fishbone diagram method, it is found that there are 3 main causes, namely material, man (labor), and machine factors. Refer to this analysis, corrective actions is carried out to reduce occurrence of defective products in the next production periods.

Mathematical modelling of thermal stresses within the borehole walls in terms of plasma action

Purpose is the development of a mathematical model to study and describe thermal processes within the borehole wall in terms of plasma-based rock breaking. Methods. The following has been applied: theoretical analysis in the framework of a theory of brittle thermoelasticity breaking, methods of mathematical modeling, and computational experiment. Findings. Brief information on the results of the development of advanced plasma-based technology for borehole reaming for hard mineral mining has been represented. The results of industrial tests of plasma plant of 150-200 kW·s power with plasma-generating gas in the air for hard rock breaking have been represented. The plant and plasma-based technology of borehole reaming were tested in underground conditions of Kryvbas mines while reaming a perimeter hole to drive a ventilation rise in silicate-magnetite quartzites. A mathematical model has been proposed to analyze heat and mechanical fields in the rock during the plasma-based action on the borehole walls. Numerical studies of the temperature dynamics and thermal stresses within the borehole-surrounding rock layer have been carried out. It has been demonstrated that if low-temperature plasma is used (Т = 3500-4000°С), thermal compressing stresses are induced within the thin rock layer; the stresses may exceed the boundary admissible ones. It has been identified that plasma-based effect on the borehole wall makes it possible to create the conditions for intense rock fracturing and breaking. Originality. Solution of a new problem of thermoelastic state of a borehole wall in terms of plasma action has been obtained. The proposed mathematical model has been formulated in a cylindrical coordinate system and considers convective and radiation heat exchange between a plasma jet and a borehole wall. Practical implications. The obtained results make it possible to assess the rock state depending on the plasma jet parameters. The proposed methods of calculations will help carry out research to evaluate breaking parameters (the required heating time, thickness of the heated layer, and approximate spall dimensions) and develop different methods for the breaking process control.

Virtual reality environment for industrial robot control and path design

The current market trends have focused on personalization, where products based on the same platform can have different variations so they can satisfy multiple market segments. Trying to keep up with these trends, industries have introduced hybrid Human Robot Collaborative stations that offer short throughput times, along with the flexibility to process different tasks. For this kind of flexibility to be achieved in production, a concept is examined for remotely reprograming industrial robots. As a result, a fully automated assembly line or a production station, could be repurposed to handle different products or processes, using the currently installed equipment with minor adjustments. The concept that is described in this paper presents a teleoperation – based method for process design and control of industrial robots utilizing Virtual Reality. The main aim is to reduce the time and effort required for repurposing the robot operation without the physical presence of a robot operator at the shop floor. A case study is presented to demonstrate the above described concept.

Process Capability Studies in an Automated Flexible Assembly Process: A Case Study in an Automotive Industry

Statistical Process Control (SPC) methods can significantly increase organizational efficiency if appropriately used. The primary goal of process capability studies is to obtain critical information about processes to render them even more effective. This paper proposes a comprehensive framework for proper implementation of SPC studies, including the design of the sampling procedure and intervals as well as process capability indices. Some of the most essential process capability indices in the literature were reviewed to develop a methodology to utilize process capability indices within the SPC framework. The current study presents an efficiency-oriented criterion designed for measuring SPC implementation productivity. The framework is applied to the windshield installation process of an Iranian automobile assembly line. The process was sampled in various sessions. Results verify that the implemented SPC framework could successfully improve the process and that the proposed framework could significantly address bottleneck in the process and enhance the quality level of the process from satisfactory to excellent according to the reference values of process capability indices. Managerial insights are also drawn from results.

Modeling in-process machining data using spatial point cloud vs. time series data structures

In-process machining data (e.g., cutting forces and vibrations) have been typically collected and structured as time-referenced measurements (i.e., time-series data) and utilized in this structure to develop statistical data models used in process monitoring and control methods. This paper argues that a time-only-referenced representation overlooks the 3D nature of the physical process generating the data, and that machining data can be represented alternatively as functions of the tool-workpiece relative position resulting in a spatial point cloud data structure. High-density measurements of such spatially refenced data could be highly correlated to surrounding measurements, resulting in spatial correlation structures that could be of physical meaning and value to preserve and leverage. Using a simulated data study, this paper shows that preserving the spatial correlation structure of the data clearly improves the relative modeling performance when utilizing machining data point clouds versus the traditional time-referenced data structure. Specifically, this simulation study investigated the hypothesis that “considering the Gaussian process model class, the best model among all possible models developed using the spatial point cloud data structure has smaller/equal modeling and prediction errors compared to the best model among all possible models developed using the time-referenced data structure.” While this investigation was limited to considering the case of stationary isotropic processes, it demonstrated that the performance gap was relatively large. This encourages further investigations using real-world data to better understand the types of spatial correlations that exist in machining data and the specific machining regimes and process variables that would benefit the most from the spatial point cloud representation of the data.

COLOUR CONTROL FOR RETROREFLECTIVE TRAFFIC SIGNS PRODUCED BY DIGITAL PRINTING APPLICATIONS

The advancement of digital printing technologies facilitates alternative production methods to print certified reflective foils used to produce the faces of retroreflective traffic signs. Such products are approved and tested for certification in accordance with standards such as SR EN 12899-1:2007, regardless of production methods while the chromaticity and luminance factors are normative to qualify the product. This paper presents a method for process control and quality assurance using measurement devices and tools employed specifically by graphic technology. The core element is the correlation of the reference colour space (CIELAB, D50) with the standard reference from SR EN 12899-1:2007 (CIExyY, D65), also considering the conceptual difference from circular/elliptical tolerances typically used in printing processes and the colour box coordinates defined by the standard.

Multivariate statistical process control methods for batch production: a review focused on applications

ABSTRACT In this paper, we highlight the basic techniques of multivariate statistical process control (MSPC) under the dimensionality criteria, such as Multiway Principal Component Analysis, Multiway Partial Squares, Structuration à Trois Indices de la Statistique, Tucker3, Parallel Factors, Multiway Independent Component Analysis, Multiset Canonical Correlation Analysis, Slow Features Analysis, and Parallel Coordinates. Furthermore, we summarize the procedures of each statistical technique and the usage of multivariate control charts. In addition, we review the most significant proposals and applications in practical cases. Finally, we compare and discuss the benefits and limitations within methods.

Methods of analysis of glycoluril and its derivatives

The present work provides the literature data generalization concerning analysis of glycoluril, its derivatives and related compounds that allows obtaining information about the structure and properties of these com-pounds. Basic methods for analysis of glycoluril and substances on the basis thereof are considered, ad-vantages and disadvantages of these methods are described. The generalized results of the methods of analy-sis of glycoluril and its derivatives show that the majority of carried studies are focused on the revealing of purity and identification of related impurities for compounds that found practical application (drugs, mono-mers and polymers on the basis thereof). Consistent trend to active search of new methods to analyze macrocyclic and supramolecular systems synthesized on the basis of glycoluril is observed. The aim of the present review is to take attention of chemists to the most advanced methods of analysis of glycoluril and its derivatives with reference to promotion of further research. The literature analysis will be useful for research-ers dealing with designing of new molecules based on glycoluril with given properties where the methods of process control and analysis of target compounds has a decisive importance.

Modeling and prediction of the average roughness of UNS S31600 in superfinishing turning

PurposeThe purpose of this paper is to realize an effective hybrid modeling (empirical-geometric) in order to describe the real behavior of the average roughness variation of the workpiece surface in turning with an elementary operation of superfinishing, using different analytic methodologies. The previous works are limited to describe the roughness for the usual elementary operations, citing the roughing and the semi-finishing, while this analysis builds technical rails for the industrialists in order to well conduct the operation of superfinishing in turning, by choosing the cutting parameters from the proposed model.Design/methodology/approachA statistical analysis of the average roughness measurements capability study, by the statistical process control method SPC and the ANN artificial neuron network, Levenberg–Marquardt's methods modified Monte Carlo SRM response surface.FindingsThe objective of this work was to describe the average roughness generated by the penetration of the cutting tool into a part in superfinishing turning. First, the authors used artificial colony analysis to determine optimal cutting conditions in order to have an average roughness lower than 0.8 µm. The cutting conditions selected: (1) the feed rate f ϵ [0.05; 0.2] mm/rev; (2) the pass depth ap ϵ [0.25; 1] mm; (3) the corner radius re = 0.2 mm and (4) cutting speed Vc ϵ [75; 100] m/min.Originality/valueThis work consists to realize an effective hybrid modeling (empirical-geometric) in order to describe the real behavior of the average roughness variation of the workpiece surface in turning with an elementary operation of superfinishing, using different analytic methodologies. The previous works are limited to describe the roughness for the usual elementary operations, citing the roughing and the semi-finishing, while this analysis builds technical rails for the industrialists in order to well conduct the operation of superfinishing in turning, by choosing the cutting parameters from the proposed model.

Approach to Establishment of Control Strategy for Oral Solid Dosage Forms Using Continuous Manufacturing.

As a result of the research activities of the Japan Agency for Medical Research and Development (AMED), this document aims to show an approach to establishing control strategy for continuous manufacturing of oral solid dosage forms. The methods of drug development, technology transfer, process control, and quality control used in the current commercial batch manufacturing would be effective also in continuous manufacturing, while there are differences in the process development using continuous manufacturing and batch manufacturing. This document introduces an example of the way of thinking for establishing a control strategy for continuous manufacturing processes.

A Knowledge-Based System as a Sustainable Software Application for the Supervision and Intelligent Control of an Alcoholic Fermentation Process

One goal of specialists in food processing is to increase production efficiency in accordance with sustainability by optimising the consumption of raw food materials, water, and energy. One way to achieve this purpose is to develop new methods for process monitoring and control. In the winemaking industry, there is a lack of procedures regarding the common work based on knowledge acquisition and intelligent control. In the present article, we developed and tested a knowledge-based system for the alcoholic fermentation process of white winemaking while considering the main phases: the latent phase, exponential growth phase, and decay phase. The automatic control of the white wine’s alcoholic fermentation process was designed as a system on three levels. Level zero represents the measurement and adjustment loops of the bioreactor. At the first level of control, the three phases of the process are detected functions of the characteristics of the fermentation medium (the initial substrate concentration, the nitrogen assimilable content, and the initial concentration of biomass) and, thus, functions on the phase’s duration. The second level achieves the sequence supervision of the process (the operation sequence of a fermentation batch) and transforms the process into a continuous one. This control level ensures the quality of the process as well as its diagnosis. This software application can be extended to the industrial scale and can be improved by using further artificial intelligence techniques.

Research on Energy-saving Process Control Method of Bulk Cargo Terminal Based on Frequency Control Technology

The bulk cargo terminal conveying system has the problems of low equipment efficiency and high energy consumption during operating conditions such as no-load starting, ship loader shifting, and ship unloader clearing. In this paper, combined with the full frequency conversion control technology, the research on the frequency conversion control mode of the bulk cargo terminal and the energy saving effect test are carried out, and the optimized control method for the energy saving process is proposed. Under various common working conditions, the bulk cargo terminal can control the belt conveyor to run at low or zero speed according to the actual situation on the spot, so as to minimize energy consumption.

Voltage Control for a Polymer Electrolyte Fuel Cell System By Model Predictive Control Controller

Due to its high power density, fast start up ability, low operating temperature, noiseless and environmental friendliness, polymer electrolyte fuel cells (PEFCs) have been regarded as the most promising alternative power sources for a variety of applications, such as transportation system, domestic system, stationary system and so on. Stable and effective control strategy is essential for the efficient and safe operation of PEFC systems. Voltage control is always a research hotspot in PEFCs’ control study. When using a PEFC system to supply power in a real application, it is of great significance to maintain a stable output voltage to avoid an adverse voltage drop under sudden load change, which can reduce the maintenance costs of the PEFC generation system. The output voltage of the PEFC system can be easily affected by the inlet flow rate of the reactant gas, i.e., the reactions inside the fuel cell system will be more sufficient with higher input flow rate of the reactant gas to produce higher electrical voltage, otherwise, less electrical voltage is generated. Therefore, the focus of this study is to control the output voltage of a PEFC system by regulating its hydrogen and air flow rates, which stands for a multi input and single output control problem.Model predictive control (MPC) is an advanced method of process control with stronger robustness and faster response compared with conventional controllers. Its main advantage is that it allows the current timeslot to be optimized while keeping future timeslots in account. Moreover, the MPC is rather suitable for solving systems with constraints, which makes a good choice for the voltage control of the PEFC system since the fuel cell system is a complicated nonlinear and strongly coupled system, with many constraints that need to be considered to ensure the coordination and balance between every subsystem.The first part of this study is to develop a PEFC system dynamic model, which is based on the NedStack PS6 of 6kW rated power. Its polarization behavior based on different reactant flowrates are evaluated. Then based on the developed model, a novel MPC controller is designed to control the PEFC system’s output voltage at 48V, assuming that the PEFC system can be an alternative power source for an electric bicycle with 48 V by regulating the input hydrogen and air flow rates. The following figure gives an overview of the voltage control of the PEFC system. It can be seen the input of the MPC controller contains the reference stack voltage, the state vector, the actual stack voltage and the current. It should be noted that the current is the our test signal. Figure 1

Abstract 14034: Sustaining and Spreading Success: Longer Term Outcomes and Spread of a Multi-Center Quality Improvement Project to Reduce Post-operative Chest Tube (CT) Duration (on Behalf of the Pediatric Acute Care Cardiology Collaborative and Pediatric Cardiac Critical Care Consortium)

Introduction: Using a collaborative learning model, we previously showed reduced post-operative CT duration and length of stay (LOS) after 10 STS benchmark surgeries. Here we report sustained gains across the original 9 centers (labeled era 1) and spread of the project (era 2) to 9 new centers in the PAC 3 -PC 4 network. Methods: Data on patients undergoing surgeries was collected across the two eras. Each era consisted of a baseline phase (era 1: 6/2017-6/2018, era 2: 5/2019-8/2019) and an intervention phase (era 1: 7/2018-3/2020, era 2: 9/2019-3/2020). The primary outcome was post-operative CT duration in hours, with aim of 20% reduction in the intervention vs baseline phases. Balancing measures included rate of reinsertion and readmission for effusion. The collaborative learning model included monthly webinars with peer support, data transparency, and QI education. Statistical process control methods and traditional statistics were used to analyze CT duration and LOS over time. Results: Among 3656 patients at 18 centers, demographics were comparable across eras. Era 1 cohort (n=2779) sustained a 23.5% reduction in CT duration (median 88.9 vs 67.9 hours, p=<.0001) and a 12.5% reduction in LOS days (median 8 vs 7, p=0.03). Era 2 cohort (n=877) showed a 6.95% reduction (median 68.3 vs 63.5 hours, p=0.03) in CT duration in the first 7 months of intervention phase. Across both eras, rates of reinsertion (1.77% vs 1.25%, p=0.48) and readmission for effusion did not change (1.26% vs 2.29%, p=1.00). Conclusions: In this multicenter prospective interventional cohort study, reductions in CT duration and LOS were sustained in 9 centers following a collaborative learning model, without adverse events. Nine new centers show promising early results, suggesting that this intervention can be spread successfully. With its use of phased spread, peer support, data transparency, and education, this project serves as a model for sustaining and spreading clinical quality improvement.

Analysis of the causes of additional blowings in converter steel production and ways of their elimination

The article analyzes the work of the oxygen-converter shop of PJSC «ArcelorMittal Kryvyi Rih». It has been shown that almost half of the total number of additional oxygen blowings (~ 44%) is necessitated by the temperature. In order to improve the conditions of steel smelting and to reduce resource costs, calculations have been performed and new technological solutions in steel smelting to reduce the number of additional oxygen blowings have been found. The study of real smeltings demonstrated the need for corrective operations in the steel smelting using metal scrap of different types. For example, the use of cast iron requires an additional consumption of limestone in the amount of 130-140 kg per 1t of cast iron to reduce the amount of heat entering the bath. It is shown that the use of this technique makes it possible to decrease the number of additional blowings caused by the carbon amount as well as the increased temperature of the melting. It has been concluded that the most effective method of technological process control in smelting with cast iron is the integrated use of limestone and additional application of the nomogram of the dependence of silicon content in cast iron and lime consumption. Smeltings with the use of scrap exhibit a clear relationship between the amount of scrap in the charge and the temperature of the melt in the first dump. To compensate for temperature fluctuations caused by the addition of scrap, it is recommended to add ground coke in the amount of 120 kg per each ton of scrap. Calculations show that in this case, the required temperature close to 1610°C and the given carbon content are achieved in 75% of cases. The addition of «gantry» scrap to the charge has a number of uncontrolled effects on the process due to significant fluctuations in the chemical composition of this type of metal charge. The most technologically feasible solution to problems with additional blowings when using «gantry» scrap is fire cutting of the scrap. If such an operation is impossible, it is recommended to overheat the metal by 30°C to increase the degree of its penetration

Analisa defect produk sheet area corrugator 301 menggunakan metode SPC dan FMEA di PT Indah Kiat

This study aims to analyze defects in the sheet production process in the 301 Corrugator area by analyzing the total number of sheets produced and the number of sheets that have been damaged over a certain period of time using the Statistical Process Control (SPC) method and Failure Modes and Effect Analysis (FMEA). Based on the research results, there are 6 defects, namely untidy cuts, wrinkled sheets, uneven surface, curved sheets, uneven sides, loose sheet layers. The most dominant defect is uneven surface, which is 185.141 Kg or 60%. Based on the value of the RPN table, the product defect that has the highest value is the loose sheet layer with an RPN value of 245 from the calculation stage of the RPN value, a suggestion is made to reduce defects resulting from the loose sheet layer. From the stage of making improvements, the company should prioritize and focus on the types of disabilities and types of disabilities that have the highest RPN ranking when using the Failure Mode and Effect Analysis (FMEA) method.

A strategy for population pharmaceutical quality assessment based on quality by design

From a regulatory perspective, drug quality consistency evaluation must concern different processes used for the same drug. In this study, an assessment strategy based on quality by design (QbD) was developed for population pharmaceutical quality evaluation. A descriptive analysis method based on QbD concept was first established to characterize the process by critical evaluation attributes (CEAs). Then quantitative analysis method based on an improved statistical process control (SPC) method was established to investigate the process indicators (PIs) in the process population, such as mean distribution, batch-to-batch difference and abnormal quality probability. After that rules for risk assessment were established based on the SPC limitations and parameters. Both the SPC parameters of the CEAs and the risk of PIs were visualized according to the interaction test results to obtain a better understanding of the population pharmaceutical quality. Finally, an assessment strategy was built and applied to generic drug consistency assessment, process risk assessment and quality trend tracking. The strategy demonstrated in this study could help reveal quality consistency from the perspective of process control and process risk, and further show the recent development status of domestic pharmaceutical production processes. In addition, a process risk assessment and population quality trend tracking provide data-based information for approval. Not only can this information serve as a further basis for decision-making by the regulatory authority regarding early warnings, but it can also reduce some avoidable adverse reactions. With continuous addition of data, dynamic population pharmaceutical quality is meaningful for emergencies and decision-making regarding drug regulation.

Rapid Discrimination of Cheese Products Based on Probabilistic Neural Network and Raman Spectroscopy

The aim of this work is to solve the practical problem that there are relatively few fast, intelligent, and objective methods to distinguish dairy products and to further improve the quality control methods of them. Therefore, an approach of cheese product brand discrimination method based on Raman spectroscopy and probabilistic neural network algorithm was developed. The experimental results show that the spectrum contains abundant molecular vibration information of carbohydrates, fats, proteins, and other components, and the Raman spectral data collection time of a single sample is only 100 s. Due to the high spectral similarity between samples, it is impossible to identify them with naked eyes. Characteristic peak intensity combined with statistical process control method was employed to study the fluctuation characteristics of samples. The results show that the characteristic peak of experimental samples fluctuates within a certain control limit. However, due to the high similarity between the Raman spectra of different brand samples, they cannot be effectively identified as well. This paper further studied and established the analytical approach based on Raman spectroscopy, including wavelet denoising, normalization, principal component analysis, and probabilistic neural network discrimination. In db1 wavelet processing, [−1, 1] normalization, 74 principal components (cumulative contribution rate of 100%) can realize the effective discrimination of different brands of cheese products in 1 s, with the average recognition accuracy of 96%. The discriminant method established in this work has the advantages of simple operation, rapid analysis, and accurate results. It provides a technical reference for the fight against counterfeit products and has a broad application prospect.

A new model to monitor very small effects of a polynomial profile

PurposeDifferent real cases indicate that the quality of a process is better monitored by a functional relationship rather than the traditional statistical process control (SPC) methods. This approach is referred to as profile monitoring. A serious objective in profile monitoring is the sensitivity of a model to very small changes of the process. The rapid progress of the precision manufacturing also indicates the importance of identifying very small shift types of a process/product profile curve. This sensitivity allows one to identify the fault of a process sooner compared to the case of lack of the capability.Design/methodology/approachThis paper proposed a new method to monitor very small shift types of a polynomial profile for phase II of the SPC. The proposed method was named as MGWMA-PF. The performance capability of the proposed approach was evaluated through several numerical examples. A real case study was also used to investigate the capability of the proposed model.FindingsThe results addressed that the proposed method was capable of detecting very small shift types effectively. The numerical report based on the average run length (ARL) term revealed the more sensitivity of the proposed model compared to other existing methods of the literature.Originality/valueThis paper proposes a new method to monitor very small shift types of a polynomial profile for phase II of the SPC. The proposed method provides detecting a very small change manifested itself to the process.