Variety Of Processes Research Articles

Controlling pore structure and conductivity in graphene nanosheet films through partial thermal exfoliation

Thermal exfoliation is an efficient and scalable method for the production of graphene nanosheets or nanoplatelets, which are typically re-assembled or blended to form new macroscopic “graphene-based materials”. Thermal exfoliation can be applied to these macroscopic graphene-based materials after casting to create internal porosity, but this process variant has not been widely studied, and can easily lead to destruction of the physical form of the original cast body. Here we explore how the partial thermal exfoliation of graphene oxide (GO) multilayer nanosheet films can be used to control pore structure and electrical conductivity of planar, textured, and confined GO films. The GO films are shown to exfoliate explosively when the instrument-set heating rates are 100 K/min and above leading to complete destruction of the film geometry. Textured films with engineered micro-wrinkling and crumpling show similar thermal behavior to planar films. Here, we also demonstrate a novel method to produce fairly large size intact rGO films of high electrical conductivity and microporosity based on confinement. Sandwiching GO precursor films between inert plates during partial exfoliation at 250 °C produces high conductivity and porosity material in the form of a flexible film that preserves the macroscopic structure of the original cast body.

On the composition of the long tail of business processes: Implications from a process mining study

Digital transformation forces companies to rethink their processes to meet current customer needs. Business Process Management (BPM) can provide the means to structure and tackle this change. However, most approaches to BPM face restrictions on the number of processes they can optimize at a time due to complexity and resource restrictions. Investigating this shortcoming, the concept of the long tail of business processes suggests a hybrid approach that entails managing important processes centrally, while incrementally improving the majority of processes at their place of execution. This study scrutinizes this observation as well as corresponding implications. First, we define a system of indicators to automatically prioritize processes based on execution data. Second, we use process mining to analyze processes from multiple companies to investigate the distribution of process value in terms of their process variants. Third, we examine the characteristics of the process variants contained in the short head and the long tail to derive and justify recommendations for their management. Our results suggest that the assumption of a long-tailed distribution holds across companies and indicators and also applies to the overall improvement potential of processes and their variants. Across all cases, process variants in the long tail were characterized by fewer customer contacts, lower execution frequencies, and a larger number of involved stakeholders, making them suitable candidates for distributed improvement

Procurement Process Analysis Using Process Mining in Cement Manufacturing Company (Case Study PT. Semen Indonesia Persero, Tbk)

Procurement process holds crucial role in companies’ business process, particularly manufacturing company. PT Semen Indonesia as one of manufacturing Companies in Indonesia relies on procurement process in order to fulfill their business. However, existing e-procurement does not cover all the procurement process which creates process variants have made whole procurement process run into bottleneck. Deeper analysis required to dig insights on the process variants to derive the cause of problem. Hence, this research aims to explore Process Mining to gain more insights from the process using data log derived from the system. BPM lifecycle used as an approach to reach the objective of the research. However, not all phases in BPM lifecycle are imposed, yet Process Identification, Process Discovery and Process Analysis. The result showed that top three activities that take time most are Upload to E Procurement, Purchasing Configuration, and Technical Evaluation which require improvements.

Structural identification of the bearing manufacturing process – Case-study

In the manufacturing industry, globalization, shorter life cycles of products and changing customer needs, leads to high competitive pressure on companies. In addition to product quality and variety, flexibility, shorter processing times, and high-level compliance with delivery times have become essential factors for market success through efficient, efficacious and continually manufacturing processes optimization. To be successful in a highly competitive global production environment, a company must be able to deliver products that customers request at the requested time. In this paper is developed a novel method of structural identification of the bearing manufacturing process. This method allows the structuring of its activities, at all levels involved (order acceptance, production planning, product design, processes planning, and product processing), by elaborating the tree of the specific activities. The relations between the manufacturing process stages and related information circuit are revealed and the identification of the manufacturing process variants, at the level of each manufacturing activity is performed. Following the selection of the best alternatives from each level of the manufacturing activity, the optimal technological path is obtained for taking over an order for the bearing manufacture.

Biochar from pyrolysis of rice husk biomass—characteristics, modification and environmental application

Biochar produced from various biomass has been widely used in environmental applications owing to its ability to immobilize or remove the contaminants from soil, water and air. The present work summarizes various pyrolysis variants used for biochar production from rice husk, modification of biochar and its environmental application. The high volatile matter content (70.2–78.5%) and carbon content (35.2–44.7%) favoured production of biochar from rice husk through pyrolysis. Microwave-assisted hydrothermal carbonization showed highest biochar yield from rice husk (57.9%) compared to other process variants, whereas wet pyrolysis produced biochar with the highest carbon content (71.2%). Steam activation of rice husk biochar resulted in a broader pore size distribution with the presence of significant micropores compared to CO2 activation. A substantial improvement in surface area and microporous volume was observed with alkali activation compared to that of acid activation, whereas metal impregnation caused a reduction in surface area. Rice husk biochar with/without modification has been employed for adsorption of pollutants such as cations, dyes, nutrients and tetracycline. The nutrient-loaded rice husk biochar improved the soil fertility and cation exchange capacity. The studies indicated that the choice of suitable pyrolysis variant and biochar modification method is vital to improve the adsorption capacity and nutrient release potential of the rice husk biochar.

Business process variant analysis: Survey and classification

It is common for business processes to exhibit a high degree of internal heterogeneity, in the sense that the executions of the process differ widely from each other due to contextual factors, human factors, or deliberate business decisions. For example, a quote-to-cash process in a multinational company is typically executed differently across different countries or even across different regions in the same country. Similarly, an insurance claims handling process might be executed differently across different claims handling centers or across multiple teams within the same claims handling center. A subset of executions of a business process that can be distinguished from others based on a given predicate (e.g. the executions of a process in a given country) is called a process variant. Understanding differences between process variants helps analysts and managers to make informed decisions as to how to standardize or otherwise improve a business process, for example by helping them find out what makes it that a given variant exhibits a higher performance than another one. Process variant analysis is a family of techniques to analyze event logs produced during the execution of a process, in order to identify and explain the differences between two or more process variants. A wide range of methods for process variant analysis have been proposed in the past decade. However, due to the interdisciplinary nature of this field, the proposed methods and the types of differences they can identify vary widely, and there is a lack of a unifying view of the field. To close this gap, this article presents a systematic literature review of methods for process variant analysis. The identified studies are classified according to their inputs, outputs, analysis purpose, underpinning algorithms, and extra-functional characteristics. The paper closes with a broad classification of approaches into three categories based on the paradigm they employ to compare multiple process variants.

A comprehensive review on equal channel angular pressing of bulk metal and sheet metal process methodology and its varied applications

Abstract Equal Channel Angular Pressing (ECAP), being a promising technique for producing bulk ultra-fine grained material, relies on shearing the material via channels of equal cross section. The processing method keeps constantly getting modified resulting in slightly better configurations of its predecessors. A review of such processing technique modifications such as specimen orientation changes, variation in thermo-mechanical processing sequence, modifications in the die geometry etc., along with its impact on microstructural and mechanical properties are reviewed. The entire spectrum of variants of the ECAP process are classified into five major categories namely bulk metal processing, sheet metal processing, hollow section processing, powder compaction variants and extended applications. Such classification is primarily based on the product and an exhaustive review of process variants under each category are arranged in an increasing order of complexity. Conclusions are drawn on merits and demerits of existing variants of the process with suggestions for future research.

Flexible Process Model Mapping using Relaxation Labeling

Computing a mapping between two process models is a crucial technique, since it enables reasoning and operating across processes, like providing a similarity score between two processes, or merging different process variants to generate a consolidated process model. In this paper we present a new flexible technique for process model mapping, based on the relaxation labeling constraint satisfaction algorithm. The technique can be instantiated so that different modes are devised, depending on the context. For instance, it can be adapted to the case where one of the mapped process models is incomplete, or it can be used to ground an adaptable similarity measure between process models. The approach has been implemented inside the open platform NLP4BPM, providing a visualization of the performed mappings and computed similarity scores. The experimental results witness the flexibility and usefulness of the technique proposed.

Normal anatomic variants of paranasal sinus region studied by computed tomography

Background and objective: Variation in paranasal sinus anatomy, as shown on computed tomographic scans, is of potential significance as it may pose risks during surgery or predispose to certain pathologic conditions. This study aimed to investigate the frequency of anatomic variants of the nasal cavity and paranasal sinuses in our population and determine their relationship with gender and find out the association of these variants with mucosal abnormalities. Methods: This was a cross-sectional study conducted at the College of Medicine, Hawler Medical University from October 2017 to January 2019. A review of computed tomography scans of the paranasal sinuses of 300 patients was done; special attention was directed toward identifying bony anatomic variants and mucosal abnormalities. Results: Frequent variants were: Agger nasi cells (72%), nasal septal deviation (71.7%), Haller cells (70.7%), concha bullosa (61%), elongation of uncinate process (69.7%) and different variants of the sphenoidal sinus (78.8%). The frequency of variants did not differ significantly with respect to gender, except for sphenoidal variants along with Keros types and asymmetry of the ethmoidal roof. A significant association was found between middle concha variants and inferior turbinate enlargement (P <0.001). Conclusion: Anatomic variants of the paranasal sinus region were common in our population; the most frequent ones were those involving the nasal septum, ethmoid air cells, sphenoid sinuses, and middle turbinates. The study of these variants is important for the management of paranasal sinus region disease.

Design and Characterization of the CLICTD Pixelated Monolithic Sensor Chip

A novel monolithic pixelated sensor and readout chip, the compact linear collider tracker detector (CLICTD) chip, is presented. The CLICTD chip was designed targeting the requirements of the silicon tracker development for the experiment at the compact linear collider (CLIC) and has been fabricated in a modified 180 nm CMOS imaging process with charge collection on a high-resistivity p-type epitaxial layer. The chip features a matrix of $16\times 128$ elongated channels, each measuring $300\times 30\,\,\mu \text {m}^{2}$ . Each channel contains 8 equidistant collection electrodes and analog readout circuits to ensure prompt signal formation. A simultaneous 8-bit time-of-arrival (with 10 ns time bins) and 5-bit time-over-threshold measurement is performed on the combined digital output of the 8 subpixels in every channel. The chip has been fabricated in two process variants and characterized in laboratory measurements using electrical test pulses and radiation sources. Results show a minimum threshold between 135 and 180 e− and a noise of about 14 e− rms. The design aspects and characterization results of the CLICTD chip are presented.

Microbial Electrosynthesis-An Inventory on Technology Readiness Level and Performance of Different Process Variants.

The objective of microbial electrosynthesis (MES) is to combine the advantages of electrochemistry and biotechnology in order to produce chemicals and fuels. This combination enables resource-efficient processes by using renewable raw materials and regenerative energies. In the last decade, different MES processes have been described, for example, MES based on biofilms or mediators, electro-fermentation, and secondary MES. This review compares the MES technologies with regard to the reached process performances in terms of key process indicators (i.e., coulombic efficiency (CE), product titre, productivity) and technology readiness level (TRL). Often the underlying mechanism of electron transfer in biofilm-based processes has not been elucidated and can therefore not be optimized. Similarly, technical aspects of electro-fermentation processes and processes with soluble mediators are under investigation and techno-economic assessments are missing. In contrast, the electrochemical production of microbial substrates in secondary MES or hybrid systems show high key process indicators and TRLs up to 7. In summary, the different types of MES processes offer options for today's industrial use, as well as an exciting and future-oriented technology that can be applied in a medium-term perspective.

Regression-based compensation of part inaccuracies in incremental sheet forming at elevated temperatures

Incremental sheet forming is a sheet forming process for small lot sizes due to its dieless principle. One of its process variants includes local heating of the sheet to counteract some of the process restrictions (formable materials, forming forces, achievable deformations). Although forming at elevated temperatures provides various advantages, the geometric accuracy of the formed part remains low due to shrinking effects caused by local heating and cooling. This publication presents a data-driven approach where process data is gathered and used in regression learning to predict the geometric accuracy resulting from the shrinking effects. To successfully apply regression learning, a big amount of process data is needed covering a wide range of possible process states. Therefore, a specific experimental series, consisting of 54 individual forming experiments, is designed and carried out. Based on the 3D digitization of the formed parts, a process database is built up comprising 408,296 records, each representing a toolpath point. This process database is used to train 19 different regression models. The performance of their ability to predict the geometric deviations is investigated. A compensation approach is presented that improves the geometric accuracy through a prediction-based modification of the toolpath. Validation experiments demonstrate the improvement of the geometric accuracy of the formed part and the generalizability of the approach.

Plasma-Functionalized Water: from Bench to Prototype for Fresh-Cut Lettuce

Fresh-cut produce like lettuce may contain a very high microbial load, including human pathogens. Therefore, the need for antimicrobial agents at post-harvest stages to mitigate microbial cross-contamination and growth is evident. Sanitation based on non-thermal plasma (NTP) reveals innovative food processing possibilities by application at different points along the food chain, for production, modification, and preservation, as well as in packaging of plant- and animal-based food. The aim of the present study was to evaluate the applicability of plasma-treated water (PTW) as antimicrobial process water additives for washing in fresh-cut lettuce processing. Antibacterial activities of PTW the natural occurring microflora of lettuce were examined. Different process variants of PTW application inside the washing process were investigated. Fresh-cut lettuce were investigated regarding microbiological safety and food quality. Samples were analyzed for antimicrobial and metabolic activity as well as metabolic vitality to prove food safety. The investigations for food quality included color and texture analyses and nitrate concentration detection in fresh tissue as well as microscopic measurements by scanning electron microscopy (SEM) and atomic force microscopy (AFM) for tissue surface structure and transmission electron microscopy (TEM) for cell organelle investigations. The application of PTW allowed up to 5 log10 cycle reduction, depending on the process variant and scale (lab and pilot scale). The increase of antimicrobial activity was accompanied by a reduction of metabolic activity, but not consequently by a decrease in metabolic vitality. Food quality was not affected by the use of PTW in the washing process of the fresh-cut lettuce. The promising results in color and texture were supported by the results of the microscopic assays. These promising results may lead to an industrial application of PTW as process water additive in fresh-cut produce processing to reduce the microbial load on the food surface and in addition in the process water or on food processing surfaces.

A decision support system for proactive failure prevention: a case in a leading automotive company

PurposeIn the automotive industry, the high process complexity becomes an important issue because of the increased number of product and process variants demanded by the customers. To avoid quality defects in assembly and losses in such a complex manufacturing environment, new predictive support systems are required. This study aims to develop a multiple attribute decision support system (DSS) for the prediction and quantification of the risk of failures on the workstations of a leading Turkish automotive manufacturing company.Design/methodology/approachInitially, the factors affecting the failures in workstations and the attributes to evaluate the factors are identified. Subsequently, the relations among the attributes are specified and priorities of them are calculated. Finally, the risk of failures is calculated and tested in a pilot study and validated with real production data.FindingsTo the best of authors’ knowledge, this is a unique study that computes the risk scores on the workstations via DSS. The DSS has various advantages for improvements of the manufacturing quality: the risk of failures can be detectable and comparable, the effect of changes in the design of new workstations can be observed. Stations that have medium or high complexity scores demonstrated strong correlation with failure rates. A sensitivity analysis is conducted to predict the effect of improvement actions on the riskiness of the workstations.Originality/valueHigh level of production complexity becomes a crucial issue for companies that use various production processes. Considering this fact, it is a requirement for companies to observe and monitor the risk factors, especially in the assembly lines to be able to eliminate failures derived from complexity. Accordingly, to measure risk scores of the workstations in the assembly lines, a decision support for companies aids executives to manage the complexity level in a reliable and effective way. In this study, the authors develop such a DSS for TOFAS, a leading Turkish automotive company. The proposed DSS is verified and applied through a pilot study on a specific basic production unit. A sensitivity analysis is also conducted to see the effects of potential improvements on the risk scores. Additionally, the trend of risk scores for the stations can also give valuable information for tracing the changes in the time horizon. The proposed DSS also enables an opportunity for the executives in their decision of design processes of new production lines by allocating limited resources in an appropriate way based on the risk scores of possible workstations. The proposed DSS is the first and unique proactive failure prevention model developed in a Fiat Chrysler Automobiles (FCA) plant across the world. TOFAS executives also plan to introduce and enlarge the usage of the model to other FCA plants. It may also be possible to apply the model to other assembly lines in any sector. Another plan of the executives of TOFAS is developing a software, which manages each parameter, to constitute data to the DSS to run this system more instantly and effectively. Moreover, they can take integration actions of the software with world-class manufacturing problem management system that is currently in use in TOFAS.

Assessing performance of mined business process variants

ABSTRACT Process mining can be used to discover different variants of a business process. To optimise the performance of the process, the best variant needs to be identified. However, process performance is multi-dimensional and how these dimensions weigh out against each other to find the best performing process is often unclear. This paper proposes to use conjoint analysis and regression analysis to assess the overall performance of different process variants discovered by process mining. The approach has been implemented in a visual tool and has been applied to an industrial case study.

Behind the scenes

Purpose Prior studies on product standardization–adaptation in multinational corporations (MNCs) have revealed environmental factors that can influence the choices of MNCs. However, these studies have not shown how these choices are made behind the scenes in new product development (NPD). In many industries, MNCs face the dual pressures for product standardization and adaptation from the environment. This study aims to explore how MNCs facing dual pressures can make choices of product standardization–adaptation in NPD. Design/methodology/approach A qualitative case study of four high-performing MNCs was conducted. The four MNCs were selected using the theoretical sampling approach. Data were collected, mainly through 74 semi-structured interviews. Coding was conducted and four aggregate dimensions were generated. Findings This study reveals that choices of product standardization–adaptation are made through a process in MNCs’ NPD, including four steps – organizing for NPD, organizational diversity, cross-unit integration and combination of design practices. In addition, MNCs adopt different process variants to address different environmental pressures. Research limitations/implications This research focuses on high-performing MNCs in manufacturing industries. Future research can explore different types of firms. Practical implications Managers in MNCs should focus more on the process of choices for product standardization–adaptation, than on the level of product standardization–adaptation. They should also keep monitoring the environmental pressure and employ experienced engineers. Originality/value By focusing on NPD, the authors shift the attention from product standardization–adaptation to product feature standardization–adaptation in MNCs, which is a fresh and refined perspective. The authors show a process in NPD composed of activities and mechanisms that managers might use for handling product standardization–adaptation challenges in MNCs. The authors contribute to the area of cross-unit integration in MNCs’ NPD by revealing mental mechanisms for mitigating tensions in cross-unit interactions.

Designing Isothermal Batch Deracemization Processes with Optimal Productivity: 1. Parametric Analysis Using a Population Balance Equation Model

Isothermal batch deracemization (Viedma ripening) is an attractive process variant to separate conglomerate forming enantiomers. These processes rely on a complex interplay between a racemization r...

Model-driven support for business process families with the Common Variability Language (CVL)

&#x0D; &#x0D; &#x0D; To achieve a business objective, organizations may require variants of the same business process that depend on the context in which they are enacted. Several proposals have emerged to deal with the variability of business processes, focused on the modeling of a so-called process family. The proposals try to avoid modeling each variant separately, which implies duplication and maintenance of the common parts. Few of them also focus on automatically deriving a process variant from the definition of a process family, which is a central and complex task. One of these proposals is the Common Variability Language (CVL), which allows representing variability transparently in a host language. This article aims to explore the use of CVL together with the Business Process Model and Notation (BPMN 2.0) for modeling business process families, and the use of Model-Driven Engineering (MDE) techniques for the automatic generation of process variants. We also present a graphical tool supporting these ideas and a qualitative evaluation of the variability approach by using the VIVACE framework.&#x0D; &#x0D; &#x0D;

THERMODYNAMIC LAWS OF CHROMIUM REDUCTION BY MIXTURES OF СН4 + Н2О AND СН4 + СО2

The development of a physico-chemical model of methane behavior in the processes of solid-phase reduction of chromium-containing raw materials will allow us to create the technological basis for the production of multicomponent sponge ligatures. The reduction of oxides with methane is accompanied by the deposition of soot carbon. The negative effect of carbon black, which is blocking the reaction surface, can be eliminated by adding carbon dioxide or water vapor to methane. A thermodynamic analysis of the reduction of chromium oxide with mixtures of CH4-CO2, CH4-H2O was carried out. The effect of the partial replacement of methane by carbon on the thermodynamic preferences of the process is analyzed. A physicochemical model of the behavior of the CH4 molecule in the recovery process is proposed. The thermodynamic features of reduction at various ratios of СН4 are considered: (Н2О, СО2, О2), as well as the composition of the mixture (Н2О+СО2+О2), which ensure the conditions of solid-phase reduction of oxides and the product of carbide destruction. The use of CH4 + H2O + O2 mixtures in the reduction of chromium oxide is thermodynamically less effective. The use of a mixture of СН4 + Н2О + СО2 has a very insignificant effect on the conversion of methane, and also reduces the thermodynamic preference for the reduction of Cr2O3 in comparison with СН4 + Н2О + О2 and СН4 + Н2О. However, it should be noted that in addition to CO and H2, carbon can be present in the reduction products, so the high reduction potential in this process variant (C+CO+H2) can be used to reduce oxides. The reduction of chromium oxide with mixtures of СН4 + Н2О + О2, СН4 + Н2О, and СН4 + Н2О + СО2 can be thermodynamically realized in the temperature range excluding the melting of the charge. As a result of this process, a carbide phase is formed, as well as a gas phase, which has a high reduction potential and can be used in further technological schemes. Meanwhile, it seems possible to control the carbon content in the sponge ligature by selecting the optimal composition of the source gas mixture.

Microstructural and Corrosion Resistance of Lean Duplex Stainless Steel UNS S32304 Welded by SAW with Cold Wire Addition

The results of the corrosion tests, in chloride environment, of lean duplex stainless steel UNS S32304 welded by submerged arc welding (SAW) process variant with cold wire, indicated that the sample with higher heat input heat input (HI) (2.7 kJ/mm) had higher corrosion resistance, which can be explained by higher amount of austenite and lower amount of precipitates. Therefore, the results indicate that the use of HI above the limit recommended by literature (2.5 kJ/mm) may produce welds with adequate corrosion resistance with SAW with cold wire addition, because this technique has the potential to deliver higher productivity still controlling the process HI.