Search

Organizations increasingly recognize the need to act in accordance with the idea of sustainable development. In the context of a production system, this is based not only on minimizing material losses but also on human support in the work process. The activities described in this article verify the operation of the system by collecting data on problems occurring during the production process, and the presented case study shows not only that companies do not always have to base their analyses on expensive solutions constructed on big data but they also misinterpret the causes of disruptions, which leads to further losses. This study presents an innovative system supporting the identification of downtime, and the results obtained allowed the examined organization to introduce changes based on specific premises, which led to reducing the waste of resources. The research carried out showed that it is not the excessive load on machines that is the problem but unnecessary downtime resulting from, for example, poor-quality materials for packaging goods. [ABSTRACT FROM AUTHOR]

This study aims to experimentally confirm whether knowledge that has been challenging to transfer through traditional on-the-job training (OJT) can be effectively transferred by introducing a formalized OJT approach that describes the improvement process knowledge of skilled production systems consultants, facilitating imitation by unskilled consultants. We adopted the Digital Triplet (D3) concept, an extension of the authors' digital twin framework to intelligent activities, aligning with our study objectives. Recognizing the difficulty and inadequacy of knowledge transfer in production systems consulting OJT, we propose an OJT support method integrating a decision-making modeling approach for skilled consultants' processes based on the Generalized Production Systems Consulting Process Model (GCPM) from prior literature into traditional OJT methods involving self-learning and direct instruction. This method enables the construction of a domain-specific GCPM, formalizing the improvement process flow implemented by skilled consultants and linking it to production improvement expertise and tools. In a case study focused on energy-saving improvement, we constructed and tested a domain-specific GCPM's efficacy in facilitating the transfer of difficult-to-transfer knowledge. The results indicate that domain-specific GCPM facilitates such knowledge transfer, including specialized improvement, knowledge utilization, rationale, and adaptation to specific cases. [ABSTRACT FROM AUTHOR]

The foundry industry is an important component of the economy on which other progressive industries depend. The reliability of the products it manufactures is determined by the technologies used, but, most importantly, it ensures the expected level of quality. The purpose of the article is to develop a synergistic quality-cost model for the improvement of casting products. The model is based on an integral methodological configuration that makes it possible to determine the level of relevance of the causes of casting nonconformity in the quality-cost context. The model integrates techniques such as the Pareto-Lorenz diagram, ranking, brainwriting, Ishikawa diagram, Likert rating scale, and matrix diagram. Verification of the method by its implication in the manufacturing process of a gearbox casting is performed. The model makes it possible to identify quality-cost relationships between key categories of problem causes and major product nonconformities. The main causes of the loss of quality stability of the analyzed product are found to be low quality of molding sand, poor technical condition of foundry equipment (too infrequent repairs and overhauls), and ineffective quality control. Carrying out the analysis made it possible to develop appropriate improvement measures. It is proposed to implement changes in the casting process, implement the TPM method, conduct periodic training, develop job instructions, implement a control system, and provide supervision of employees. Further research directions will concern the implications of the method within the other positions in the casting company and its development towards automation of analysis. [ABSTRACT FROM AUTHOR]

The productivity of the quarry during the wet season heavily depends on how well the personnel adjusts to the mine's environmental conditions and management plans. The improvement of granite production through workers' impact identification and mining advancement decision-making in Ondo State, Nigeria, has been considered in this study. The rate of granite production and the factors influencing workers’ efficiency were assessed using a well-structured survey and descriptive-analytic technique. To improve the production rate, the Multiple Criteria Decision-Making (MCDM) technique was used to select the most productive pit depending on a number of key labor impact factors. Health and safety in employment, the energy crisis, market conditions and level of competition, on-site accidents, natural disasters, and language barriers were some of the factors identified as external influencer factors affecting mine labor efficiency in granite quarrying. Finally, using the criteria's significance through the inter-criterion (CRITIC) approach, the mine workers’ influence on production was estimated and utilized for the best pit selection. The result of the MCDM revealed that the five pits (Pit 1, Pit 2, Pit 3, Pit 4, and Pit 5) had the following decision performance scores: 0.659, 0.617, 0.5, 0.5, and 0.5, respectively. This made Pit 1 the best production pit to be considered during the rainy season. The optimal solution was validated with the 2021 production report. The report shows that production from Pit 1 had the highest revenue of $16,000 Per annum, the lowest dewatering cost, and the highest production rate compared to the other four pits. [ABSTRACT FROM AUTHOR]

StrR-like pathway-specific transcriptional regulators (PSRs) function as activators in the biosynthesis of various antibiotics, including glycopeptides (GPAs), aminoglycosides, aminocoumarins, and ramoplanin-like lipodepsipeptides (LDPs). In particular, the roles of StrR-like PSRs have been previously investigated in the biosynthesis of streptomycin, novobiocin, GPAs like balhimycin, teicoplanin, and A40926, as well as LDP enduracidin. In the current study, we focused on StrR-like PSRs from the ramoplanin biosynthetic gene cluster (BGC) in Actinoplanes ramoplaninifer ATCC 33076 (Ramo5) and the chersinamycin BGC in Micromonospora chersina DSM 44151 (Chers28). Through the analysis of the amino acid sequences of Ramo5 and Chers28, we discovered that these proteins are phylogenetically distant from other experimentally investigated StrR PSRs, although all StrR-like PSRs found in BGCs for different antibiotics share a conserved secondary structure. To investigate whether Ramo5 and Chers28, given their phylogenetic positions, might influence the biosynthesis of other antibiotic pathways governed by StrR-like PSRs, the corresponding genes (ramo5 and chers28) were heterologously expressed in Actinoplanes teichomyceticus NRRL B-16726 and Nonomuraea gerenzanensis ATCC 39727, which produce the clinically-relevant GPAs teicoplanin and A40926, respectively. Recombinant strains of NRRL B-16726 and ATCC 39727 expressing chers28 exhibited improved antibiotic production, although the expression of ramo5 did not yield the same effect. These results demonstrate that some StrR-like PSRs can "cross-talk" between distant biosynthetic pathways and might be utilized as tools for the activation of silent BGCs regulated by StrR-like PSRs. [ABSTRACT FROM AUTHOR]

The paper examines the technological properties of diverse vanadium-containing raw materials, including titanium-magnetite concentrate, converter slag, dump sludge, neutralization sludge, slag from ferrovanadium smelting, fuel oil ash and slag, black shale, and spent catalysts. The existing chains of their formation and processing are described, considering the volume of raw materials underutilized for vanadium extraction, such as blast furnace slag, tailings, ilmenite concentrate, red mud, vanadium slag, and titanomagnetite concentrates. Most of these materials prove suitable for vanadium extraction. According to our estimates, annually produced industrial raw materials involve approximately 53.6 thousand tons of vanadium relative to V2O5. This includes 4.4 thousand tons of V2O5 suitable for extraction and 12.0 thousand tons of V2O5 potentially suitable for extraction. Additionally, about 28.5 thousand tons of vanadium relative to V2O5, found in titanium magnetite concentrates and converter slag, could be further engaged in processing. Consequently, the reserve of raw materials unused for vanadium extraction amounts to 45 thousand tons relative to V2O5. Processing these raw materials holds the potential to manufacture vanadium-containing products of a deeper degree of processing, including purified vanadium pentoxide V2O5, vanadium trioxide V2O3, and vanadium alloys, thereby reducing dependence on imported equivalents. [ABSTRACT FROM AUTHOR]

Milbemycins (MILs), a group of 16-membered insecticidal macrocylic lactones, are widely used as the biological pesticide and the precursors of semi-synthetic veterinary drugs. Polyketide synthases (PKSs), which require phosphopantetheinyl transferases (PPTases) to activate their ACP domains from apo forms to holo forms, catalyze the backbone biosynthesis of MILs. Here we found there was a complex phosphopantetheinylation network mediated by five putative PPTases in Streptomyces bingchenggensis. Repression mutants of PpA27 and PpA62 via CRISPRi both produced significantly lower yields of MILs than that of the control strain. Repression mutant of PpA68 led to abolishment of the pigment production. MILs production was significantly enhanced by PpA27 overexpression, while not by the overexpression of other PPTases. PpA27 was thus proved a dedicated post-translational enzyme to activate PKSs involved in the MILs biosynthesis. MILs titer was further enhanced by co-overexpression of PpA27 and MilR, the pathway‑specific transcriptional activator of MIL biosynthetic gene cluster. When PpA27 and MilR were co-overexpressed in the industrial S. bingchenggensis HMB, MILs production was increased by 40.5%. These results indicated that tuning the antibiotic biosynthetic pathway by co-engineering transcriptional regulation network and post-translational phosphopantetheinylation network is an effective strategy for antibiotic production improvement. [ABSTRACT FROM AUTHOR]

This study aims to experimentally confirm whether knowledge that has been challenging to transfer through traditional on-the-job training (OJT) can be effectively transferred by introducing a formalized OJT approach that describes the improvement process knowledge of skilled production systems consultants, facilitating imitation by unskilled consultants. We adopted the Digital Triplet (D3) concept, an extension of the authors’ digital twin framework to intelligent activities, aligning with our study objectives. Recognizing the difficulty and inadequacy of knowledge transfer in production systems consulting OJT, we propose an OJT support method integrating a decision-making modeling approach for skilled consultants’ processes based on the Generalized Production Systems Consulting Process Model (GCPM) from prior literature into traditional OJT methods involving self-learning and direct instruction. This method enables the construction of a domain-specific GCPM, formalizing the improvement process flow implemented by skilled consultants and linking it to production improvement expertise and tools. In a case study focused on energy-saving improvement, we constructed and tested a domain-specific GCPM’s efficacy in facilitating the transfer of difficult-to-transfer knowledge. The results indicate that domain-specific GCPM facilitates such knowledge transfer, including specialized improvement, knowledge utilization, rationale, and adaptation to specific cases.

AbstractThailand is among high-ranking coffee-exporting countries in the world. This study investigated, analyzed and proposed ideas for improved production of coffee to meet the demands from the local and international market. Using data collected from site visits, observation and interviews, value stream mapping analysis was used to identify the activities in the coffee production process. Automated machine deployment was used to improve the performance of coffee production. From the findings, it was shown that the total cycle time could be reduced by more than 82 %, the profit of sorted cherry coffee could be increased by 80%, and the processing time of green bean coffee could be reduced by almost 97%. An automated color sorting machine was deployed to improve the production process. With integrated lean and automated mechanization techniques, farmers can gain several benefits and become more responsive to future customer demands.

This study aims to analyze the process flow of skilled consultants who utilize production improvement know-how and digital technology to enhance production systems in external companies. The concept of a Digital Triplet (D3), which expands the authors' Digital Twin framework to include the intelligent activity world, is adopted as it aligns with this study's objective. Given the complexity of the problems faced by production system consulting and the resulting inadequacy of reusing decision-making processes of skilled engineers based on the Generalized Process Model (GPM) using D3, a production system consulting modeling method is proposed. This method incorporates the Generalized Production System Consulting Process Model (GCPM) to generalize the production system consulting process. Using the proposed method, a case study focusing on energy-saving improvements was conducted to describe and analyze the consulting process of skilled consultants. The results show that the proposed method effectively captures the process flow of skilled consultants while considering the iterative structure of the GCPM. Additionally, utilizing the GCPM enables a comprehensive view of the entire process, facilitating an understanding of how knowledge and tools are utilized in various contexts. [ABSTRACT FROM AUTHOR]

StrR-like pathway-specific transcriptional regulators (PSRs) function as activators in the biosynthesis of various antibiotics, including glycopeptides (GPAs), aminoglycosides, aminocoumarins, and ramoplanin-like lipodepsipeptides (LDPs). In particular, the roles of StrR-like PSRs have been previously investigated in the biosynthesis of streptomycin, novobiocin, GPAs like balhimycin, teicoplanin, and A40926, as well as LDP enduracidin. In the current study, we focused on StrR-like PSRs from the ramoplanin biosynthetic gene cluster (BGC) in Actinoplanes ramoplaninifer ATCC 33076 (Ramo5) and the chersinamycin BGC in Micromonospora chersina DSM 44151 (Chers28). Through the analysis of the amino acid sequences of Ramo5 and Chers28, we discovered that these proteins are phylogenetically distant from other experimentally investigated StrR PSRs, although all StrR-like PSRs found in BGCs for different antibiotics share a conserved secondary structure. To investigate whether Ramo5 and Chers28, given their phylogenetic positions, might influence the biosynthesis of other antibiotic pathways governed by StrR-like PSRs, the corresponding genes (ramo5 and chers28) were heterologously expressed in Actinoplanes teichomyceticus NRRL B-16726 and Nonomuraea gerenzanensis ATCC 39727, which produce the clinically-relevant GPAs teicoplanin and A40926, respectively. Recombinant strains of NRRL B-16726 and ATCC 39727 expressing chers28 exhibited improved antibiotic production, although the expression of ramo5 did not yield the same effect. These results demonstrate that some StrR-like PSRs can “cross-talk” between distant biosynthetic pathways and might be utilized as tools for the activation of silent BGCs regulated by StrR-like PSRs.

Objective: This study aims to identify waste and its causes in the production process and provide suggestions for improvement. Design/Methods/Approach: The author uses a qualitative research method approach to obtain research data. The author identifies the waste that occurs using Value Stream Mapping (VSM). Identify waste in the coffee bean production process using structured question weighting and direct interviews with several parties related to the production process, including the café owner, production manager, head barista, and two baristas in the production section. Findings: The waste causes that occur in the identified coffee production process are waiting time due to the first stage sorting process still using hands manually, the absence of tools, defects caused by the inevitable side effects of the roasting process, and unnecessary motion. After knowing the cause of the waste that occurred, the company was given a suggestion for improvement using 5W-1H tools, such as using a coffee sieve of a certain size for the first stage sorting process, making a new product in the form of ground coffee, processing defect coffee beans that always exist from the roasting results, and adding a fan and exhaust in the roasting room to reduce unnecessary movement during the process. Originality: The paper contributes to the limited literature on lean production in the coffee processing business and disseminates this information to improve production efficiency.

The global automotive manufacturing industry's growth in downtime reductio is substantial, valued at $3272.6 billion USD with a 3.01% growth rate.This growth in downtime reduction underscores the industry's commitment to enhancing efficiency, quality, and overall productivity across its diverse range of operations. Downtime in the braking system assembly line can lead to utilization loss or technical availability loss. In this context, many proactive maintenance strategies are explored but there's limited focus on addressing error-prone machines and utilizing Machine Learning for predicting downtime. The objective is to prioritize downtime reduction through error analysis, critical machine identification, and implementing ML-based solutions. This comprehensive research delved into the significance of minimizing downtime in the braking system final assembly line through meticulous data analysis, visualization techniques and targeted interventions and then identified key issues and achieved tangible improvements in operational efficiency. The analysis revealed significant findings and then employed the Pareto Principle to identify top downtime machines, illustrating their distribution through a Pareto chart of machine defects. Furthermore, Exceptions and Problem Areas were identified utilizing statistical process controls, offering insights into critical error contributors. Notably, a comprehensive exploration of the most prominent downtime machine was undertaken, evidenced by LCL and UCL charts and a Fishbone Diagram detailing causal relationships. The research leverages real-world data involving dates, machine names, and downtime durations to develop a predictive model that aids in proactively managing production disruptions. The application of RPN calculations before and after error correction demonstrated a substantial reduction from of 432 to 75, validating the efficacy of the corrective actions. The real time data was used to build a model that can predict when production machines downtime might happen. This helps us be prepared and manage any possible disruptions in production.The outcome of the project highlights the intrinsic link between downtime reduction and assembly line efficiency, emphasizing the importance of data-driven interventions. This culminated in the resolution of key issues, illustrated by the mitigation of the PCBA Pressin machine and LVDT sensor errors, yielding tangible reductions in downtime and notable productivity improvements. In this direction, exploring Ai driven predictive maintenance holds immense potential for advancing downtime reduction strategies. Leveraging AI algorithms to analyse live data streams from machinery and sensors can enable the detection of patterns indicating imminent failures and can pre-emptively prevent downtime. [ABSTRACT FROM AUTHOR]

This study aims to analyze the process flow of skilled consultants who utilize production improvement know-how and digital technology to enhance production systems in external companies. The concept of a Digital Triplet (D3), which expands the authors’ Digital Twin framework to include the intelligent activity world, is adopted as it aligns with this study’s objective. Given the complexity of the problems faced by production system consulting and the resulting inadequacy of reusing decision-making processes of skilled engineers based on the Generalized Process Model (GPM) using D3, a production system consulting modeling method is proposed. This method incorporates the Generalized Production System Consulting Process Model (GCPM) to generalize the production system consulting process. Using the proposed method, a case study focusing on energy-saving improvements was conducted to describe and analyze the consulting process of skilled consultants. The results show that the proposed method effectively captures the process flow of skilled consultants while considering the iterative structure of the GCPM. Additionally, utilizing the GCPM enables a comprehensive view of the entire process, facilitating an understanding of how knowledge and tools are utilized in various contexts.

In this paper, an active draghead visor controller is proposed based on DDPG (Deep Deterministic Policy Gradient)algorithm to optimize the output of loading process of TSHD. The controller will autonomously control the optimum visor angle relative to the ground according to the current working status of the draghead, and control the density of suction through the visor angle relative to the ground, thus controlling the instantaneous production of the undisturbed soil to optimize the production. The controller was verified on XINHAIHU8. Compared with human control, the active draghead visor controller based on DDPG algorithm can improve production effectively. [ABSTRACT FROM AUTHOR]

Objective: This study aims to identify waste and its causes in the production process and provide suggestions for improvement. Design/Methods/Approach: The author uses a qualitative research method approach to obtain research data. The author identifies the waste that occurs using Value Stream Mapping (VSM). Identify waste in the coffee bean production process using structured question weighting and direct interviews with several parties related to the production process, including the café owner, production manager, head barista, and two baristas in the production section. Findings: The waste causes that occur in the identified coffee production process are waiting time due to the first stage sorting process still using hands manually, the absence of tools, defects caused by the inevitable side effects of the roasting process, and unnecessary motion. After knowing the cause of the waste that occurred, the company was given a suggestion for improvement using 5W-1H tools, such as using a coffee sieve of a certain size for the first stage sorting process, making a new product in the form of ground coffee, processing defect coffee beans that always exist from the roasting results, and adding a fan and exhaust in the roasting room to reduce unnecessary movement during the process. Originality: The paper contributes to the limited literature on lean production in the coffee processing business and disseminates this information to improve production efficiency. [ABSTRACT FROM AUTHOR]

It is highly possible to obtain high-quality microbial products in appreciable amounts, as aerospace technology is advancing continuously. Genome-wide genetic variations in microorganisms can be triggered by space microgravity and radiation. Mutation rate is high, mutant range is wide, and final mutant character is stable. Therefore, space microorganism breeding is growing to be a new and promising area in microbial science and has greatly propelled the development of fermentation technology. Numerous studies have discovered the following improvements of fermentation potential in microorganisms after exposure to space: (1) reduction in fermentation cycle and increase in growth rate; (2) improvement of mixed fermentation species; (3) increase in bacterial conjugation efficiency and motility; (4) improvement of the bioactivity of various key enzymes and product quality; (5) enhancement of multiple adverse stress resistance; (6) improvement of fermentation metabolites, flavor, appearance, and stability. Aerospace fermentation technology predominantly contributes to bioprocessing in a microgravity environment. Unlike terrestrial fermentation, aerospace fermentation keeps cells suspended in the fluid medium without significant shear forces. Space radiation and microgravity have physical, chemical, and biological effects on mutant microorganisms by causing alternation in fluid dynamics and genome, transcriptome, proteome, and metabolome levels. [ABSTRACT FROM AUTHOR]

Cellulolytic enzymes play the most indispensable and centralized role in the hydrolysis of cellulosic material. Effective enzymatic hydrolysis is one of the major prerequisites in the development of a successful lignocellulosic biorefinery. However, the high cost of cellulase production yet remains to be the major bottleneck for large-scale commercial realization of lignocellusic bio-refinery. In addition, the lack of specificity and inconsistent bioconversion efficiencies of enzymes have restricted their applications towards bioconversion of narrow range of substrates. In view of addressing such bottlenecks associated with cellulase applications and further to improve the applicability of cellulase enzyme in various industrial processes, the current review essentially captures up-to-date information of various strategies adopted for the prospective production and purification of cellulase enzymes. Some holistic strategies deliberated in this review, which evolved over time and have brought about notable improvements in the final titer, yield, specificity, and productivity of the cellulolytic enzymes. It includes utilization of low-cost industrial or agricultural wastes for onsite production, application of enzyme, strain improvement through mutagenic, metabolic engineering and genetic engineering approaches, application of suitable bioprocess optimization techniques, development of ideal bioreactor configuration based on mode of fermentation process, and adaptation of the most intensive purification schemes. Additionally, to address the present existing challenges, more emphasizes have been concentrated towards economically sustainable and comprehensive production strategies of the enzyme. [ABSTRACT FROM AUTHOR]

Copyright of China Forest Products Industry is the property of China Forest Products Industry Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

For TOC (Theory of Constraints) implementation in a production system, the determination of the system's bottleneck is a crucial step. Effective bottleneck identification allows setting priorities for the improvement of a production system. The article deals with a significant problem for the manufacturing industry related to the location of a bottleneck. The article aims for a detailed analysis of methods for bottleneck identification based on a comprehensive literature review and the design of a generalised methodology for bottleneck identification in the production system. The article uses two research methods, first, the combination of a narrative and scoping literature review, and second, the logical design. Several methods for bottleneck identification are reviewed and compared, finding some being similar, and others giving new insights into the evaluated production system. A methodology for bottleneck identification is proposed. It contains several detailed methods arranged in coherent steps, which are suggested to be followed when aiming for the recognition of a production system's bottleneck. The proposed methodology is expected to be helpful in the practical TOC implementation. The presented methodology for the identification of bottlenecks in a production system is a practical tool for managers and experts dealing with TOC. However, it is still a conceptual proposal that needs to be tested empirically. The proposed methodology for bottleneck identification is an original concept based on the current literature output. It contributes to the production management theory as a practical managerial tool.

Abstract Plastic pollution is a severe threat to our environment which necessitates implementation of bioplastics to realize sustainable development for a green world. Polyhydroxyalkanoates (PHA) represent one of the potential candidates for these bioplastics. However, a major challenge faced by PHA is the high production cost which limits its commercial application. Halophiles are considered to be a promising cell factory for PHA synthesis due to its several unique characteristics including high salinity requirement preventing microbial contamination, high intracellular osmotic pressure allowing easy cell lysis for PHA recovery, and capability to utilize wide spectrum of low-cost substrates. Optimization of fermentation parameters has made it plausible to achieve large-scale production at low cost by using halophiles. Further deeper insights into halophiles have revealed the existence of diversified and even novel PHA synthetic pathways within different halophilic species that greatly affects PHA type. Thus, precise metabolic engineering of halophiles with the help of advanced tools and strategies have led to more efficient microbial cell factory for PHA production. This review is an endeavour to summarize the various research achievements in these areas which will help the readers to understand the current developments as well as the future efforts in PHA research.

Abstract Fusicocca-2,10(14)-diene (FCdiene) is a diterpene which is interesting as a precursor of the anti-cancer drug fusicoccin A and therefore for pharmaceutical applications. Production of FCdiene using a genetically modified Saccharomyces cerevisiae has been previously demonstrated with batch cultivations with a product concentration up to 10 mg/L. However, it is widely known that fed-batch processes can significantly improve product titer in yeast fermentations. This study focuses on the establishment of fed-batch fermentation for FCdiene production because fed-batch cultivations using FeedBeads® indicated that limiting glucose supply could increase yields of biomass (1.07 gCDW/gGlucose instead of 0.20 gCDW/gGlucose) and FCdiene (21.54 mgFCdiene/gGlucose instead of 9.74 mgFCdiene/gGlucose) in shake flask scale and may have implications for larger scale processes. We implemented a new exponential glucose feed profile in a 1.8 L stirred tank reactor. This reduced overfeeding and the consequent, ethanol production. As a result improvements in cell concentrations up to 246% could be achieved and FCdiene yield increased up to 2.8X in the first 28 h. FCdiene concentration reached 161 mg/L and 320 mg/L at 44 h. Fed-batch and batch mode were combined to examine dynamics of bi-modal cultivation where a fed-batch phase was used for biomass production and a batch phase used for FCdiene production potentially supported by ethanol consumption as reported on production of betulinic acid. The present study highlights the potential of process development improvements which increase high-value heterologous diterpene yields from S. cerevisiae.

Plastic pollution is a severe threat to our environment which necessitates implementation of bioplastics to realize sustainable development for a green world. Polyhydroxyalkanoates (PHA) represent one of the potential candidates for these bioplastics. However, a major challenge faced by PHA is the high production cost which limits its commercial application. Halophiles are considered to be a promising cell factory for PHA synthesis due to its several unique characteristics including high salinity requirement preventing microbial contamination, high intracellular osmotic pressure allowing easy cell lysis for PHA recovery, and capability to utilize wide spectrum of low-cost substrates. Optimization of fermentation parameters has made it plausible to achieve large-scale production at low cost by using halophiles. Further deeper insights into halophiles have revealed the existence of diversified and even novel PHA synthetic pathways within different halophilic species that greatly affects PHA type. Thus, precise metabolic engineering of halophiles with the help of advanced tools and strategies have led to more efficient microbial cell factory for PHA production. This review is an endeavour to summarize the various research achievements in these areas which will help the readers to understand the current developments as well as the future efforts in PHA research. [ABSTRACT FROM AUTHOR]

This work addresses an important problem in industry – locating the bottleneck in a production line – and suggests a practical approach to accomplish that end. We describe and validate, using discrete event simulation, a novel method of bottleneck detection in open, asynchronous serial production lines with finite buffers. The technique uses a single measure – station interdeparture time variance – to locate the system bottleneck. The proposed method is compared to other bottleneck detection approaches and it is shown that the proposed method performs as well and sometimes better than other methods. We conclude that the proposed approach has a number of significant advantages. It is easy to use and implement, not requiring data about failure and repair times, raw process times, buffer sizes, etc., but instead uses a single piece of easily obtained real-time production line data – station work-in-process (WIP) interdeparture time. The proposed method can identify production constraints without the need to build an analytical or simulation model, is well suited for use in industry, and can be readily implemented in standard simulation tools. [ABSTRACT FROM PUBLISHER]

Pottery is a gem in the history of human civilization and a crystallization of human wisdom. Yunnan Jianshui purple pottery is one of the four famous types of pottery in China, with a long history and superb craftsmanship. Used as tableware, research on the composition and element dissolution of pottery is extremely significant for production and health. This paper takes Jianshui purple pottery as its research object, samples its raw ores and finished products, and conducts X-ray fluorescence, scanning electron microscopy, inductively coupled plasma mass spectrometry experiments, and dissolution tests. The chemical composition, microstructure, and trace element concentrations of pottery before and after firing were measured. Results show that the dissolution of purple pottery under various use scenarios is low and meets health requirements. Combined with the characteristics of purple pottery, the composition changes and the mechanism of change before and after firing are discussed, which can be used as the theoretical basis for improving pottery production in the future.

The paper deals with the analysis of elements which represent a starting point in implementation of a business process reengineering. We have used Lean tools through the analysis of 5S model in our research. On the example of finalization of the finished transmitter in IHMT-CMT production, 5S tools were implemented with a focus on Quality elements although the theory shows that BPR and TQM are two opposite activities in an enterprise. We wanted to distinguish the significance of employees’ self-discipline which helps the process of product finalization to develop in time and without waste and losses. In addition, the employees keep their work place clean, tidy and functional.

A variety of organisms, such as bacteria, fungi, and plants, produce secondary metabolites, also known as natural products. Natural products have been a prolific source and an inspiration for numerous medical agents with widely divergent chemical structures and biological activities, including antimicrobial, immunosuppressive, anticancer, and anti-inflammatory activities, many of which have been developed as treatments and have potential therapeutic applications for human diseases. Aside from natural products, the recent development of recombinant DNA technology has sparked the development of a wide array of biopharmaceutical products, such as recombinant proteins, offering significant advances in treating a broad spectrum of medical illnesses and conditions. Herein, we will introduce the structures and diverse biological activities of natural products and recombinant proteins that have been exploited as valuable molecules in medicine, agriculture and insect control. In addition, we will explore past and ongoing efforts along with achievements in the development of robust and promising microorganisms as cell factories to produce biologically active molecules. Furthermore, we will review multi-disciplinary and comprehensive engineering approaches directed at improving yields of microbial production of natural products and proteins and generating novel molecules. Throughout this article, we will suggest ways in which microbial-derived biologically active molecular entities and their analogs could continue to inspire the development of new therapeutic agents in academia and industry. [ABSTRACT FROM AUTHOR]

The main purpose of this article is to present an author's methodology of production levelling and to show the impact of levelling on the time during which the product passes through the process and on staff performance. The article presents the analysis of literature concerning the method of improving the production process, especially taking production levelling into consideration. The authors focussed on the definition and methodologies of production levelling. A diagram of interrelations showing determinants and efficiency measures of production levelling as well as an author's production levelling methodology have been presented. An example of the implementation of production levelling in one of the departments of a company manufacturing surgical instruments has also been shown. Analysis of the current state, stages of implementation and end effects have been presented. Attention was focussed on the time during which the product passes through the process and on staff performance. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to explore how the acquisition experience – an acquiring firm's experience of acquiring and integrating the resources of an acquired firm – affects the production resource efficiency of the acquiring firm. Design/methodology/approach: The authors used data obtained from US manufacturing industries over the 1992–2014 period. The sample includes 784 acquisitions by 417 firms. The proposed hypotheses were tested through econometric analysis. Findings: Results show that the acquisition experience has a positive association with production resource efficiency. The acquisition experience is most positively associated with acquiring firms' production efficiency when they successfully accomplished previous performance outcomes. While the literature has recognized the relatedness of acquiring and acquired firms as a contextual moderator, the interaction of the related acquisition and the acquisition experience has no impact on efficiency benefits. Originality/value: This study enhances the understanding of how prior acquisition experience can be leveraged by acquiring firms to gain efficiency benefits in the manufacturing industry. [ABSTRACT FROM AUTHOR]

Drilling and completion techniques in petroleum industries have advanced significantly over the last few decades to improve the recovery from hydrocarbon reservoirs. The conventional method of drilling followed by well completion is replaced by various intelligent ways, which effectively support the production improvement. Smart well completion is one of these intelligent or modern techniques that include permanent downhole sensors and surface-controlled downhole flow control valves, allowing to record, evaluate, and actively manage production in real time without any well interventions. In addition, Smart wells provide the ability to control uncertainties associated with reservoir heterogeneity. These mitigate unexpected sand production due to fractures and hence increase the ultimate recovery. The design, selection and installation of different tools and equipments in a smart well completion are conducted in an effective manner so that the wells can be brought into production within the operator's objectives for the field development. Once a smart well is developed, valves can be used to independently control each segment/branch of the well in a reactive mode, such as shutting off a zone when it starts producing water; or in a defensive mode, which requires a prior determination of valve settings. The smart well system is comprised of different downhole sensors and valves which facilitate to improve the performance of the well, literally signifies the improvement of productivity and bypassing different unwanted occurrences. Various objectives are served like water cut minimization, and net present value maximization. Besides the sand production can also be minimized which causes serious distortion in the production scenario. So the intelligent completion method of production well can destine towards a logical and effective stability. In this paper, the completion system of a smart well is reviewed and presented with its pros and cons. The proper arrangement structure is furnished here which will be helpful to get a clear idea about the smartest completion outlook and can be effectively used for further practical applications. [ABSTRACT FROM AUTHOR]

Objective: To develop a reliable and easy to use expression system for antibiotic production improvement of Streptomyces. Results: A two-compound T7 RNA polymerase-dependent gene expression system was developed to fulfill this demand. In this system, the T7 RNA polymerase coding sequence was optimized based on the codon usage of Streptomyces coelicolor. To evaluate the functionality of this system, we constructed an activator gene overexpression strain for enhancement of actinorhodin production. By overexpression of the positive regulator actII- ORF4 with this system, the maximum actinorhodin yield of engineered strain was 15-fold higher and the fermentation time was decreased by 48 h. Conclusion: The modified two-compound T7 expression system improves both antibiotic production and accelerates the fermentation process in Streptomyces. This provides a general and useful strategy for strain improvement of important antibiotic producing Streptomyces strains. [ABSTRACT FROM AUTHOR]