Factory Performance Research Articles

A Cloud-based Digital Twin Manufacturing System based on an Interoperable Data Schema for Smart Manufacturing

ABSTRACT The worldwide manufacturing industry is facing a wide range of changes. Examples include the diversification of customer demands, increases in labor costs and energy resource costs, environmental pollution, and growth uncertainty. Based on the experience of advanced countries and global manufacturers, smart manufacturing systems (SMS) have the potential to address these. SMS can connect raw materials, production systems, logistic companies, and maintenance schedules using the capabilities of industrial, internet of things (IoT). These connections are creating cyber-physical production systems (CPPS) and linking functions across the entire product lifecycle. These connections are possible today because of the advances in digital manufacturing (DM) technologies that can facilitate factory design, redesign, and analysis in CPPS and help to continuously and efficiently manage factory performance optimization. However, implementing DM today, especially in SMEs, is difficult because the required interface standards and data schema do not exist – unlike other technologies and system such as CAD, PLM, MES, and SCM. This paper describes an approach to design and develop such a data schema based on a reference activity model developed by NIST. The paper then develops a cloud-based DM system based on the data schema. Lastly, its application cases are described, and application effects are discussed.

Pengaruh Kapasitas Olah, Ketersediaan Bahan Baku dan Capaian Rendemen Terhadap Harga Pokok Pengolahan Pabrik Kelapa Sawit di Pabrik Kelapa Sawit Torgamba PT. Perkebunan Nusantara III (Persero)

Palm oil was first introduced in Indonesia by the Dutch government in 1848, at that time there were 4 oil palm seedlings planted at Bogor Botanical Garden (Botanical Garden) in Bogor, two from Bourbon (Mauritius) and two from the Hortus Botanicus, Amsterdam ( Netherlands). Currently the development of oil palm cultivation is increasing with an area of 2017 covering 11.5 million hectares and the production of palm oil (CPO) has reached ± 30 million tons in 2018. The main objective of this research is to find out the influence of the increase of capacity achievement, availability of raw materials and the achievement of oil and palm kernel oil to the performance of oil palm factory, especially the cost of processing so that it can give added value to the company. Based on the result of the research, it is known that the capacity of X1 is negative but not significant. This is in accordance with the hypothesis, the availability of raw material (X2) is negative but not significant and the yield of rendement (X3) is negative but not significant this is in accordance with the hypothesis and capacity though, the availability of raw materials and yields of yields together have a significant effect on the cost of processing. On the basis of this, then the management should increase attention to the capacity of the process, the availability of raw materials and the achievement of rendemen to minimize the basic price.

Safety requirements for symbiotic human–robot collaboration systems in smart factories: a pairwise comparison approach to explore requirements dependencies

Industry 4.0 is expected to deliver significant productivity gain taking advantage of Internet of things (IoT). Smart solutions, enhanced by IoT, are constantly driving revolutionary approaches in multiple domains. Smart factories are one domain where intelligent integrated robotic systems will revolutionize manufacturing, resulting in a complex ecosystem, where humans, robots and machinery are combined. In this setting, human safety requirements are of paramount importance. This paper focuses on symbiotic human–robot collaboration systems (HRC), where human safety requirements are essential. Hence, it aims to explore and prioritize human safety requirement dependencies, as well as their dependencies with other critical requirements of smart factory operation, as effectiveness and performance. Toward this end, the proposed approach is based on SysML to represent the requirements dependencies and pairwise comparisons, a fundamental decision-making method, to quantify the importance of these dependencies. This model-driven approach is used as the primary medium for conveying traceability among human safety requirements as well as traceability from safety requirements to effectiveness and performance requirements in the system model. The analysis is based on the operational requirements identified in the European project HORSE, which aims to develop a methodological/technical framework for easy adaptation of robotic solutions from small-/medium-sized enterprises. Validation of the results is also performed to further elaborate on human safety requirement dependency exploration. The outcomes of this paper may be beneficial for symbiotic HRC systems in the early design stage. As the system is being developed with an emphasis on human safety, all these requirements that have been assessed with highly prioritized dependencies should be taken into account, whereas those with negligible ones have to be ignored since they do not significantly affect the rest of the process. Since operational requirements may be conflicted and incompatible, this approach may be very useful for other systems as well during the system design phase to find the appropriate solution satisfying the majority of the requirements, giving a priority to the ones with highly ranked dependencies and hence facilitating the implementation phase and afterward the production line. The outcomes may be used as a step in developing a model-driven approach which should be able to support the manufacturing process, facilitating the integration of systems and software modeling, which is increasingly important for robotic systems in smart factories incorporating HRC.

Performance Evaluation of Seismic Stopper using Structural Analysis and AC156 Test Method

Recently, studies have been actively conducted on seismic design and improvement of the seismic performance of bridges, buildings, factories, and plants. In particular, heavy items that are being manufactured or waiting to be shipped from factories (such as generators, engines, and boilers) must be equipped with seismic stoppers to prevent them from moving or falling during an earthquake. Seismic stoppers should be suitably determined by the size and weight of these heavy items; however, they have no general design standard. In this study, structural analyses and seismic tests were conducted to evaluate the performance of newly designed seismic stoppers. Structural analysis was performed on three stopper models to estimate the external load at which the yield stress of the material was not exceeded. Based on the analysis results, a seismic test of the stopper was carried out in accordance with the AC156 test method. Finally, product specifications for all three seismic stopper models were determined and their static/dynamic load performance was evaluated.

Reverse engineering of fatty acid-tolerant Escherichia coli identifies design strategies for robust microbial cell factories

Adaptive laboratory evolution is often used to improve the performance of microbial cell factories. Reverse engineering of evolved strains enables learning and subsequent incorporation of novel design strategies via the design-build-test-learn cycle. Here, we reverse engineer a strain of Escherichia coli previously evolved for increased tolerance of octanoic acid (C8), an attractive biorenewable chemical, resulting in increased C8 production, increased butanol tolerance, and altered membrane properties. Here, evolution was determined to have occurred first through the restoration of WaaG activity, involved in the production of lipopolysaccharides, then an amino acid change in RpoC, a subunit of RNA polymerase, and finally mutation of the BasS-BasR two component system. All three mutations were required in order to reproduce the increased growth rate in the presence of 20 mM C8 and increased cell surface hydrophobicity; the WaaG and RpoC mutations both contributed to increased C8 titers, with the RpoC mutation appearing to be the major driver of this effect. Each of these mutations contributed to changes in the cell membrane. Increased membrane integrity and rigidity and decreased abundance of extracellular polymeric substances can be attributed to the restoration of WaaG. The increase in average lipid tail length can be attributed to the RpoCH419P mutation, which also confers tolerance to other industrially-relevant inhibitors, such as furfural, vanillin and n-butanol. The RpoCH419P mutation may impact binding or function of the stringent response alarmone ppGpp to RpoC site 1. Each of these mutations provides novel strategies for engineering microbial robustness, particularly at the level of the microbial cell membrane.

Green construction performance – A study on stakeholders’ perceptions

This study is conducted to explore stakeholders’ understanding of the performance of green-certified factories in the South of Vietnam. The study, based on the LEED Rating system, employs a qualitative approach to address objectives and in-depth interviews with 43 respondents including employees, managers, and buyers of green factories to collect data. The categories taken from LEED such as Water Efficiency, Indoor environmental quality, Energy & atmosphere, Resources & materials, Sustainable sites are used as the main analytical basis. To tackle the research objective, the study aims (1) to explore stakeholders’ awareness of green factories’ performance, and (2) to propose recommendations to enhance the effectiveness of green factories. The research findings show that, in general, stakeholders are satisfied with the performance of green factories. Nevertheless, there are some differences in the awareness of stakeholders working in small and large size green factories in a comparison with LEED. Finally, some suggestions are proposed to enhance the performance of green factories.

Calibration point distribution study of a four-wheel alignment optimization device based on a blanket technology algorithm.

Optimal wheel alignment improves fuel efficiency, safety, and driver comfort. An explicit formula for determining kingpin parameters, namely, caster and kingpin inclination angle (KIA), in four-wheel alignment is lacking. Currently, caster and KIA values are estimated by repetitive large-scale computing with a mathematical model aimed at obtaining values infinitely close to real solutions. In this study, a four-wheel aligner calibration device was used to collect large amounts of data for a variety of four-wheel aligner measurements with a short data interval. The data were subjected to the local fractal dimension analysis with fractional dimension-based blanket technology (BT) to optimize the number of measurement points. Dramatic changes in data were attributable to local areas with a large fractional number dimension. Appropriate increase in the number of calibration measuring points in areas with a relatively low fractional number dimension can reduce the overall quantity of measuring points. The results provide a scientific basis for the development of alignment calibration standards and demonstrate that these parameters can be assessed based on a small number of measurements. Our BT-based methodology can facilitate factory inspection and performance testing of four-wheel aligners and may improve the accuracy of wheel positioning parameter assessments.

국내 태양광발전시스템 적합성 평가를 위한 기술기준

Currently, KS certification system for new and renewable energy facilities in Korea is operated at the level of issuing KS certification mark through factory audit and performance audit by individual product unit. Therefore, the technical standards and performance evaluation when constructing the system by organically integrating each subsystem such as PV inverter, photovoltaic module, photovoltaic junction box, and monitoring device. In this regard, it is not currently reflected in the KS certification system for new and renewable energy facilities in Korea. In addition, domestic photovoltaic power generation system construction is being supplied to public institutions and government offices through the Public Procurement Service’s excellent product system. Only the GS-certified product registered in the copyright and technology development successful product of R&D business is applied, but the performance evaluation of the technical standard of each system unit is not made. As a result, most of the domestic photovoltaic power generation system builders are evaluated for the performance of the photovoltaic power generation system by issuing a report through their own test evaluation by a domestic accredited testing institute for the purpose of registering the successful product development of the R&D business of the excellent product system. Therefore, in this paper, we propose a specification related to system diagnosis evaluation through status information in case of interoperation and abnormality between subsystems.

Integration of Lean practices and Industry 4.0 technologies: smart manufacturing for next-generation enterprises

Industry 4.0 technologies have attempted to transform current industrial settings to a level that we have never seen before. While at the same time, prevailing applications of Lean tools and techniques over the last 20 years have already dramatically reduced wastes ranging from shop floor production to cross-functional enterprise processes. This paper aims to provide a comprehensive review and report on links between Lean tools and Industry 4.0 technologies, and on how simultaneous implementation of these two paradigms affects the operational performance of factories. The existing and potential enhancements of Lean practices enabled by Industry 4.0 technologies such as wireless networks, big data, cloud computing, and virtual reality (VR) will also be explored. A cloud-based Kanban decision support system is also presented as a real-world demonstrator for integration of an Industry 4.0 technology (cloud computing) and a major Lean tool (Kanban).

Engineering Escherichia coli lifespan for enhancing chemical production

Industrial chemical production from renewable feedstocks by microbial cell factories provides a promising avenue towards sustainability. However, the small size of bacterial cells and environmental stress significantly affect microbial cell factory performance. Here, we engineered the Escherichia coli lifespan to improve the chemical production of poly(lactate-co-3-hydroxybutyrate) and butyrate. The replicative lifespan was shortened by deleting a carbon storage regulator, and the chronological lifespan was extended by deleting a response regulator and overexpressing sigma-38 in Escherichia coli. The replicative lifespan was fine-tuned using a two-output recombinase-based state machine, and the cell size was enlarged 13.4-fold. The highest poly(lactate-co-3-hydroxybutyrate) content of 52 wt% was achieved in a 5-l fermenter. The chronological lifespan was modulated through a multi-output recombinase-based state machine, resulting in the highest butyrate titre of 29.8 g l−1, by programming cell differentiation according to different fermentation stages. These results highlight the applicability of engineering the bacterial lifespan to increase microbial cell factory performance. To implement more sustainable processes in industry, a high efficiency of microbial biocatalytic systems for the production of industrial chemicals from renewable feedstocks is important. Now, engineering the lifespan of Escherichia coli is presented as a platform technology for improving the bioproduction of chemicals.

Smart factory performance and Industry 4.0

Existing literature on the Industry 4.0 concept does not empirically verify if, how, and for which types of firms, a greater openness to enabling technologies of Industry 4.0 provides further opportunities. This study analyzes the causal relationship between this degree of openness and performance, with an empirical analysis based on a sample representing local manufacturing units. Performance is measured by the extent of opportunities businesses obtain. The degree of openness is investigated using two indicators: breadth, or the number of technologies used; and depth, or the number of value chain stages involved. The regression models demonstrate that: (1) breadth and (2) depth of Industry 4.0 allow greater opportunities, and (3) micro-level local units achieve best performances. Verifying the opportunities for companies with Industry 4.0 is extremely relevant, as investments in Industry 4.0 are high in terms of costs, the acquisition of new skills, and the risks of obsolescence to enable better strategic decisions. This work also provides a scope for future analyses of this topic conducted on panel data. Despite the limited application of Industry 4.0, this study's results can encourage managers and policy-makers to implement a wider range of enabling technologies in the various stages of the value chain.

The impact of workplace harassment and domestic violence on work outcomes in the developing world

Workers’ mistreatment is a serious problem, particularly for disadvantaged populations in the global garment supply chain who are often subjected to human and labor rights violations. Workplace abuses are believed to originate from human resource management practices, which aim to reduce production costs and achieve inflated production targets. Improvements in worker well-being are often perceived as costs rather than investments. Family life might be an equally important contributor to workers’ well-being and factory outcomes, yet its impact often remains completely beyond the scope of interest of local factory management and the leadership of companies at the top of the supply chain. This study addressed the prevalence of workplace harassment (WH) and domestic violence (DV) in the garment industry in Mexico, Sri Lanka, China and Cambodia and the impacts of WH and DV on outcomes related to withdrawal from work (intentions to leave, quitting, and limited abilities to perform usual tasks), work attitudes (work engagement and job satisfaction) and self-reported work quality. Survey data from 5328 garment industry workers from four countries and information from personnel files are used. The relationships are modelled using linear, logistic or Cox proportional hazard regressions. The results from the longitudinal subsample substantiate the robustness of the findings. WH and DV are found to be significant stressors and affect withdrawal from work, work attitudes and work quality. Contrary to common belief, the findings do not reveal that WH and DV contribute to decisions to quit; however, they were found to impact intentions to leave. The results from the longitudinal sample corroborate the influence of WH and DV on work outcomes. The results of this study convey a message to global brands and factory managers to foster worker well-being, which may improve factory performance.

Contextualized genome-scale model unveils high-order metabolic effects of the specific growth rate and oxygenation level in recombinant Pichia pastoris

Pichia pastoris is recognized as a biotechnological workhorse for recombinant protein expression. The metabolic performance of this microorganism depends on genetic makeup and culture conditions, amongst which the specific growth rate and oxygenation level are critical. Despite their importance, only their individual effects have been assessed so far, and thus their combined effects and metabolic consequences still remain to be elucidated. In this work, we present a comprehensive framework for revealing high-order (i.e., individual and combined) metabolic effects of the above parameters in glucose-limited continuous cultures of P. pastoris, using thaumatin production as a case study. Specifically, we employed a rational experimental design to calculate statistically significant metabolic effects from multiple chemostat data, which were later contextualized using a refined and highly predictive genome-scale metabolic model of this yeast under the simulated conditions. Our results revealed a negative effect of the oxygenation on the specific product formation rate (thaumatin), and a positive effect on the biomass yield. Notably, we identified a novel positive combined effect of both the specific growth rate and oxygenation level on the specific product formation rate. Finally, model predictions indicated an opposite relationship between the oxygenation level and the growth-associated maintenance energy (GAME) requirement, suggesting a linear GAME decrease of 0.56 mmol ATP/gDCW per each 1% increase in oxygenation level, which translated into a 44% higher metabolic cost under low oxygenation compared to high oxygenation. Overall, this work provides a systematic framework for mapping high-order metabolic effects of different culture parameters on the performance of a microbial cell factory. Particularly in this case, it provided valuable insights about optimal operational conditions for protein production in P. pastoris.

Design for improvement of sugar factory performance based on statistical thinking

The amount of sugar production is determined, among others, by the quality of sugar cane and the performance of sugar factory equipment. The quality of sugar cane as an agricultural product is influenced by the quality of sugar cane seeds, soil conditions and climate. The differences in the factors affect the quality of sugarcane production. Sugarcane milling is not based on the quality of sugarcane but on the arrival time to the factory. Under this condition, different sugarcane qualities will be milled together. As a consequence, it may not yield the optimal sugar production. In the sugar production process, equipment performance must always be monitored. Equipment failure will reduce the amount of sugar produced. Therefore, efforts to increase sugar production must consider both factors, namely the variation of input quality and monitoring of equipment performance. One approach in solving this problem is statistical thinking approach. The purpose of the paper is to design the performance improvement of sugar factory based on statistical thinking. The improving activity based on statistical thinking will concentrate on manufacturing process enhancement and problem breaking that rely on realizing and degrading variation. The study shows that the statistical thinking approach potentially able to increase sugar production using process enhancement framework and overcome factory equipment failure using problem breaking framework.

An integrated and parametric simulation model to improve production and maintenance processes: Towards a digital factory performance

In recent years with the emergence of the concept of Industry 4.0 digitalization is transforming the industrial scenario. A great attention is focused on integrated simulation system, an emerging enabling technology, as a particular decision support tool, to represent the increasingly complex modern production systems. The advantage is that it is possible to perform simulations and reconfigure models to evaluate modified or alternative scenarios to achieve current demands of increasingly competitive markets. The aim of the present research is the definition of an integrated parametric simulation model for integration management enhancing the production and maintenance process. Thus, a framework for implementing simulation models that help production and maintenance managers to make cost-effective decisions as well as optimize the use of resources is developed. System Dynamics approach is used to simulate, through PowerSim Software®, the nonlinear behavior of the analyzed complex systems over time. The results revealed that the proposed simulation optimization procedure can be used to solve and to manage complexity in a ‘‘real-time’’. Furthermore, the output of this simulation optimization procedure gives the decision maker the most probable scenario.

The Effect of Work Culture and Organizational Commitments to Performance of Employees Factory of Pt Semen Baturaja (Persero) Tbk

this research aims to analyzes the influence of work culture and organizational commitment on the performance of PT. Semen Baturaja (Persero) Tbk. The analysis technique used is multiple linear regression analysis with a sample of 181 employees of PT. Semen Baturaja (Persero) Tbk. The results of the study can be concluded that the independent variables namely work culture and organizational commitment can influence employee performance significantly in PT. Semen Baturaja (Persero) Tbk.

Can smart factories bring environmental benefits to their products?: A case study of household refrigerators

AbstractSmart factories have been widely adopted as a new manufacturing paradigm, in which the state‐of‐the‐art technologies are introduced to improve relevant processes. Yet, whether smart factories affect the environmental performance remains unknown. In this article, we examine the environmental performance of a smart refrigerator factory by comparing the environmental impacts of its product to a similar model that is produced in a traditional fashion. This article quantifies and verifies the theoretically predicted impacts of this smart factory on the individual processes. Though the overall differences in the two models are quite minor, we find that this smart factory can notably reduce the values of most impact categories associated with the parts and refrigerator production; the reduction in the value of climate change is 33%. Owing to higher material efficiency—raw material savings in this smart factory contributes to the greatest reductions in most categorized impacts—the contribution to the reduction of climate change is 39%. Yet, all categorized impacts of procurement and delivery are increased due to product personalization and direct delivery. The results of sensitivity analysis show that promoting product modularity, adopting clean energy such as wind power can further improve the environmental performance of the selected refrigerator. The introduction of auxiliary equipment and systems slightly increases the value of each category; yet their impacts are negligible compared to their benefits as facilitating production efficiency. Based on the quantitative results, recommendations are given to improve the environmental performance of smart factory, including optimizing current strategies and promoting horizontal and end‐to‐end integration.

Build Your Bioprocess on a Solid Strain-β-Carotene Production in Recombinant Saccharomyces cerevisiae.

Robust fermentation performance of microbial cell factories is critical for successful scaling of a biotechnological process. From shake flask cultivations to industrial-scale bioreactors, consistent strain behavior is fundamental to achieve the production targets. To assert the importance of this feature, we evaluated the impact of the yeast strain design and construction method on process scalability -from shake flasks to bench-scale fed-batch fermentations- using two recombinant Saccharomyces cerevisiae strains capable of producing β-carotene; SM14 and βcar1.2 strains. SM14 strain, obtained previously from adaptive evolution experiments, was capable to accumulate up to 21 mg/gDCW of β-carotene in 72 h shake flask cultures; while the βcar1.2, constructed by overexpression of carotenogenic genes, only accumulated 5.8 mg/gDCW of carotene. Surprisingly, fed-batch cultivation of these strains in 1L bioreactors resulted in opposite performances. βcar1.2 strain reached much higher biomass and β-carotene productivities (1.57 g/L/h and 10.9 mg/L/h, respectively) than SM14 strain (0.48 g/L/h and 3.1 mg/L/h, respectively). Final β-carotene titers were 210 and 750 mg/L after 80 h cultivation for SM14 and βcar1.2 strains, respectively. Our results indicate that these substantial differences in fermentation parameters are mainly a consequence of the exacerbated Crabtree effect of the SM14 strain. We also found that the strategy used to integrate the carotenogenic genes into the chromosomes affected the genetic stability of strains, although the impact was significantly minor. Overall, our results indicate that shake flasks fermentation parameters are poor predictors of the fermentation performance under industrial-like conditions, and that appropriate construction designs and performance tests must be conducted to properly assess the scalability of the strain and the bioprocess.

Науково-інноваційне забезпечення розвитку агропромислового виробництва Центрального регіону

The purpose. Filling up agrarian market of Central region of Ukraine with scientific-and-innovative products and increase of level of development of agricultural factories in state-of-the-art conditions of managing. Methods. Statistical-economic analysis, simulation, questioning, comparison, synthesis. Results. Scientific-and-organizational approaches, and market-oriented tools of experimental production and transfer of high technology products in agrarian and industrial complex of region are developed. Assessment of state-of-the-art situation and perspectives of innovative evolution of agricultural factories is carried out. Suggestions on filling up agrarian market with innovative products are elaborated: scientific-and-consulting and informational services through architecture of conferences, seminars, «Days of field», «Circular tables», courses, exhibitions-fairs; creation of scientific-and-demonstration and technological proving grounds, demonstration farms; publications in issuings, performances on radio and television, spread of booklets and issuings of recommendations. Data bank is created of the completed scientific developments (innovations) that are recommended for mastering in soil-climatic conditions of Kirovograd region, Portfolio for orders of innovative products (seeds, pedigree resources, hardware components, etc.) is generated. Conclusions. Analysis of overall performance of agricultural factories of Kirovograd region proves that nowadays only those of them which use innovative development and constantly or very often use scientific reaching at production of agricultural produce have stable financial and economic state. Mainly they are large enough factories which spend renewal of basic production assets and annually restore high quality content of cultivated crops. Application of innovations ensures resistant economic propagation, raises industrial and social evolution of a society, secures economic safety and stability.

Research on optimum joint operation with various hydraulic systems basing on AB line and C line of Uzbekistan section in trans-asian natural gas pipeline

AB line and C line of Trans-Asia natural gas pipeline has attained a gas transmission capacity as 55 billion cubic meters per year. In recent years, pipeline transportation throughput accounts for about 20% of Chinese apparent consumption of natural gas. In order to ensure an economic and efficient operation of this transnational pipeline system, this paper conducts a comprehensive study on the joint operation of AB line and C line of Uzbekistan section of Trans-Asia natural gas pipeline. This paper innovatively puts forward “Methods of correction on multi-pressure head and multi-performance curve of centrifugal compressor”, aka. Data difference adjustment method”, to correct the factory performance curve of compressor, to ensure that the simulation accuracy is higher than 95%, and to provide support for operation decision-making. Based on the principle of minimum energy consumption of AB line and C line system of Trans-Asian natural gas pipeline, a set of optimal air intake allocation scheme between AB and C lines is studied and integration method of process operation scheme of AB line and C line are studied to support the optimum operation. Pipeline joint operation method for different hydraulic systems is studied. The pressure control principle by pressure balance method which realizes the joint operation of pipelines from different hydraulic systems is suggested for the first time, by which the pipeline operates stably. This paper studies the best location of 8 bridges reservations in AB line and C line in Uzbekistan, in order to enhance the comprehensively allocation capability of the whole system of transnational pipeline network in an all-round way, and to realize the function of energy conservation under normal conditions and of throughput guarantee under abnormal conditions. With additional bridges, pipeline transportation capacity can be increased up to 26 million m3/day and save energy consumption by up to 660 thousand m3/day under accident conditions.