Short Throughput Times Research Articles

Quality-based scheduling for a flexible job shop

Recent developments in food consumption open up new challenges in production control in manufacturing systems with low levels of automation. The demand for fresh and healthy products, in combination with the demand for processed products, requires short throughput times and attribution of exposure to process-specific, time-sensitive negative quality influences on certain products. Therefore, this article presents a framework incorporating quality aspects into production planning and control by developing mixed-integer linear programming for scheduling and integrating it into simulation-based control for sequencing. The article applies this framework to a flexible job shop problem derived from a real-world use case. The resulting schedules are used in a simulation model using different order release schemes and priority rules to test how the scheduling approach could deal with dynamic manufacturing environments. The evaluation shows the satisfying integration of quality issues in a flexible job shop problem by minimizing the deterioration while not compromising on makespan and utilization.

A New Heart-Cutting Method for a Multiplex Quantitative Analysis of Steroid Hormones in Plasma Using 2D-LC/MS/MS Technique.

The aim of the current research was to develop a simple and rapid mass spectrometry-based assay for the determination of 15 steroid hormones in human plasma in a single run, which would be suitable for a routine practice setting. For this purpose, we designed a procedure based on the 2D-liquid chromatography-tandem mass spectrometry with a minimalistic sample pre-treatment. In our arrangement, the preparation of one sample takes only 10 min and can accommodate 40 samples per hour when tested in series. The following analytical run is 18 min long for all steroid hormones. In addition, we developed an independent analytical run for estradiol, significantly increasing the assay accuracy while taking an additional 10 min to perform an analytical run of a sample. The optimized method was applied to a set of human plasma samples, including chylous. Our results indicate the linearity of the method for all steroid hormones with squared regression coefficients R2 ≥ 0.995, within-run and between-run precision (RSD < 6.4%), and an accuracy of 92.9% to 106.2%. The absolute recovery for each analyzed steroid hormone ranged between 101.6% and 116.5%. The method detection limit for 15 steroid hormones ranged between 0.008 nmol/L (2.88 pg/mL) for aldosterone and 0.873 nmol/L (0.252 ng/mL) for DHEA. For all the analytes, the lowest calibration point relative standard deviation was less than 10.8%, indicating a good precision of the assay within the lowest concentration of interest. In conclusion, in this method article, we describe a simple, sensitive, and cost-effective 2D-LC/MS/MS method suitable for the routine analysis of a complex of steroid hormones allowing high analytical specificity and sensitivity despite minimal sample processing and short throughput times.

Reducing Lifecycle Costs due to Profile Scanning of the Powder Bed in Metal Printing

First time right is one major goal in powder based 3D metal printing. Reaching this goal is driven by reducing life cycle costs for quality measures, to minimize scrap rate and to increase productivity under optimal resource efficiency. Therefore, monitoring the state of the powder bed for each printed layer is state of the art in selective laser melting. In the most modern approaches the quality monitoring is done by computer vision systems working with an interference on trained neural networks with images taken after exposure and after recoating. There are two drawbacks of this monitoring method: First, the sensor signals - the image of the powder bed - give no direct height information. Second, the application of this method needs to be trained and labeled with reference images for several cases. The novel approach presented in this paper uses a laser line scanner attached to the recoating machine. With this new concept, a direct threshold measure can be applied during the recoating process to detect deviations in height level without prior knowledge. The evaluation can be done online during recoating and feedback to the controller to monitor each individual layer. Hence, in case of deviations the location in the printing plane is an inherent measurement and will be used to decide which severity of error is reported. The signal is used to control the process, either by starting the recoating process again or stopping the printing process. With this approach, the sources of error for each layer can be evaluated with deep information to evaluate the cause of the error. This allows a reduction of failure in the future, which saves material costs, reduces running time of the machine life cycle phase in serial production and results in less rework for manufactured parts. Also a shorter throughput time per print job results, which means that the employee can spent more time to other print jobs and making efficient use of the employee’s work force. In summary, this novel approach will not only reduce material costs but also operating costs and thus optimize the entire life cycle cost structure. The paper presents a first feasibility and application of the described approach for test workpieces in comparison to conventional monitoring systems on an EOS M290 machine.

Virtual reality environment for industrial robot control and path design

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

Simulation of utilization for LPBF manufacturing systems

Due to resolving major technological challenges Additive Manufacturing (AM) is on the brink of industrialization. In order to operate capital-intensive AM equipment in an economically viable manner, service providers must configure their production environment in a way which enables high capacity utilization and short throughput times while minimizing work in process. The interrelation of those three mentioned production-related key performance indicators, also known as the scheduling dilemma, must be addressed with due consideration of the technology’s characteristics. Within the framework of this paper the authors describe the impact of a service provider’s facility configuration regarding machine pool, operator availability and distribution of work content on the production system’s utilization. The evaluations rely on a simulation model developed in Matlab®, which allows for modification and execution of production schedules within AM facilities of different configurations. The validation of the proposed model is based on empirical data gathered on the shopfloor of GKN Additive, a global AM service provider.

Traditional versus fast fashion supply chains in the apparel industry: an agent-based simulation approach

In the past, most companies in the European apparel industry focused on minimizing manufacturing costs in the design of supply chains in conjunction with long-distance shipping from production sites in the Far East and relatively long production cycles. Today, for some market segments, the speed of production cycles is more important than the cost because short throughput time allows the flexibility to adjust to rapidly changing fashion trends in these market segments. Accordingly, choosing the most beneficial supply chain strategy has become an established research topic. However, apparel markets are complex systems. Therefore, attempts to reduce the underlying complexity in order to model these markets have limited existing research to the consideration of only selected aspects of markets (e.g., considering only homogeneous buyers, a single period, a single product, or a single manufacturer in the absence of competition) rather than taking a more comprehensive view. These limitations can be overcome by applying an agent-based simulation approach—an approach that can account for a wider range of factors, including several competing manufacturers utilizing different supply chain strategies, individual consumer preferences and behavior, word-of-mouth communication, normative social influence, and first-hand experience, as well as advertising. In this paper, the capability potential of such agent-based market simulation is demonstrated by investigating two supply chain strategies (fast fashion vs. traditional fashion) with varying product and communication strategies (product attributes and advertising) in several market scenarios.

External information sourcing and lead-time advantage in product innovation

PurposeHaving a short throughput time for innovation projects, i.e. lead-time, can put firms in an advantageous position. The time that lapses between a project’s start and its completion, is influenced not only by the firm's internal capabilities but also by how the firm connects to external knowledge. This paper assesses the relation between knowledge sourcing and lead-time advantage.Design/methodology/approachThis paper empirically tests the relation between external knowledge sourcing and lead-time advantage based on firm level Community Innovation Survey (CIS) data.FindingsI find that breadth and depth of the external knowledge sourcing are positively relating to lead-time advantage, albeit with diminishing returns. Investment into absorptive capacity, i.e. internal R&amp;D, mitigates the diminishing of returns. Firms directing their external knowledge sourcing strategy toward consumers, suppliers and science are better able to capitalize on their innovations through lead-time advantages and firms also benefit from the special case of collaboration for product development.Originality/valueThe conceptual novelty of this research largely consists in empirically bringing together for the first time conceptualizations of external knowledge sourcing and the strategic use of lead-time. Given the prevalence of both concepts in the modern and fast changing economy, investigating this link is of great importance.

The Quality Amplification Challenge

In dynamic production environments, positive business outcomes often require pursuing high quality, shorter throughput time, and low cost simultaneously. This research tries to track the timing effect of having undetected defects continue to progress through the supply chain. The purpose is to demonstrate the influence of throughput time on quality variance amplification and the effect of quality loss on manufacturing performance. A time series model is developed, and numerical analyses are conducted to understand how various parameters affect the quality variance fluctuation and quality loss amplification phenomena. The results show that the variance in quality increases as materials move down a supply chain, away from a supplier. In addition, the quality loss experienced by a manufacturer is greater than that faced by a supplier. Finally, both quality variability and quality loss amplification phenomena are larger when throughput time is longer.

Applicability of the melanger for chocolate refining and Stephan mixer for conching as small-scale alternative chocolate production techniques

Conventional dark chocolate production methods that are applied in the industry consist of several steps, which require equipment with big investment costs. There are however few cost-effective alternatives suggested for small-scale production. Meanwhile, knowledge on these alternative equipment/techniques are insufficient to promote miniature production of high quality chocolates, either for research purposes in an industrial context, or for producers in developing countries, where the cost of investing in conventional equipment seems to be an impediment. The aim of this study was two-fold; first, to assess the feasibility of utilizing the ECGC-12SLTA CocoaTown melanger as an alternative to the conventional 3-roll refiner at different settings and fat content. Thereafter, one optimal setting was selected for each equipment for further investigation on the impact of the refining on some quality attributes of the final dark chocolate (70% cocoa). Secondly, the Stephan mixer; being used to mimick a conching-like process, was assessed with respect to two processing factors; the dry conching temperature (60 °C, 80 °C) and the duration of vacuum pump connection (0, 30, 60 min). The latter was to facilitate adequate moisture removal. The melanger proved to be a suitable alternative to the 3-roll refiner, provided that refining was carried out at moderate/high (ca. 40%) fat content, as is often the case for “high-percentage-cocoa” chocolates. Refining for 180 min with the mini drum at 40% resulted in D (v,0.9) significantly (p < 0.05) lower than when the 3-roll refiner was used. Nonetheless, a comparative advantage of the latter would be its short throughput time (5–10 min). Due to a resultant linear speed gradient of the chocolate mass due to the cylindrical roller stones, a more efficient refining was achieved with the mini drum than with the big drum. More so, refining in excess fat (40%) may have contributed to a more efficient coating of the newly created hydrophilic sugar surfaces, thus, limiting the possibility for moisture-induced agglomeration as may have been the case for the recipe with 27% fat. In spite of trivial difference in moisture content, chocolates manufactured following melanger and 3-roll refining showed significant (p < 0.05) differences in terms of particle size, flow parameters and color. For chocolates that were conched with the Stephan mixer, the vacuum duration had a significant (p < 0.05) impact on moisture content and D (v,0.9). Also, an impact of all factors and their interaction on the Casson yield values of the chocolates was observed. However, these factors proved to be less important in dictating the final viscosities of the chocolates. Among others, it is suggested that the influence of the high fat content of the chocolates may have played a more important role. Although all chocolates exhibited less thixotropic behavior, a direct proportional relationship between the particle surface area and thixotropy was observed. Finally, the interaction effect of both factors also significantly (p < 0.05) influenced the color of the chocolates.

Analysis of critical machine reliability in manufacturing cells

Purpose: In an increasingly competitive business environment, machine reliability problem merits special attention in operations of manufacturing cells. This is mainly due to flow line nature of the cellular layout, interdependency of downstream and upstream of machines related to each other. This study investigates the effect of critical machine reliability improvement on production capacity and throughput time in manufacturing cells. Design/methodology/approach: A discrete-event simulation model was developed to investigate the effectiveness of a reliability plan focusing on the most critical production machines in improving the performance level as an alternative to increasing the reliability of all machines. Four machine criticality policies are examined in the simulation experiments.Findings: The results of this experimental study indicated that an improvement of reliability of a limited number of machines leads to an increase in overall production capacity and speed in cellular manufacturing operations. A reliability plan, that focuses on a set of critical machines, potentially offers a more economical alternative to increasing the reliability of all machines in such facility.Research limitations/implications: The results demonstrate that to achieve higher production capacity and shorter throughput times, managers should consider directing more resources to increase the reliability of critical machines, particularly, those with shorter mean time to failure and higher utilization.Originality/value: The designed simulation model is unique in representing the dynamics of a real world manufacturing cell environment by encoding operational functions such as machine failure, maintenance resource allocation, material flow, job sequencing and scheduling. A new machine availability metric is defined as well.

Databased learning of influencing factors in order specific transition times

Abstract Manufacturing companies are faced with increasing customized product individualization in the last decade. To flexibly adjust manufacturing systems to customized orders, producing factories are challenged to achieve high adherence to delivery dates (ADD) and short throughput times (TPT). TPT mainly consists of non-value-adding transition times (TT), which make up to 95% of TPT in production. In factories, the calculation of TT is mostly made without considering all situational shopfloor conditions and influencing factors. Results are increasing deviations between predicted and real TT (respectively TPT) and thus decreasing ADD. This paper presents a methodology for databased identifying influencing factors in order specific TT. Scientifically, the methodology roots on the Cross-Industry Standard Process for Data Mining (CRISP-DM) and includes filter and wrapper as feature selection methods for data mining (DM). The methodology considers factory specific characteristics, identifies relevant and non-redundant features as key factors and continuously integrates factory employees in the learning process.

Approach for a Production Planning and Control System in Value-Adding Networks

The increasing demand for individualised high-quality products at low cost is forcing companies to offer products based on their core competencies in value-adding networks. To reach overall objectives, such as shorter throughput times or less inventory throughout the network, an intense transfer of progress-relevant information among the network partners is required. This publication presents an approach for a network-wide production planning and control (PPC) system focusing on technical, organisational and monetary dimensions. The proposed approach comprises the modelling of the value-adding network, the development of both a system architecture and an incentive scheme, as well as a hierarchical optimisation.

Effect of High Porosity on Bending Fatigue Properties of 3D Printed AISI 316L Steel

Selective laser melting (SLM) is an effective way to produce optimized metallic parts in relatively short through-put times for various applications. The microstructure of SLM-manufactured metals is affected by the melting parameters applied, namely the total heat-input during SLM. The SLM processing can also introduce defects, such as pores and residual stresses in the part, resulting in impaired mechanical performance. Especially under dynamic loading, pores and microstructural defects can lead to premature cracking. In this study, the effects of melting parameters and the surface quality on the bending fatigue strength of SLM-manufactured AISI 316L austenitic stainless steel are demonstrated. Two sets of specimens were manufactured using two combinations of laser power and scan speed simulating a low and a high heat input. The specimens were heat-treated in a furnace at 600 °C for 120 min prior testing to relief the residual stresses. The surfaces were either as-built or electropolished conditions. The porosity existing in the specimens was estimated from the surface views. It was found that although the higher strength of the low energy density specimens increased the fatigue limit, the surface finish did not have any effect on it due to a high amount of porosity at sub-surface layers masking the effect of surface polishing.

Schwingungsdämpfung bei Industrierobotern

The wish for shorter through-put times in the industrial production is connected with higher requirements on the dynamic of industrial robots. These are susceptible to vibrations due to the combination of serial kinematics, flexible gears and the drive-sided position control of the axes. In order to counteract this circumstance, an approach to reduce vibrations via semi-active damping is presented in this article. The potential of the method is demonstrated by means of a forward dynamic simulation.

Schwingungsdämpfung bei Industrierobotern

The wish for shorter through-put times in the industrial production is connected with higher requirements on the dynamic of industrial robots. These are susceptible to vibrations due to the combination of serial kinematics, flexible gears and the drive-sided position control of the axes. In order to counteract this circumstance, an approach to reduce vibrations via semi-active damping is presented in this article. The potential of the method is demonstrated by means of a forward dynamic simulation.

Model-based Analysis of Reassembly Processes within the Regeneration of Complex Capital Goods

In regenerating complex capital goods two of the key criteria for success on the market include keeping downtimes to a minimum in order to realize short throughput times and maintaining a high degree of schedule reliability. When unable to comply with the market's demands on their logistical performance, companies that provide regeneration services are faced with significant financial penalties and costs for delays as well as the threat of customers switching to competitors. In addition, regeneration processes must be economically effective. Efficiently designing and planning the entire regeneration process is therefore indispensable.As a core element, the reassembly at the end of the process chain plays a key role. Since the various material flows merge together here, the logistic quality of the supply processes is particularly visible at this point. Furthermore, reassembly is generally the last value-adding process within the regeneration supply chain. Up until now, descriptive and analytical approaches consider the various supply processes independently of one another and ignore to some degree existing statistical dependencies between these processes. These dependencies however, are frequently found in the industry and have to be taken into consideration when planning tasks and evaluating design measures. This paper will thus introduce the different existing approaches for describing and analyzing reassembly processes and compare them using a case study.

Quantitative analysis of estradiol and six other steroid hormones in human saliva using a high throughput liquid chromatography–tandem mass spectrometry assay

The aim of the current research was to develop a fast and sensitive analytical strategy that allows for the simultaneous measurement of estradiol and other steroid hormones in human saliva. For this purpose, we established an assay using high performance liquid chromatography–tandem mass spectrometry (LC–MS/MS) with Atmospheric Pressure Chemical Ionization (APCI) coupled with on-line solid phase extraction (SPE). The protocol was designed for the simultaneous identification of estradiol, cortisol, cortisone, testosterone, progesterone, corticosterone and dehydroepiandrosterone (DHEA) from samples of 100µL saliva. After protein precipitation, the sample was injected into the LC–MS/MS system for direct measurement. The protocol involved minimal sample preparation and could be run with throughput times of 5.20min.Results indicated linearity of the method for all steroid hormones over ranges of 0.001–10ng/mL (0.01–20ng/mL for DHEA) with linear correlation coefficients of r=0.999 for each steroid. Intra- and inter-assay coefficients of variance were between 4.3% and 10.8%. The lower limits of quantification (LOQ) were below (or equal to) 5pg/mL for all steroids, except for DHEA for which the LOQ was 10pg/mL. A re-analysis of 16 saliva samples that had produced unusual estradiol values when quantified by immunoassay showed normal, endogenous concentrations for all samples when measured by the current method.In conclusion, we describe an LC–MS/MS method which can be routinely employed in physiological and psychological research laboratories allowing high analytical specificity and sensitivity despite minimal sample processing and short throughput times.

Short-term Cyber-physical Production Management

For most manufacturing companies a high adherence to delivery dates is their main logistic target. In consideration of the fact that for example material and information flows in production plants are getting more intersected and networked than ever before and customer demand tailored products in short throughput times, keeping an overview as well as responding properly becomes a huge challenge for the production manager. In the paper the new approach of cyber-physical short-term assistance of the production manager will be described. Its goal is to support the production controller by providing prioritized short-term actions through new sensor technologies, big data processing and simulation. The paper will outline how the roadmap to short-term cyber-physical production management is developed and what the real benefit for the production manager will be. With the help of intelligent visualization the application will display the effects of a performed action therefore be an optimal basis for decision for the production manager.

Integrated and objective-oriented statistical process control

Global competition and increased environmental concern have emphasized the significance of process quality for an economic success. Statistical Process Control (SPC) is considered as one of the major tools for better quality. However, there are many opinions about the nature, the role and the results of SPC in industry. If SPC is understood and implemented correctly, then it should not only lead to "a reduction of waste, shorter throughput times and greater reliability of supply, but also in a better understanding of the processes and their variation" as Does, Roes and Trip formulated it. SPC should ultimately lead to "an operational management of the continuous improvement of processes." The aim of an industrial production process is to make profit, thus quality should be measured by process profitability. From a more operational point of view highest quality, i.e. highest profitability, is reached by producing with high conformance to an appropriately selected target value, and quality improvement means further reduction of variation around the target value. Thus, understanding the inherent variation represents the key for controlling "profitability" and for being able to implement a system of continuous "quality improvement". The inherent variations reflect the complex relations between everything concerning the production process and results in uncertainty about the future development. Exactly at this point stochastics, the science of uncertainty, enters the stage. For controlling profitability the relations and the resulting variations have to be taken appropriately into account by an integrated and objective-oriented stochastic approach.

New molecular virus detection methods and their clinical value in lower respiratory tract infections in children

SummaryDuring the past decade, several new respiratory viruses and their subgroups have been discovered. All these new viruses, as well as previously known respiratory viruses, can be detected by sensitive PCR methods, which have become popular in the diagnostic workup of respiratory viral infections. Currently, respiratory viruses can be detected in up to 95% of children with lower respiratory tract illness. On the other hand, virus detection rates in asymptomatic children are also high (up to 68%), as are coinfection rates in symptomatic children (up to 43%) and justified concerns of causality have been raised. Imposing progress has been made in developing multiplex quantitative PCR assays; here, several primer sets are run within a single PCR mixture. These PCR assays give a better understanding of the dominant viral infection, of viral infections that may be incipient and of any waning infections than does a single-target PCR. Multiplex PCR assays are also gaining popularity due to their cost-effectiveness and short throughput time compared to multiple single-target PCRs. Our understanding of the indications of virus PCRs and our ability to interpret the results from a clinical point of view have improved. This paper reviews the progress in PCR assays and discusses their role in the diagnosis of lower respiratory tract infections in children.