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In smart manufacturing, machines are interconnected through cyber physical system (CPS) to achieve efficient manufacturing production. Manufacturing efficiency of precision magnetic scale has surfaced as an inevitable challenge. The manufacturing of precision magnetic scale requires precise flatness throughout production and handling processes. In the current technological shortcomings in magnetic scale manufacturing, any flatness defects in the scale would substantially influence its position sensing accuracy. Thus, the goal of this research is to develop and examine a hybrid mechanics model to ensure the scale’s flatness in manufacturing. This model is validated that accurate roller setting can be obtained prior to machine operation, which can significantly improve manufacturing efficiency. In this work, the proposed hybrid mechanics model is performed, validated, and compared to experimental and factory recommended results. The results have demonstrated its capability in predicting optimal leveling roller settings under given conditions, suggesting the possibility of smart manufacturing for magnetic scales.

The manufacturing efficiency resulting from production design by a reduced program is considered. In a reduced program, the production design is based on a small number of representative parts, rather than all of the parts within the specified program. A method is recommended for dividing the parts corresponding to the specified program into groups and selecting a representative part for each group. The representative part is best chosen as an aggregate part reflecting the maximum characteristics and constraints relevant to all the parts in the group.

Over the past few decades, optical waveguides have been increasingly used in wearable/implantable devices for on-body sensing. However, conventional optical waveguides are stiff, rigid, and brittle. A mismatch between conventional optical waveguides and complex biointerfaces makes wearable/implantable devices uncomfortable to wear and potentially unsafe. Soft and stretchable polymer optical waveguides not only inherit many advantages of conventional optical waveguides (e.g., immunity to electromagnetic interference and without electrical hazards) but also provide a new perspective for solving the mismatch between conventional optical waveguides and complex biointerfaces, which is essential for the development of light-based wearable/implantable sensors. In this review, polymer optical waveguides' unique properties, including flexibility, biocompatibility and biodegradability, porosity, and stimulus responsiveness, and their applications in the wearable/implantable field in recent years are summarized. Then, we briefly discuss the current challenges of high optical loss, unstable signal transmission, low manufacturing efficiency, and difficulty in deployment during implantation of flexible polymer optical waveguides, and propose some possible solutions to these problems.

Just-in-sequence supply solutions are highly searched problems of the scheduling the manufacturing and logistics resources. The cost reduction, efficiency and capacity utilization are based on the controlled and designed parameters of the participant supply processes and services. The optimization of the supply process is unavoidable in the development processes of the supply chain' inventory activities along the logistic operations and other services. The aim of this article is to measure the efficiency of the supply chain's inventory activities in manufacturing technology processes. Based on the results of the application of our ABC-XYZ model approach to defines the importance of product values in the inventory management systems. Based on just-in-sequence strategy, the case study and computational results validate the matrix model and evaluates its efforts to renewing the efficiency of manufacturing and delivery processes in inventory strategies.

Fiber composite components play an important role in the turnaround in energy policy as well as in stopping global warming. Therefore, it is essential to improve the manufacturing efficiency of these components. RFID technology is spreading to digitize and organize processes in production and logistics more efficiently. Since cure monitoring is a crucial factor in the manufacturing of composite components, the question arises whether the RFID technology is applicable for cure monitoring. This paper presents two methods of how an into glass fiber-reinforced plastics integrated RFID transponder could monitor the curing. Following the assumption that the change in permittivity of the glass fiber-reinforced plastic during curing influence the RFID signal, experiments in a measuring chamber (low-interference environment) were conducted. It was investigated whether the optimal response frequency of the integrated RFID transponder changes and whether the received signal strength indicator (RSSI) changes at a specific frequency during curing. As a reference method, the dielectric analysis as a well-known method for cure monitoring was used and compared with the RFID measurements. The results indicate that the optimal response frequency remains constant but the RSSI increases and possess a very high linear correlation with the measurement of the dielectric analysis in a low-interference environment. Consequently, the RFID technology is applicable to monitor the curing of glass fiber-reinforced plastics by measuring the RSSI in a low-interference environment.

While continuous manufacturing (CM) of pharmaceutical solid-based drug products has been shown to be advantageous for improving the product quality and process efficiency in alignment with FDA’s support of the quality-by-design paradigm (Lee, 2015; Ierapetritou et al., 2016; Plumb, 2005; Schaber, 2011), it is critical to enable full utilization of CM technology for robust production and commercialization (Schaber, 2011; Byrn, 2015 ). To do so, an important prerequisite is to obtain a detailed understanding of overall process characteristics to develop cost-effective and accurate predictive models for unit operations and process flowsheets. These models are utilized to predict product quality and maintain desired manufacturing efficiency (Ierapetritou et al., 2016). Residence time distribution (RTD) has been a widely used tool to characterize the extent of mixing in pharmaceutical unit operations ( Vanhoorne, 2020 , Rogers and Ierapetritou, 2015 , Tezyk et al., 2015 ) and manufacturing lines and develop computationally cheap predictive models. These models developed using RTD have been demonstrated to be crucial for various flowsheet applications ( Kruisz, 2017 , Martinetz, 2018 , Tian, 2021 ). Though extensively used in the literature (Gao et al., 2012), the implementation, execution, evaluation, and assessment of RTD studies has not been standardized by regulatory agencies and can thus lead to ambiguity regarding their accurate implementation. To address this issue and subsequently prevent unforeseen errors in RTD implementation, the presented article aims to aid in developing standardized guidelines through a detailed review and critical discussion of RTD studies in the pharmaceutical manufacturing literature. The review article is divided into two main sections – 1) determination of RTD including different steps for RTD evaluation including experimental approach, data acquisition and pre-treatment, RTD modeling, and RTD metrics and, 2) applications of RTD for solid dose manufacturing. Critical considerations, pertaining to the limitations of RTDs for solid dose manufacturing, are also examined along with a perspective discussion of future avenues of improvement.

In the wake of COVID-19, significant influence on the manufacturing industries has been observed in the past year due to the restrictions of in-person communications and interactions. As a consequence, manufacturing efficiency has reduced remarkably all over the world. Despite the great harm to the industrial operations under the pandemic, the opportunities for remote collaborative manufacturing system also arise. Effective and efficient remote manufacturing systems for the real industries have been highly demanded. Through the integration of industrial internet and digital twin systems, the remote manufacturing system can be largely facilitated. This paper proposes a general framework for the remote manufacturing system during the COVID-19 era. The concept of the intelligent collaborative remote manufacturing system is firstly reviewed, as well as discussions of the current pandemic situation and its influence on the industries. The current commercial platforms of the systems are also presented. A case study on the lighthouse factories at the Foxconn Technology Group is finally presented for understanding the implementation of the proposed strategy. The effectiveness of the framework has been validated in the real industrial scenarios, and great economic and operational benefits have been obtained. The proposed framework offers a promising solution for the remote manufacturing system under the current pandemic.

With a worldwide trend towards the efficient use of renewable energies and the rapid expansion of the electric vehicle market, the importance of rechargeable battery technologies, particularly lithium-ion batteries, has steadily increased. In the past few years, a major breakthrough in electrolyte materials was achieved by simply increasing the salt concentration in suitable salt–solvent combinations, offering technical superiority in numerous figures of merit over alternative materials. This long-awaited, extremely simple yet effective strategy can overcome most of the remaining hurdles limiting the present lithium-ion batteries without sacrificing manufacturing efficiency, and hence its impact is now widely felt in the scientific community, with serious potential for industrial development. This Review aims to provide timely and objective information that will be valuable for designing better realistic batteries, including a multi-angle analysis of their advantages and disadvantages together with future perspectives. Emphasis is placed on the pathways to address the remaining technical and scientific issues rather than re-highlighting the many technical advantages. New electrolyte materials can offer breakthroughs in the development of next-generation batteries. Here Atsuo Yamada and colleagues review the progress made and the road ahead for salt-concentrated electrolytes, an emerging and promising electrolyte candidate.

Manufacturing efficiency improvement can be achieved by different means, e.g., effective load of equipment, reduced manufacturing time, production cost decrease and Lean manufacturing. The paper reviews the mentioned improvements and focuses on production scheduling aimed to reduce the overall production time. The sequence of simultaneous launch for production is often not considered, but it affects the overall production time. The elaborated production sequence eliminates waste waiting time, reduces production cost and manufacturing time, and thus improves the manufacturing efficiency. The authors propose to apply a software agent, which is engaged with production scheduling and production process improvement that includes the following tasks: effective workload of equipment, production lead-time decrease, organization of continuous product flow on production department. The agent uses such priority levels, as order deadline and class affiliation of ABC analysis in its production scheduling. The paper presents a case study on elaborated production scheduling for manufacturing efficiency improvement.

Based on the study of two-dimensional irregular parts layout algorithm, a layout system suitable for semi-finished parts of automobile welding jig was designed and developed with visual studio as the development platform, using C++ language and CAA technology. This paper puts forward the system framework, the functions of the sub-modules and the interactive interface in detail. The system can effectively improve Jig manufacturing efficiency.

With the increasing application of robots in manufacturing industry, the problem of collaboration between human and robot and the efficiency of collaboration between multiple robots becomes more and more prominent in complex production scenes. An optimization method of operators and robots using depth vision sensors and intelligence trajectory planning algorithm is proposed in human-robot system. The research is expected to improve the manufacturing efficiency by reducing the waste of time with better time-consuming stability performance to the maximum extent and guarantee the safety of operators.

This paper proposes an additive nanomanufacturing approach to fabricate a personalized lab-on-a-chip fluorescent peptide nanoparticles (f-PNPs) array for simultaneous multi-biomarker detection that can be used in Alzheimer’s disease (AD) diagnosis. We will discuss optimization techniques for the additive nanomanufacturing process in terms of reliability, yield and manufacturing efficiency. One contribution of this paper lies in utilization of additive nanomanufacturing techniques to fabricate a patient-specific customize-designed lab-on-a-chip device for personalized AD diagnosis, which remains a major challenge for biomedical engineering. Through the integrated bio-design and bio-manufacturing process, doctor’s check-up and computer-aided customized design are integrated into the lab-on-a-chip array for patient-specific AD diagnosis. In addition, f-PNPs with targeting moieties for personalized AD biomarkers will be self-assembled onto the customized lab-on-a-chip through the additive nanomanufacturing process, which has not been done before. Another contribution of this research is the personalized lab-on-a-chip f-PNPs array for AD diagnosis utilizing limited human blood. Blood-based AD assessment has been described as “the holy grail” of early AD detection. This research created the computer-aided design, fabrication through additive nanomanufacturing, and validation of the f-PNPs array for AD diagnosis. This is a highly interdisciplinary research contributing to nanotechnology, biomaterials, and biomedical engineering for neurodegenerative disease. The conceptual work is preliminary with intent to introduce novel techniques to the application. Large-scale manufacturing based on the proposed framework requires extensive validation and optimization.

Complex engineering systems present a wealth of uncertainties concerning aspects ranging from performance measurements to maintainability and through-life characteristics. A quantifiable understanding of these uncertainties is vital to system optimisation and plays a key role in decision-making processes for manufacturing organisations worldwide; impacting profit, product availability and manufacturing efficiency. The aim of this paper is to examine challenges and complications that arise when quantifying uncertainties in complex engineering systems that rely on expert opinion. A thermographic inspection system is utilised as a use case. Contractor-client and supervisor-maintainer relationships are examined. Key challenges highlighted involve accurate depiction of error margins and corresponding uncertainties of components where data is only heuristically obtainable, as well as the influence of environmental conditions and skill of the maintainer.

Several parameters and variables affect the production cost and the company competitiveness. The manufacturing part cost is directly influenced by factors related to tools, workpiece materials, equipment, personnel, automation, etc. These factors also have a significant influence on the manufacturing efficiency and performance. The presented model determines the production performance with respect to the actual cost for each factor involved. The CPR relationship sets the cost of a given factor in relation to its production performance. CPR may be used to evaluate or find optimal technical solutions with respect to individual factors.

In recent years, the development of bispecific antibody (bsAb) has become a major trend in the biopharmaceutical industry. By simultaneously engaging 2 molcular targets, bsAbs show unique mechanisms of action that could lead to clinical benefits unattainable by conventional monoclonal antibodies. Various bsAb generation formats have been described, and several are being investigated in clinical development. However, some bsAb constructs have proven to be problematic due to their unfavorable physicochemical and pharmacokinetic properties, as well as poor manufacturing efficiencies. We describe here a new bispecific design, Fabs-in-tandem immunoglobulin (FIT-Ig), in which 2 antigen-binding fragments are fused directly in a crisscross orientation without any mutations or use of peptide linkers. This unique design provides a symmetric IgG-like bispecific molecule with correct association of 2 sets of VH/VL pairs. We show that FIT-Ig molecules exhibit favorable drug-like properties, in vitro and in vivo functions, as well as manufacturing efficiency for commercial development.

Industry 4.0 aims to ensure the future competitiveness of the manufacturing industry by providing Companies with the ability to react to rapid product changes and disturbances, efficiently and reliably, through re-configurability. In this paper, we explore the value creation process within Industry 4.0, with special emphasis on its relationship with mass customization and the sustainability issue. Based on the identified research gaps and opportunities derived from a literature review of relevant concepts, we propose the development of the Customer-Product-Process-Resource (CPPR) 4.0, a comprehensive framework that puts the value proposition-creation-capture cycle proper of an Industry 4.0 environment, in the context of a manufacturing organization&rsquo, s customer-product-process-resources views. The usefulness of the proposed framework is exemplified by using it to derive system dynamics model of the mass customization paradigm. A discussion of the managerial implications of the obtained results for both the sustainability and the case of Small-to-Medium Enterprises (SMEs) is offered at the end of the paper.

Chatter vibration in turning and milling operations is one of the most critical problems that causes low workpiece quality and manufacturing efficiency. Therefore, the determination of stable cutting depths is crucial for these operations. Several vibrational characteristics [natural frequency (ωn), stiffness coefficient (k), and damping coefficient (s)] affect stable cutting depths. The vibration characteristics of these operations show randomness for every setup condition. For this reason, the randomness of the vibration characteristics should be modeled. In this study, a probabilistic approach and regression model are combined for turning operation. Also, a probabilistic approach and analytical model are integrated for milling operation. The purpose of these models is to establish confidence intervals for stability diagrams. As a result, the operators can work in a secure region during the operations.

The manufacturing error is a very important factor that influences the quality of workpieces, which will obviously reduce the manufacturing accuracy of the workpieces. Excessive manufacturing errors may even cause the workpieces to be scrapped and seriously affect the manufacturing efficiency and benefits.

The development of mechanical design and manufacturing and automation engineering is not only an effective support to realize the goal of China’s industrial power and improve the gross national product, but also can improve the people’s living standards and provide the production basis for the current social development. The development of artificial intelligence can promote the degree of mechanical automation. In order to better distinguish the influence of artificial intelligence technology on mechanical design and manufacturing, we selected 30 students from mechanical college and equally divided them into two groups. Group A students used traditional mechanical design and manufacturing method to carry out experiments, while group B used artificial intelligence on this basis be able to design and manufacture machinery. With the development of experiment time and progress, we found that there was a big difference between the two groups of students. The experimental results show that when the mechanical manufacturing reaches 30%, the waste rate of group A is 0.4%, and the waste rate of group B is 0.2%, saving 0.2%. When the manufacturing progress reaches 50% and 70%, the waste of resources in group B is 0.3% less than that in group A 5% in group A and 1% in group B, saving 0.5%. Thus, the use of artificial intelligence technology can not only improve the manufacturing efficiency of mechanical manufacturers, but also reduce the waste of resources, which has a profound impact on the rapid development of mechanical design and manufacturing.

Emulsion quality evaluation using machine vision techniques depends on the efficiency of the image segmentation algorithms. Two different machine vision techniques are investigated to determine their competency in detecting droplets from in-process microscopic images of a cream emulsion. Histogram-based segmentation shows promising potential compared to edge and symmetry detection. A statistical study of the droplet characteristics was conducted. The results demonstrate that the histogram-based approach is more proficient in the progressive analysis of droplet evolution during emulsification. A real-time integration of the technique is proposed, as a soft sensor, to predict the optimum process time and to increase manufacturing efficiency in chemical industries.

In order to improve the design and manufacturing efficiency of propellers, a dedicated CAD/CAM system for the whirling process of propeller blades is proposed. The main functions of the proposed system include parametric modeling of propeller blades and tool path solution for the whirling process of the blade. The former takes advantage of Creo to construct propeller’s 3D model by means of parametric modeling of the original design data; the latter is aimed to help manufacture the propeller blades using whirling process which is primarily used in producing threaded parts.

Bispecific antibody (BsAb) has become an important trend in developing next generation biologics therapies. By simultaneously engaging two molecular targets, BsAbs show distinctive mechanism of actions that could lead to clinical benefits unattainable by conventional monoclonal antibodies (mAbs). Successful launch provided clinical validation and encourage more BsAb development in the pipeline of pharmaceutical companies. Fabs-in-tandem immunoglobulin (FIT-Ig™) format was initially described in 2017. This unique design provides a symmetrical and tetravalent IgG-like bispecific molecule with correct association of 2 sets of VH/VL pairs, where two Fabs are fused directly in a crisscross orientation without any mutations or use of peptide linkers. FIT-Ig can be readily made from 2 existing monoclonal antibodies by basic molecular biology techniques with high expression level in mammalian cells, and easily purified to homogeneity using standard approaches without extensive optimization. FIT-Ig molecules exhibit favorable drug-like properties, in vitro and in vivo functions, as well as manufacturing efficiency for commercial development. Here, we provide an example of construction and preliminary characterization of a FIT-Ig molecule with discussions on optimization and general utility.

The idle and delay time in an industry is categorized as production waste that will cause problems such as production quantity below the target. In addition, the waste also leads to cost losses and eliminate opportunities for the industry to gain profit. The need of waste analysis to optimize the costs incurred due to the idle and delay time. Lean manufacturing approach can be used to minimize that production waste. Value stream mapping (VSM) is one of lean tools that can be used to identify all production activity for an industry. This study is conducted in a steel processing industry. The result shows that the dominant production waste is delay time. There are seven factors causing the main production waste, i.e. operation, mechanic, adjustment, electric, computer, instrument, and utility. These factors are the cause of production waste and production activities that do not add value to product. A maintenance improvement program is developed to reduce the production waste. Manufacturing cycle efficiency in actual condition is 68,08% while efficiency value in the future condition is 71,3% so from proposed improvement plan that can increase manufacturing cycle efficiency equal to 3,75%.

With a worldwide trend towards the efficient use of renewable energies and the rapid expansion of the electric vehicle market, the importance of rechargeable battery technologies, particularly lithium ion batteries, has steadily increased. In the past few years, a major breakthrough in electrolyte materials was achieved by simply increasing the salt concentration in suitable salt/solvent combinations, offering technical superiority in numerous figures of merit over alternative materials. This long-awaited extremely simple yet effective strategy can overcome most of the remaining hurdles limiting the present lithium ion batteries without sacrificing manufacturing efficiency, and hence, its impact is now widely felt in the scientific community, withserious potential for industrial development. I will try to provide timely and objective information that will be valuable for designing better realistic batteries, including a multi-angle analysis of their advantages and disadvantages together with future perspectives. Emphasis is placed on the pathways to address the remaining technical and scientific issues rather than re-highlighting the many technical advantages.

PurposeThe purpose of this paper is to examine the impact of radio frequency identification (RFID) technology utilization in manufacturing firms on manufacturing efficiency and effectiveness.Design/methodology/approachUsing systems theory as a basis, a RFID utilization and outcome(s) performance model was developed from the literature. Data from a sample of 155 manufacturers were collected and the model was assessed using a structural equation methodology.FindingsFindings indicate that utilization of RFID technology leads to improved manufacturing efficiency and manufacturing effectiveness. Improvements in efficiency lead directly to improved organizational performance, and improvements in effectiveness lead directly to improved supply chain performance.Research limitations/implicationsData were collected during the growth stage of RFID technology adoption and were only collected from firms in the manufacturing sector. Results should be interpreted with these limitations in mind.Practical implicationsThe implementation of RFID technology can result in improved manufacturing efficiency and effectiveness. Practitioners considering adoption of the technology should fully account for these potential efficiency and effectiveness related benefits when determining the justification for adoption of this technology.Originality/valueThe paper describes one of the first empirically‐based studies investigating the impact of RFID technology implementation on supply chain and organizational performance in manufacturing organizations.

PurposeThe purpose of this paper is to analyse the use of a product‐oriented layout and a work‐cell strategy in order to maximise efficiency. These two categories of layout strategies are discussed separately, and are then used collectively in an analysis of the company. The aim is to understand how improvements on layout design could positively impact the future efficiency of the case study company.Design/methodology/approachA model was developed and measured using 26 weeks of data between the fourth quarter of 2009 and the first quarter of 2010 during layout transformations at the case study company based in upstate New York. The model compared variables such as the distance traveled to retrieve parts, average daily output of engines, labour cost per unit produced, and the amount of time the engine remains in each cell; the aim of which is to increase the efficiency of the facility.FindingsThe findings indicate that there is a strong correlation between the variables improved at both the cell‐structures and the product‐structures of the facility and the overall efficiency of the manufacturing facility itself. The results also show that an overall higher efficiency allows for the facility to handle much larger workloads and also drives down both short‐run and long‐run costs. The outcomes also allow for a suggestive redesign of the facility in order to further maximise efficiency. However, it was found that the amount of time a product remains in each cell on the assembly line does not have an effect on the overall output of diesel engines.Research limitations/implicationsVarious studies have been conducted focusing on the “facility layout problem,” yet thorough analyses of the redesigning of layout in regards to efficiency are not as available. Instead, an understanding of the topic was derived through sources focusing on the specificities of manufacturing layout.Originality/valueThis paper describes layout efficiency through redesigns and layout using work‐cells in a product‐oriented environment. This study would be useful to manufacturers having low variability in their product and having the ability to use work‐cell layout within their facility.

The possibility of continuous processing in pharmaceutical tablet manufacturing is hampered by the viscoelastic recovery of tablets post-compaction. Compacted tablets are typically aged before coating to allow complete viscoelastic recovery so as to avoid subsequent coating defects. There has been little attempt to overcome tablet recovery in order to enable continuous processing and improve manufacturing efficiency. However, with the introduction of improved or newly developed types of tablet-coating equipment, there is renewed interest in the coating of tablets in-line. In-line tablet coating is defined as the coating of tablets immediately after compaction. It is a one-step highly integrated system that circumvents the delay in processing time typically given to allow viscoelastic recovery of tablets. This review aims to summarize the requirements of an in-line tablet-coating system. The possibility of carrying out in-line tablet coating in the near future will also be discussed.

The in-depth analysis of cutting procedure is a topic of particular interest in manufacturing efficiency because in large-scale production the effective use of production capacities and the revenue-increasing capacity of production are key conditions of competitiveness. That is why the analysis of time and material removal rate, which are in close relation to production, are important in planning a machining procedure. In the paper three procedures applied in hard cutting are compared on the basis of these parameters and a new parameter, the practical parameter of material removal rate, is introduced. It measures not only the efficiency of cutting but also that of the whole machining process because it includes the values measured by time analysis as well. In the investigations the material removal rate was analyzed, first on the basis of geometrical data of the component. After that different machining procedures (hard machining) were compared for some typical surfaces. The results can give some useful indications about machining procedure selection.

The construction cost for the wafer fab. of a semiconductor manufacturing is about NT$ 50 to 70 billions. Owing to the higher reentrant characteristics of the manufacturing process routing, the Automated Material Handling System (AMHS) and the layouts of the manufacturing fab. will determine the manufacturing efficiency at the earlier planning stage. The current wafer fab. layouts are their basis on the spine layout concepts. The spine layout is to allocate the material handling system at the center (like the spine of human body) of the manufacturing facilities, with the rest of the bays assigned to areas along the spine. This layout can reduce the material handling distance (time) and decrease the collision and vibration of the material handling systems. The benefits of this concept can utilize the modularized function area to form the desired construction for use. A bay configuration arranged along a central spine and served by an AMHS is common for the layout and material handling system in th...

Reducing wastage from the unnecessary cutting of raw material is a key issue in the manufacture of diamonds and gemstones. The accuracy with which stones are graded prior to their being processed through the various manufacturing stages of cutting and finishing is a key determinant of yield and so profit. This presently manual activity requires a skilled craftsman to assess the grade and spot opportunities for upgrading through the judicious cutting away of imperfections in the raw material. There is however a balance to be struck between raising quality and lowering wastage. This paper describes iGem, an artificial intelligence tool that integrates rule-based knowledge representation, fuzzy logic and genetic algorithms to produce a system for automating, and introducing consistency into, the grading of diamonds and gemstones. In this paper we show how iGem derives its knowledge from repeated examples of previously correctly graded stones and can improve its performance by learning from experience. The industrial benefit of iGem extends beyond simply improving grading but also to the introduction of consistency and so greater control into the overall manufacturing process. We believe the approach described has application in other situations where overall yield and manufacturing efficiency depends on trade-off decisions between removal of imperfections and loss of material as well as consistency in quality assessment. A further noteworthy aspect of the iGem project is its development of an objective quality assessment technique out of a hitherto substantially subjective one.

From this early experience, the concepts of manufacturing/industrial 'efficiency' were born with the underlying comparison of 'standard time' to available hours usually calculated from the discipline of 'clocking in'. Whilst the concept of manufacturing efficiency is still a valid one even today, the shortcomings of such an approach are now well recognised particularly in terms of the way such measures can drive behaviours, which are unhelpful to the overall objectives of most modern businesses. Modern measurements are now more directed at providing a balanced set of numbers, which together portray the health of any business in a more rounded way. 'Balanced scorecard' is the shorthand way that such overall approaches to measurement are now referred. The authors give some factors that must be borne in mind when establishing performance measures.

The investigation of the possibility of low-cost SMES is an indispensable theme if that practical use is to be realized. We optimized the system composition by selecting the most suitable charge/discharge rate. We conducted the optimum design on the structure of superconductor and the coil system under special consideration of the material unit price, the total material amount, the manufacturing efficiency, and so on. The pool-cooling double-row solenoid system using NbTi base conductor is the most suitable one as 15kWh-100MW SMES for the system-stabilizing use and 500kWh-100MW SMES for the load-fluctuation-compensating and frequency-controlling use.

An increasingly competitive environment and the changing customers' preference have forced manufacturers to find ways to increase productivity. The cellular manufacturing system has proved to be an alternative for improving manufacturing efficiency and increasing productivity. A major problem in implementing an FMC is how to evaluate its total throughput efficiently. In this paper, we apply a network flow model to select different machines in an FMC. This network flow model can be used in a processing environment with multiple available routings and obtain the maximum total throughput. In addition, two numerical examples are demonstrated to illustrate the use of this model. The results show that the network flow model established in this paper provides a simple and powerful tool when evaluating different machine configurations with limited information available. That is, only the operating routings and operating time are required when using the network flow model.

Inkjet printing of 2D layered materials, such as graphene and MoS2, has attracted great interests for emerging electronics. However, incompatible rheology, low concentration, severe aggregation and toxicity of solvents constitute critical challenges which hamper the manufacturing efficiency and product quality. Here, we introduce a simple and general technology concept (distillation-assisted solvent exchange) to efficiently overcome these challenges. By implementing the concept, we have demonstrated excellent jetting performance, ideal printing patterns and a variety of promising applications for inkjet printing of 2D layered materials. QC 20141205

The dynamic cellular manufacturing system (DCMS) is a well-known strategy that typically improves manufacturing efficiency in dynamic and changing production environment product mix and demand usually change. The literature which relates to DCMS is reviewed. Then an integrated mixed-integer model which comprehensively investigate and analyze cell formation, intercellular and intracellular materials handling, inventory and backorder holding, considering multi-production planning with multi-functional machines where each period has different demands. An numerical example is solved using a genetic algorithm and it presents that proposed model is useful.

To remain competitive, the US chemical industry needs to use all available tools to increase productivity. Computational chemistry can help design new materials and improve manufacturing efficiency. However, it needs to focus on method development at all length and time scales. The article illustrates the challenges and opportunities with two specific examples of industrial problems.

Line balance wall is a simple and easily understood method to measure a production line whether balance or not, and it is widely used in manufacturing enterprises to balance the production line. In this paper, the application of line balance wall and the way of using line balance wall to improve production efficiency have been introduced, and an assembly line of one manufacturing company has been given as an example to further show the improving effect of the application of line balance wall when it is used to improve production process in manufacturing enterprises. The meaning of this research is that introducing an effect method to production site-improvements, and line balance wall will be used more and more widely and increase the manufacturing efficiency.

The design of cellular manufacturing (CM) systems has received considerable attention from both practitioners and academics in the study of automated manufacturing systems. CM, an application of group technology (GT), focuses on grouping parts with similar design and/or process characteristics into part families and forming associated machines into machine cells in order to achieve higher manufacturing efficiency. In this paper, we propose a quadratic programming model for machine cell formation with congestion constraint, which in addition to assigning the machines to the cells, finds the optimal number of machine cells. An efficient algorithm based on graph partitioning is used for solving the problem. Extensive computational tests are conducted to test the performance of the proposed algorithm with respect to several performance measures under various problem parameters.

Machining technology is one of the most important sectors influencing mechanical products' manufacturing quality and manufacturing efficiency directly. The scientific and rational machining technology design is the key to determine mechanical products' cost-performance ratio and whether the design is successful. For decision-making of the design scheme of machining technology is one important and complicated process influenced by many different factors directly, the decision-making methodology of determining the scientific and rational design scheme of machining technology is proposed based on fuzzy logic. The goal of determining the optimum design scheme of machining technology is achieved by application of the methodology of fuzzy comprehensive evaluation. Finally, an example of decision-making of design scheme of machining technology based on the methodology of fuzzy comprehensive evaluation on one certain workpiece is represented for the illustration of the proposed methodology, and the result indicates that the optimum design scheme of machining technology is provided by the methodology of fuzzy comprehensive evaluation.

Verification is key in the assurance of safe food, to confirm that the HACCP system is working effectively. Guidelines on the application of the principles of HACCP suggest that validation activities are used to support the principle of verification. The food and drink industry undertakes extensive validation in the establishment of processes and products and thereafter during production to aid in the continuing assurance of food safety. Validation techniques involve the quantification of data, its analysis and its use to assure product safety. In many sectors the impact of temperature on product safety is often a critical factor that requires validating. Validation has been based on the direct measurement of the destruction of micro-organisms in inoculated samples or systems. An alternative approach has been to gather in-product/process time and temperature data and use these as the basis of the validation approach. The common factor to both is that a model must be applied to interpret either dataset in the context of product safety. Traditional approaches have depended upon the selection of challenge samples that correspond to the “worst case” thought to occur in production. This approach has limitations and although this is often satisfactory in the context of safety, the degree of overprocessing induced can have a serious impact on the commercial performance of the company in terms of product quality and manufacturing efficiency.

For the manufacturing of submicron or deep submicron ULSIs, it is important to completely suppress particles and contamination created on the silicon wafer surface. The time and logistics associated with particle testing on product have driven manufacturing to find fast and effective monitoring techniques that can deliver high manufacturing efficiency at lower cost. Using particle monitoring is an accurate and cost effective method of contamination control in a production environment. In general, the traditional method is using 2 pieces control wafers (top and bottom) in slot position to monitor production environment. In this work, an improvement method was proposed to implement using 6-pieces control wafers replacing the traditional method (2 pieces). The experimental results shown that the improvement method has 7 times sensitive efficiencies than the traditional one.

Production management performance relies on data specified by engineers that are neither an economists nor production planners. Therefore, production planning and control becomes a complex task. This paper presents a method where engineer’s task is not to make decisions but rather to prepare a “road map”. Each user will generate routine that meets his needs at the time of need by using KBMS CAPP. Thereby increase dramatically manufacturing efficiency.

The ex vivo storage of cells at low temperatures for extended periods of time has been one of the most important advances that led to the creation of biobanks and the widespread therapeutic use of cellular products. Most cellular products used today spend a large portion of their product lifecycle at hypothermic temperatures or cryopreserved and stored frozen in freezers. As it is generally understood in the biobanking industry that the length and temperature of pre-cryopreservation storage can influence the post-thaw recovery of cells, biobankers have empirically established thresholds for the “optimal” conditions for the: shipment of raw material to centralized manufacturing sites, cell selection, donor testing and processing. Unfortunately, there is a general lack of appreciation of the impact that pre-cryopreservation processing and storage has on critical cell properties that are crucial to post-thaw recovery of viable cells. This presentation will provide a biologist’s perspective on the impact that cell manufacturing conditions can have on the quality of cellular therapeutics. Emerging data on the hypothermic storage lesion and cryoinjury of red blood cells and hematopoietic progenitor cells will be discussed with a focus on changes to cell metabolism, oxidative injury and membrane remodeling. The impact of the biological changes on the ability for cells to respond to the physical and chemical stresses encountered during cryopreservation will be introduced. Current quality control methods and international regulations will be briefly described. Recent clinical data on the effects of hypothermic storage and cryopreservation on recipient outcomes will be reviewed. While there is a practical / commercial need to optimize the pre-cryopreservation manufacturing efficiency of cellular products, consideration must be given to the impact and dependency that each manufacturing step has on the quality and potency of the final product.

For many companies, the implementation of material requirements planning systems has failed to produce the expected improvements in manufacturing efficiency. This paper shows that MRP failure can occur in the common situation in which MRP is installed in a manufacturing environment that has evolved around manual methods of material control. A system dynamics simulation model is used to interrelate decision functions (policies) of a manufacturing firm. Simulation runs of the model operating with manual methods of material control show six- to seven-year fluctuations in production, ordering, and labor. A modified version of the model, changed only by the introduction of a requirements explosion to represent MRP, shows that MRP can actually cause more severe production fluctuations, resulting in lower average labor productivity and higher manufacturing costs. The major practical implication of the analysis is that the organizational environment that suits MRP (and utilizes its inherent strengths) is different from the environment that is likely to prevail at the time of implementation.

This paper states that the successful business is one that makes the best use of working capital and demonstrates a technique for examining this, principally in a general engineering environment with low batches and a high design engineering content. The technique is used to develop a manufacturing efficiency ratio, and methods of improving this ratio are discussed.

The rapidly expanding usage of composite components in automotive and other mass production industries has focused attention on continuous production techniques as they apply to these engineering materials. It is recognized that where product volume warrants, a continuous processing system from raw material to finished product approaches optimum manufacturing efficiency. In composites, where properties are dependent almost solely on fiber orientation, continuous processing has the additional advantage of providing dependable control of filament orientation and tensioning. The combination of these and other more subtle processing advantages results in product economies not achievable by other processing techniques.

Manufacturing efficiency has too distinct aspects: the procedural aspect that deals with the input-output relations of the manufacturing process and the logistical aspect that deals with the question of what item to manufacture in what quantity and at what time. The latter aspect is part of the overall logistical control that governs the operational planning of every company.