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This paper presents a collection of models of humans involved in complex systems with a focus on control of the system while allowing human participation in decisions for system operation. The existence of a formal model that captures human behaviour in a complex system allows for the efficient development of modelling and control software of man-machine systems. This paper provides a foundation for modelling and software development for complex systems that includes human activities. A modelling formalism, based on the automata theory for human-machine cooperative systems is demonstrated in this paper in consideration with the ecological concept of affordance. [ABSTRACT FROM AUTHOR]

In this paper, we develop an optimal tool replacement model based on the actual tool wear status. In this model, we consider separately the probability distribution of the tool capacity obtained under testing conditions and the tool capacity consumption by the workpieces. Special cases with exponential distribution for tool capacity consumption and in which one tool can process many workpieces are solved. [ABSTRACT FROM AUTHOR]

Expert systems have demonstrated their ability to solve problems of a specific domain and achieve quality performance. The technology has been applied in numerous engineering areas. In this paper, an expert system based AS/RS controller, ECSSIM, is presented. The system plans a control strategy based on the long term system characteristics. However, the system alters the control strategy tactically according to the short term control needs. The system performed very well particularly at high demand levels. It also demonstrated its capability of sensing poor control strategies, and tactically compensate for the strategy selection error. [ABSTRACT FROM AUTHOR]

The on-line control and scheduling of flexible manufacturing systems has been a major interest in the production research area since these systems first appeared. In this paper, a scheduling algorithm is described which employs discrete simulation in combination with straightforward part dispatching rules in a dynamic fashion. The result is that, instead of scheduling being planned ahead of time and then being applied to a rapidly changing system, a dispatching rule is determined for each short period just before the implementation time occurs. In the long run, the algorithm combines various dispatching rules in response to the dynamic status of the system. The algorithm is described in detail. The efficacy of the algorithm is discussed and demonstrated on a prototype system. [ABSTRACT FROM AUTHOR]

Automated process planning (APP) is a critical interface to both design and manufacturing. Several evolving systems have employed artificial intelligence (AI) procedures to capture the basic logic used by a process planner. However, no effort has been directed to systemize the knowledge in the field of process planning. In this paper process planning knowledge extraction and formalization will be discussed. A framework for the development of intelligent APP systems capable of learning through user interaction is also presented. [ABSTRACT FROM AUTHOR]

Human interpretation of CA D data is required for generating process plans and NC tape images in existing CAD/CAM systems. In order to eliminate this human interpretation, an algorithm for automatically identifying all machined surfaces on symmetric rotational parts is presented. An implementation procedure of the surface recognition algorithm is described along with examples. The algorithm is suitable for manufacturing applications, such as automated process planning, classification and coding, and NC tape image generation. [ABSTRACT FROM AUTHOR]

CAN-Q is a recursive algorithm for solving a closed-form stochastic model of production systems. This paper presents an investigation of the effect of departures from the assumptions underlying the analytical queueing network model on the performance predicted by CAN-Q. [ABSTRACT FROM AUTHOR]

Two types of heuristic capacity-control policies are evaluated using a simulation model of a materials-requirements-planning production system. The control-policy decisions are based solely on the size of the queue, as measured in standard hours of work, at each work center in the production system. Several classes of product mixes and product structures and several levels of the control parameters of each policy, are investigated. The results indicate that each control policy gives rise to a unique population of weekly labor, work in process and intermediate inventory level. Product structure is identified as a major variable in materials- requirements-planning systems performance. Sensitivity analysis of the cost functions for each policy indicates the conditions under which it will minimize the sum of labor costs, work-in-process holding costs and inventory holding costs. [ABSTRACT FROM AUTHOR]

Presents a generative process planning system approach in computer-aided process planning. Use of a boundary representation from a computer-aided design database; Utilization of the information stored in a process knowledge base to determine manufacturing processes; Geometric modelling of the system.

Although milling is one of the most common chip metal removal processes, little has been done to aid in identifying the optimum operational conditions for milling processes. In this paper, a mathematical model for milling operations is developed and the five primary control variables identified. The model is then decomposed and an efficient optimization procedure developed for control variable identification. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) can significantly reduce the development time for small batch parts or parts with complicated geometries. However, the accuracy of most metal AM processes requires parts to be subjected to secondary processing (typically machining) in order to obtain requisite tolerances. Process plan development for hybrid manufacturing, which is defined for the following as additive manufacturing followed by subtractive multi-axis computer numerical control (CNC) machining, typically takes weeks rather than hours or days. This paper outlines a feature-based advanced hybrid manufacturing process planning system (FAH-PS) that uses feature-specific geometric, tolerance, and material data inputs to generate four-automated process plans based on user-specified feature precedence for hybrid manufacturing. FAH-PS currently has the capability to identify manufacturing processes for critical pockets, flat surfaces, and hole features. Additional plans generated by FAH-PS minimize tool changes, orientation changes, etc., to improve process times. FAH-PS is modular and extensible to allow for additional feature types, materials, tool sizes, and/or optimization strategies to be included in future versions. A case study, using a custom patient-specific bone plate, demonstrated system capabilities and processing time reductions as compared to the current manual process planning for hybrid manufacturing methodologies. Using the generated FAH-PS process plan resulted in a 35% reduction in machining time from the current hybrid manufacturing strategy. Imploring a strategy of minimizing tool and orientation changes generated a process plan that demonstrated that even further improvements were possible. [ABSTRACT FROM AUTHOR]

For successful cartilage tissue engineering, the ability to generate a high number of chondrocytes in vitro while avoiding terminal differentiation or de-differentiation is critical. The ability to accomplish this by using the abundant and easily sampled costal cartilage could provide a practical alternative to the use of articular cartilage and mesenchymal stem cells. Chondrocytes isolated from pig costal cartilage were expanded in either serum-free medium with FGF2 (SFM) or fetal bovine serum-containing medium (SCM), under either high (21%) or low (5%) oxygen conditions. Overall, chondrocytes cultured in SFM and low oxygen (Low-SFM) demonstrated the highest cell growth rate ( p < 0.05). The effect of passage number on the differentiation status of the chondrocytes was analyzed by alkaline phosphatase (AP) staining and real-time PCR for known chondrocyte quality markers. AP staining indicated that chondrocytes grown in SCM had a higher proportion of terminally differentiated (hypertrophic) chondrocytes ( p < 0.05). At the mRNA level, expression ratios of ACAN/VCAN and COL2/COL1 were significantly higher ( p < 0.05) in cells expanded in Low-SFM, indicating reduced de-differentiation. In vitro re-differentiation capacity was assessed after a 6-week induction, and chondrocytes grown in Low-SFM showed similar expression ratios of COL2/COL1 and ACAN/VCAN to native cartilage. Proteomic analysis of in vitro produced cartilage indicated that the Low-SFM condition most closely matched the proteomic profile of native costal and articular cartilage. In conclusion, Low-SFM culture conditions resulted in improved cell growth rates, reduced levels of de-differentiation during expansion, greater ability to re-differentiate into cartilage on induction, and an improved proteomic profile that resembles that of in vivo cartilage. [ABSTRACT FROM AUTHOR]

Over the last decade, bioprinting has emerged as a promising technology in the fields of tissue engineering and regenerative medicine. With recent advances in additive manufacturing, bioprinting is poised to provide patient-specific therapies and new approaches for tissue and organ studies, drug discoveries and even food manufacturing. Manufacturing Readiness Level (MRL) is a method that has been applied to assess manufacturing maturity and to identify risks and gaps in technology-manufacturing transitions. Technology Readiness Level (TRL) is used to evaluate the maturity of a technology. This paper reviews recent advances in bioprinting following the MRL scheme and addresses corresponding MRL levels of engineering challenges and gaps associated with the translation of bioprinting from lab-bench experiments to ultimate full-scale manufacturing of tissues and organs. According to our step-by-step TRL and MRL assessment, after years of rigorous investigation by the biotechnology community, bioprinting is on the cusp of entering the translational phase where laboratory research practices can be scaled up into manufacturing products specifically designed for individual patients. [ABSTRACT FROM AUTHOR]

Product life ends when a product cannot adapt itself to new requirements, such as advances of technology, changes in customers’ preferences, etc. Product upgrade is an effective means to extend the product life, especially for high-investment, low-volume, and long-lifetime products; however, upgrade planning is complex both for product developers and product users. A product upgrade problem can be modeled as a series of decisions over time, and involve trade-offs between product performance and operation costs. These upgrade decisions might also be influenced by future technology changes. This paper proposes a quantitative method based on dynamic programming to help upgrade planners and product users to find an optimal upgrade plan incorporating the forecasts for technology development and end-of-life decisions. Through this method, total useful life cost can be minimized and sustainability can be also improved by upgrading appropriate modules at the right time with minimal impact on the system performance. [ABSTRACT FROM AUTHOR]

This article presents economic models for a new hybrid method where additive manufacturing (AM) and subtractive methods (SMs) are integrated through composite process planning. Although AM and SM offer several unique advantages, there are technological limitations such as tolerance and surface finish requirements; tooling and fixturing, etc. that cannot be met by a single type of manufacturing. The intent of this article is not to show a new manufacturing method, but rather to provide economic context to additive and subtractive methods as the best practice provides, and look at the corresponding economics of each of those methods as a function of production batch size, machinability, cost of the material, part geometry and tolerance requirements. Basic models of fixed and variable costs associated with additive, subtractive and hybrid methods to produce parts are also presented. An experimental design is used to study the influence of production volume, material and operating cost, batch size, machinability of the material and impact of reducing AM processing time. A composite response model for the unit cost is computed for the various levels associated with such engineering requirements. The developed models provide insight into how these variables affect the costs associated with engineering a mechanical product that will be produced using AM and SM methods. From the results, it appears that batch size, AM processing time and AM processing cost were the major cost factors. It was shown that the cost of producing ‘near-net’ shape through SM and AM was the decision criteria; which will be critical for tough-to-machine alloys and at multi-batch size. [ABSTRACT FROM AUTHOR]

Due to the rough nature of surfaces produced by current additive metal processes, a deviation between the nominal and actual pose of the part arises when fixturing in an NC machine. Modern 3D scanning systems are capable of generating high density measurements that may be used to localize the part and compensate for these errors; but require that scan data be transformed from the scanner to the CNC coordinate systems. In this work, precisely located fiducial features are automatically detected in the scan data and used to compute the pose of the scanner. This information is used to register each scan to the CNC machine space, and thereby create a model of the workpiece as-built and as-mounted in the machine, for use in process planning and localization. An implementation of the system was built and tested against a machined part that was offset to simulate uncertain position and orientation. The initial performance evaluation of the system indicates that it is capable of successfully registering surfaces to the machine coordinate system with accuracy in line with the scanner performance specification. [ABSTRACT FROM AUTHOR]

Most of the product life cycle costs and environmental impacts are determined during product design stage. A product supply chain network can be seen as a system dealing with product life cycle processes. Ideally, a product should be designed to have a structure yielding a good life cycle performance in its existing supply chain network. However, there is a lack of research related to modeling supply chain effects in the product design stage. This paper aims at investigating the supply chain effects on product modular design. The life cycle performance of a modular structure (life cycle cost and life cycle environmental impact) at various supply chain states is evaluated by a supply chain evaluation model and analyzed by statistical techniques. The preliminary results indicate that the supply chain-related effects on product life cycle performance are significant and modular structure optimization is effective in reducing the surge of life cycle cost and life cycle environmental impact caused by various supply chain states. The main supply chain effects are identified for use in product design improvement. [ABSTRACT FROM AUTHOR]

There is a pressing need to control the occurrences of nosocomial infections due to their detrimental effects on patient well-being and the rising treatment costs. To prevent the contact transmission of such infections via health-critical surfaces, a prophylactic surface system that consists of an interdigitated array of oppositely charged silver electrodes with polymer separations and utilizes oligodynamic iontophoresis has been recently developed. This paper presents a systematic study that empirically characterizes the effects of the surface system parameters on its antibacterial efficacy, and validates the system's effectiveness. In the first part of the study, a fractional factorial design of experiments (DOE) was conducted to identify the statistically significant system parameters. The data were used to develop a first-order response surface model to predict the system's antibacterial efficacy based on the input parameters. In the second part of the study, the effectiveness of the surface system was validated by evaluating it against four bacterial species responsible for several nosocomial infections - Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa, and Enterococcus faecalis - alongside non-antibacterial polymer (acrylic) control surfaces. The system demonstrated statistically significant efficacy against all four bacteria. The results indicate that given a constant total effective surface area, the system designed with micro-scale features (minimum feature width: 20 μm) and activated by 15 μA direct current will provide the most effective antibacterial prophylaxis. [ABSTRACT FROM AUTHOR]

Nanomaterials play a significant role in biomedical research and applications because of their unique biological, mechanical, and electrical properties. In recent years, they have been utilized to improve the functionality and reliability of a wide range of implantable medical devices ranging from well-established orthopedic residual hardware devices (e.g., hip implants) that can repair defects in skeletal systems to emerging tissue engineering scaffolds that can repair or replace organ functions. This review summarizes the applications and efficacies of these nanomaterials that include synthetic or naturally occurring metals, polymers, ceramics, and composites in orthopedic implants, the largest market segment of implantable medical devices. The importance of synergistic engineering techniques that can augment or enhance the performance of nanomaterial applications in orthopedic implants is also discussed, the focus being on a low-intensity direct electric current (LIDC) stimulation technology to promote the long-term antibacterial efficacy of oligodynamic metal-based surfaces by ionization, while potentially accelerating tissue growth and osseointegration. While many nanomaterials have clearly demonstrated their ability to provide more effective implantable medical surfaces, further decisive investigations are necessary before they can translate into medically safe and commercially viable clinical applications. The article concludes with a discussion about some of the critical impending issues with the application of nanomaterials-based technologies in implantable medical devices, and potential directions to address these. WIREs Nanomed Nanobiotechnol 2013, 5:191-204. doi: 10.1002/wnan.1201 Conflict of interest: Drs. Richard A. Wysk and Paul H. Cohen are Principals in ArgentumCidalElectrics Inc., Lewistown, PA, a company with multiple patents pending on the LIDC activated antimicrobial technology discussed in this article. Drs. Rohan A. Shirwaiker and Nancy A. Monteiro-Riviere have previously received a research grant from the company to study the cytotoxic effects of the LIDC activated antimicrobial technology. For further resources related to this article, please visit the WIREs website. [ABSTRACT FROM AUTHOR]

The increased use of Residual Hardware Devices (RHDs) in medicine combined with antimicrobial resistant-bacteria make it critical to reduce the number of RHD associated osteomyelitic infections. This paper proposes a surface treatment based on ionic emission to create an antibiotic environment that can significantly reduce RHD associated infections. The Kirby-Bauer agar gel diffusion technique was adopted to examine the antimicrobial efficacy of eight metals and their ionic forms against seven microbes commonly associated with osteomyelitis. Silver ions (Ag+) showed the most significant bactericidal efficacy. A second set of experiments, designed to identify the best configuration and operational parameters for Ag+ based RHDs addressed current and ionic concentrations by identifying and optimizing parameters including amperage, cathode and anode length, separation between anode and cathode, and surface charge density. The system demonstrated an unparalleled efficacy. The concept was then implemented during in vitro testing of an antimicrobial hip implant, RHD. [ABSTRACT FROM AUTHOR]

In this paper, we define a representation for tolerances associated with robotic machine tending operations. The intent of the representation and analysis presented in the paper is to assess whether a robotic material handler is capable of holding the accuracies required for loading and unloading a machine. This representation and analysis, therefore, provides the basis of a process planning system for robotic operations. This representation is critical for flexible and automated manufacturing because it enables automatic planning of unload and load operations from and to machining centers that are required for discrete part manufacturing. Planners can use this representation along with the specified tolerance criteria to conservatively assess if a given robot resource is capable of using a specific gripper to unload or load a given part from a given fixture on a machining center. For a new part, this assessment allows an automatic material handling operations planner to determine if reconfiguration or procurement of resources is required for the material handing of the new part or if simple reprogramming of the robot and machine resources is sufficient. Also, this representation helps providing flexibility to the manufacturing system control software in the case of the addition of a new machine to the manufacturing system. In this case, the new resource data would be input into the resource model, and the decision on the machine tending operations (loading or unloading) would be carried out in the same manner. This representation was tested successfully using an automatic operations planner at The Pennsylvania State University’s Factory for Advanced Manufacturing Education (FAME) lab. [ABSTRACT FROM AUTHOR]