Discrete Production Research Articles

Classification of R&D infrastructure models in basic business incubators technology in the state of Paraná

Support for the development of new technology-based business is a major challenge in Brazil. One reason is the change of the paradigm of an economy based on supply of commodities to an economy of developing and offering technology. In this environment, business incubators are presented as a key player in this process. However, incubators lack of infrastructure available for the technological development of products, as entrepreneurs begin to demand something beyond basic infrastructure. This article aims to classify research and development infrastructure models, based on the degree of importance earned by entrepreneurs belonging to incubators of technology-based companies in the state of Parana. An extensive literature review identified seven research infrastructure development models and discrete manufacturing products. These models were then classified by their features and practices. Following, a hierarchy was built, using the Analytic Hierarchy Process (AHP). Based on this hierarchy, an electronic questionnaire was designed and it was applied to 115 entrepreneurs belonging to 15 incubators of technology-based company, all located in the state of Parana. The responses were used for the construction of the weights of criteria based on the characteristics and analyzed practices. Finally, seven models were classified according to the AHP, providing incubator managers with the best options of laboratory models, according to the characteristics and needs.

Firm Strategy in Business Ecosystems: An Empirical Review

In this paper, I review the key strategic issues confronting firms that operate in business ecosystems–networks of complementary firms that produce discrete products or services that comprise a coh...

Asymptotics for varying discrete Sobolev orthogonal polynomials

We consider a varying discrete Sobolev inner product such as(f,g)S=∫f(x)g(x)dμ+Mnf(j)(c)g(j)(c),where μ is a finite positive Borel measure supported on an infinite subset of the real line, c is adequately located on the real axis, j≥0, and {Mn}n≥0 is a sequence of nonnegative real numbers satisfying a very general condition. Our aim is to study asymptotic properties of the sequence of orthonormal polynomials with respect to this Sobolev inner product. In this way, we focus our attention on Mehler-Heine type formulae as they describe in detail the asymptotic behavior of these polynomials around c, just the point where we have located the perturbation of the standard inner product. Moreover, we pay attention to the asymptotic behavior of the (scaled) zeros of these varying Sobolev polynomials and some numerical experiments are shown. Finally, we provide other asymptotic results which strengthen the idea that Mehler–Heine asymptotics describe in a precise way the differences between Sobolev orthogonal polynomials and standard ones.

Determination of the machine energy consumption profiles in the mass-customised manufacturing

This paper presents an original methodology and related algorithms that are dedicated to monitoring energy efficiency in discrete production stations. The learning phase of the algorithm is executed during the regular production process and is based on observations of the behaviour of the production station and energy consumption measurements. The collected information is then processed using data-mining procedures in order to find the clusters that reflect the energy consumption profiles that are specific for different variants of production. The profiles are used to monitor energy efficiency and detect anomalies. The main benefit of the proposed approach is its flexibility. No additional calibrating operations or technological knowledge are required. Although the presented proof by research results are focussed on pneumatic air installations, the proposed methodology can also be used for other media. The output of the proposed solution is a very precise estimation of energy consumption in reference to a given variant of production. It allows for the accurate detection of compressed air consumption anomalies. Such anomalies can be caused by technical (machine faults) and technological (human errors) problems. The proposed methodology can be applied for the optimisation of energy consumption and for the detection of machine maintenance problems that are visible through abnormal compressed air consumption.

Symmetric Boundary Condition for Laplacian on Net of Regular Hexagons

Hexagonal grid methods are found useful in many research works, including numerical modeling in spherical coordinates, in atmospheric and ocean models, and simulation of electrical wave phenomena in cardiac tissues. Almost all of these used standard Laplacian and mostly on one configuration of regular hexagons. In this work, discrete symmetric boundary condition and energy product for anisotropic Laplacian are investigated firstly on general net of regular hexagons, and then generalized to its most extent in two- or three-dimensional cell-center finite difference applications up to the usage of symmetric stencil in central differences. For analysis of Laplacian related applications, this provides with an approach in addition to the M-matrix theory, series method, functional interpolations and Fourier vectors.

Bidirectional transfer between joint and individual actions in a task of discrete force production.

The present study examined bidirectional learning transfer between joint and individual actions involving discrete isometric force production with the right index finger. To examine the effects of practice of joint action on performance of the individual action, participants performed a pre-test (individual condition), practice blocks (joint condition), and a post-test (individual condition) (IJI task). To examine the effects of practice of the individual action on performance during the joint action, the participants performed a pre-test (joint condition), practice blocks (individual condition), and a post-test (joint condition) (JIJ task). Whereas one participant made pressing movements with a target peak force of 10% maximum voluntary contraction (MVC) in the individual condition, two participants produced the target force of the sum of 10% MVC produced by each of them in the joint condition. In both the IJI and JIJ tasks, absolute errors and standard deviations of peak force were smaller post-test than pre-test, indicating bidirectional transfer between individual and joint conditions for force accuracy and variability. Although the negative correlation between forces produced by two participants (complementary force production) became stronger with practice blocks in the IJI task, there was no difference between the pre- and post-tests for the negative correlation in the JIJ task. In the JIJ task, the decrease in force accuracy and variability during the individual action did not facilitate complementary force production during the joint action. This indicates that practice performed by two people is essential for complementary force production in joint action.

Energy-Efficient Production Scheduling of a Cryogenic Air Separation Plant

Power-intensive processes, such as cryogenic air separation in which the major portion of the production cost is spent on energy/electricity, need to adopt a smart operational approach to ensure maximum usage of resources while minimizing the power cost. In this paper a state task network-based model of an air separation plant is designed to represent real world production constraints. A discrete time model-based production scheduling has been proposed and validated on several scenarios that reflects representative real time constraints. The optimal schedule found for every scenario chosen has shown efficient exploitation of all energy contracts and judicious utilization of the liquid products. Due to its granular and rigorous modeling approach along with computational efficiency, the proposed model manifests huge potential toward its implementation in a real-world air separation plant.

Research on manufacturability optimization of discrete products with 3D printing involved and lot-size considered

Most of the present researches in production management under the influence of three-dimensional (3D) printing technique are qualitative. The manufacturability optimization of production combining 3D printing and traditional manufacture is discussed from a point of quantitative view in this paper. A mathematical model of manufacturability optimization considering lot-size is proposed and a differential evolution (DE) algorithm is introduced to optimize the model. Numerical tests on the model and the algorithm reveal the quantitative changes with bringing in 3D printing. The model can be applied to optimize the manufacturability considering lot-size that combines 3D printing and traditional manufacture. The research is expected to offer a reference to promote the practical application in the way of 3D printing industrialization.

Mario Becomes Cognitive.

In line with Allen Newell's challenge to develop complete cognitive architectures, and motivated by a recent proposal for a unifying subsymbolic computational theory of cognition, we introduce the cognitive control architecture SEMLINCS. SEMLINCS models the development of an embodied cognitive agent that learns discrete production rule-like structures from its own, autonomously gathered, continuous sensorimotor experiences. Moreover, the agent uses the developing knowledge to plan and control environmental interactions in a versatile, goal-directed, and self-motivated manner. Thus, in contrast to several well-known symbolic cognitive architectures, SEMLINCS is not provided with production rules and the involved symbols, but it learns them. In this paper, the actual implementation of SEMLINCS causes learning and self-motivated, autonomous behavioral control of the game figure Mario in a clone of the computer game Super Mario Bros. Our evaluations highlight the successful development of behavioral versatility as well as the learning of suitable production rules and the involved symbols from sensorimotor experiences. Moreover, knowledge- and motivation-dependent individualizations of the agents' behavioral tendencies are shown. Finally, interaction sequences can be planned on the sensorimotor-grounded production rule level. Current limitations directly point toward the need for several further enhancements, which may be integrated into SEMLINCS in the near future. Overall, SEMLINCS may be viewed as an architecture that allows the functional and computational modeling of embodied cognitive development, whereby the current main focus lies on the development of production rules from sensorimotor experiences.

Cost Modeling for ABC Failure of Machines

In this paper we analyze Weibull generated failures of equipment in discrete production. At first we will classify failures using ABC analysis. Obtained characteristics of each group of failures can be used to generate time of their occurrence and duration which are essential for assessment of their cost. We use optimization tool Solver from MS Office - Excel to solve problem of maintenance of machines. We optimize strategy of maintenance also according to cost of failures in categories ABC classification. Results of this optimization are tables, graphs, having that it can offer to managers a new unconventional access at the efficiency of investment. We create the proposed approach of solving models on demonstration example.

Characterization of the Second Parcel of the Alternative Buffer Material (ABM) Experiment — I Mineralogical Reactions

AbstractThe performance of bentonite barriers for high level radioactive waste (HLRW) disposal is currently being tested in various real-and up-scale disposal tests. One of the disposal tests, the ABM test (ABM = alternative buffer material), was conducted by SKB (Svensk Kärnbränslehantering) as a mediumscale experiment at the Äspö hard rock laboratory in Sweden. The present study deals with the second parcel (ABM-II), which was retrieved after 6.5 years with 2.5 years of water saturation and 3–4 years of heating up to 141°C. Nine different bentonites and two marine clays were tested to investigate the performance. The aim of the study was to provide a detailed characterization of the mineralogical and chemical changes that took place in ABM-II, compare the findings with ABM-I (the first of the six test parcels), and try to draw some general conclusions concerning the use of bentonites in such geotechnical barriers. The ABM-II test parcel revealed a set of reactions that a HLRW bentonite might undergo. The most prominent reaction was the rather complete exchange of cations, which was discussed in a second part to this publication (II — cation exchange; Dohrmann and Kaufhold, 2017). The corrosion of the Fe in metal canisters was observed, but no discrete corrosion product was identified. At the interface of bentonite and the metal canister, the formation of smectite-type trioctahedral clay minerals was observed. In contrast to the ABM-I test, anhydrite was present in many of the bentonite blocks of the ABM-II test. In most concepts used for HLRW disposal in crystalline rocks, a temperature below 100°C at the canister surface was applied to avoid boiling. In the ABM-II test, boiling of water was possibly observed. Throughout the experiment, a pressure/water loss was recorded in the upper part of the geotechnical barrier and water was added to maintain pressure in the bentonite. As a result of evaporation, NaCl crusts might have formed and the barrier was partly disintegrated. These results demonstrated that a reasonable assumption is that no boiling of water occurs in disposal concepts in which a pressure loss can occur.

The versatility of an entropy inequality for the robust computation of convection dominated problems

We present a discrete inequality that exhibits versatile uses in convection dominated problems. Much like the thermodynamic entropy inequality, the sign of this so-called discrete entropy production allows us to determine unphysical regions in the numerical solution without any a-priori knowledge of the solution. Further, the sign of the discrete production also functions as an excellent indicator for mesh adaptation in convection-diffusion and other singular perturbation problems. We also show preliminary results for how the operator can be used to derive robust schemes for convection dominated problems. All the above applications i.e. (a) Detecting unphysical numerical behavior, (b) mesh adaptation and (c) stabilization, are robust in that they are achieved without any ad-hoc, user introduced, parameters. We show a range of numerical results that exhibit the efficacy of the operator.

“Turning Ourselves”

In 1974, Robert Fripp—leader of the progressive rock group King Crimson—had a spiritual experience in which “the top of [his] head blew off.” He became a student of J. G. Bennett, himself a former student of G. I. Gurdjieff, at Sherborne House in Gloucestershire, and remains a member of the Bennett Foundation to this day. When Fripp returned to the music industry, it was with an approach that favored disciplined and geometric compositions over the jagged improvisation of the earlier period. This article explores the influence of Gurdjieff and Bennett’s teaching upon Fripp and his work, and his apparent attempts to realize the former’s idea of “objective art” through his music. I pay particular attention to the development of Guitar Craft, in which Fripp applies Gurdjieff’s techniques through the teaching of the guitar. I argue that Fripp’s teaching is a little examined scion of the Gurdjieff lineage, and a case study of discrete cultural production.

Real-Time Demand Bidding for Energy Management in Discrete Manufacturing Facilities

During periods of power system stress, demand bidding (DB) programs encourage large electricity consumers to submit curtailment capacity bids and carry out load reduction, in return for financial rewards. In this paper, a real-time DB (RT-DB) program with applications in discrete manufacturing facilities is considered. A discrete manufacturing production model is constructed and an automated RT-DB algorithm is designed. An optimization problem, where the objective is to maximize the profits for manufacturers, is formulated. Solving this problem enables the RT-DB algorithm to automatically generate optimal load-reduction bids with adjusted production and energy plans. A case study is described, which shows that the proposed algorithm reduced the load demand during an RT-DB event, increasing the manufacturer's profits. Furthermore, the relationship between the incentive rate and the demand elasticity of the consumer, as well as the production volume and profits is described.

Utilization of Product Lifecycle Data from PLM Systems in Platforms for Industrial Symbiosis

Industrial Symbiosis represents a promising approach to foster the transformation towards a circular economy. To involve businesses in Industrial Symbiosis, online platforms and input-output matching tools for facilitating the exchange of by-products have been provided by industry organizations and facilitators. Regarding the discrete parts and product manufacturing industry (DPPM), little success is being reported for such platforms and tools. Within the scope of this research, a list of Input-Output matching tools was analysed regarding data sources which are currently used for input-output Matching. Specifications of by-products in the DPPM industry were reviewed in order to identify a list of requirements for data sources. Shortcomings of the currently existing input-output matching tools were identified and suggestions for additional data sources used for input-output matching in IS in DPPM were given. Results show that datasets currently used do not include organisational data sources such as Product Data Management (PDM) systems, Enterprise Resource Planning (ERP) systems, Supply Chain Management (SCM) systems, and or Manufacturing Execution Systems (MES).

Finite Fourier decomposition of signals using generalized difference operator

In this paper, we introduce discrete inner product of two functions, discrete orthogonal and orthonormal system of functions and develop finite Fourier series for polynomial factorial, polynomial, exponential, rational and logarithm functions using the inverse of generalized difference operator.

Measuring the Spillovers of Venture Capital

We provide the first measurement of knowledge spillovers from venture capital-financed companies onto the patenting activities of other companies. On average, these spillovers are nine times larger than those generated by the R&D investment of established companies. Spillover effects are larger in complex product industries than in discrete product industries. Start-ups with experienced inventors holding a patent at the time of receiving the first round of investment produce the largest spillovers, indicating that venture capital fosters the commercialization of technologies. Methodologically, we contribute by developing a novel definition of the spillover pool, combining citation-based and technological proximity-based approaches.

Linear Reformulation of Polynomial Discrete Programming for Fast Computation

Polynomial discrete programming problems are commonly faced but hard to solve. Treating the nonconvex cross-product terms is the key. State-of-the-art methods usually convert such a problem into a 0-1 mixed-integer linear programming problem and then adopt the branch-and-bound scheme to find an optimal solution. Much effort has been spent on reducing the required numbers of variables and linear constraints as well as on avoiding unbalanced branch-and-bound trees. This study presents a set of equations that linearize the discrete cross-product terms in an extremely effective manner. It is shown that embedding the proposed “equations for linearizing discrete products” into those state-of-the-art methods in the literature not only significantly reduces the required number of linear constraints from O(h3n3) to O(hn) for a cubic polynomial discrete program with n variables in h possible values but also tighten these methods with much more balanced branch-and-bound trees. Numerical experiments confirm a two-order (102-times) reduction in computational time for some randomly generated cubic polynomial discrete programming problems. There is a Video Overview associated with this article, available as supplemental material.

Using a discrete product model to determine the design element junctures

This paper describes a discrete model of a standard airframe part. The model is intended for determining the junctures between the design elements of a node (unit) in the pre-assembly procedures. We herein propose an algorithm selecting base surfaces for basing the product being assembled; selections are made on the basis of the 3D model of such product.

Model-based Systems Engineering of Discrete Production Lines Using SysML: An Experience Report

During the design of complex mechatronic systems, multiple engineering teams covering disciplines such as mechanics, electronics, control and safety must cooperate and exchange information.Today's state-of-the-practice systems engineering methodologies rely on document-based approaches to elicit and manage requirements, describe the system architecture, log design decisions and exchange this information between the project members. Unfortunately, the informal character of the documents causes misinterpretations, generates inconsistencies and prohibits the use of computer power for validation.Model-based Systems Engineering techniques promise to alleviate some of these issues. SysML is a formal graphical modeling language that aims to support this model-based design of complex multidisciplinary systems. Yet, as SysML is a general-purpose language intended to cover a broad range of systems, applying SysML to a specific domain such as production lines is not a trivial task.In this paper, we present some experiences and limitations encountered when applying and tailoring SysML 1.4 to support the systems engineering process of an industrial use case: the design of a production line by a multi-disciplinary team across several companies, consisting of process experts, control engineers, thermal designers, software engineers, mechanical designers, signal processing experts, roboticists and embedded hardware designers.