Development of manufacturing control strategies using unsupervised machine learning

This research considers the control of manufacturing systems that support job routing and process sequence flexibility. A machine learning system is presented that uses a simulation model of the target manufacturing system to discover opportunistic control rules. Learning is unsupervised and is driven by a genetic algorithm. The learning method requires very little a priori control knowledge. For this presentation, the decision-making agents are the part types being processed. Part types evolve cooperative strategies for selecting the best route through the manufacturing system based on simulated real-time information that describes the state of the system. Results are presented that demonstrate the effectiveness of the approach.     

Attrition mill operating characteristics

The attrition mill is a device for mechanically reducing solid particle size by intense agitation of a slurry of material being milled and coarse milling media. For example, in 10 hours of milling, specific surfaces of 40 and 25 m²/g were obtained for alumina and barite, corresponding to 38 and 56 nm equivalent spherical diameter, respectively. Size reduction rates for relatively coarse particles were first-order and increased linearly with power input to the mill. Optimum milling medium concentration corresponded to medium particles moving a distance of approximately 0.7 of their diameter before collision with another such particle. Power characteristics of the attrition mill were essentially the same as those of a radial flow turbine mixer. Laminar flow became disrupted at N_Re ≈ 200, while turbulent flow was established at N_Re > 8000. Slurries of fine powders exhibited the same linear power-average density dependence as single-phase liquids. However, a different dependence was observed with large particles.     

The reaction of activated vinyl compounds with cotton cellulose via internal catalysis

The reactions of a variety of activated vinyl compounds with cotton cellulose fabric containing quaternary ammonium hydroxide substituents were explored. Each reaction, catalyzed by the basic groups in the cellulose, was followed to or near the point of leveling off. The results are analyzed and discussed in terms of accessibility of the cellulosic compositions and in terms of the efficiency of the quaternary ammonium substituents as catalysts for the addition reactions. Estimates of relative forward rate constants (k_f) and equilibrium constants (K) for the reactions were made. The values of k_f for reactions of the vinyl compounds with the quaternary ammonium celluloses show a relative order which is similar to that for the reactions of the vinyl compounds with simple alcohols. Evidence is presented to indicate that, in some cases, the addition of vinyl compounds is accompanied by anionic-catalyzed graft polymerization.     

Studies of microhardness and mar resistance using a scanning probe microscope

Scanning probe microscopy (SPM) is in a period of rapid development. It shows great promise for characterizing coating surfaces. This paper describes modification of an SPM so that it can be used to mar the surfaces of coatings under controlled conditions and to characterize the mars. Mar resistance of coatings is analyzed in terms of a ‘three response, two mechanism model.' The three responses (fracture, elastic, and plastic) can be measured quantitatively using the SPM. Of the three responses, only two (fracture and plastic deformation) are marring mechanisms – elastic deformations recover instantaneously. In some cases mars resulting from plastic deformation may recover slowly with time or with immersion in water; this phenomenon is attributed to viscoelastic creep. Microhardness is also measured with the modified SPM. Some thermoset coatings appear to be substantially harder near their surfaces than in the mass of material, and such materials may respond quite differently to stress applied at different levels near the surface. This finding has important implications for all coating properties that are strongly influenced by the surface. A quantity called ‘micro mar resistance' is defined. It may be useful for comparing different coatings under specified conditions of marring. However, there can be no single quantity that expresses ‘mar resistance' of a coating under all conditions.     

Mosaic organization of DNA nucleotides

Long-range power-law correlations have been reported recently for DNA sequences containing noncoding regions. We address the question of whether such correlations may be a trivial consequence of the known mosaic structure ("patchiness") of DNA. We analyze two classes of controls consisting of patchy nucleotide sequences generated by different algorithms--one without and one with long-range power-law correlations. Although both types of sequences are highly heterogenous, they are quantitatively distinguishable by an alternative fluctuation analysis method that differentiates local patchiness from long-range correlations. Application of this analysis to selected DNA sequences demonstrates that patchiness is not sufficient to account for long-range correlation properties.     

On the definition of the intuitionistic fuzzy subgroups

In this paper, a new kind of intuitionistic fuzzy subgroup theory, which is different from that of Ma, Zhan and Davvaz (2008) [22], [23], is presented. First, based on the concept of cut sets on intuitionistic fuzzy sets, we establish the neighborhood relations between a fuzzy point $x_a$ and an intuitionistic fuzzy set $A$. Then we give the definitions of the grades of $x_a$ belonging to $A$, $x_a$ quasi-coincident with $A$, $x_a$ belonging to and quasi-coincident with $A$ and $x_a$ belonging to or quasi-coincident with $A$, respectively. Second, by applying the 3-valued Lukasiewicz implication, we give the definition of $(\alpha ,\beta )$-intuitionistic fuzzy subgroups of a group $G$ for $\alpha ,\beta \in \{\in ,q,\in \wedge q,\in \vee q\}$, and we show that, in 16 kinds of $(\alpha ,\beta )$-intuitionistic fuzzy subgroups, the significant ones are the $(\in ,\in )$-intuitionistic fuzzy subgroup, the $(\in ,\in \vee q)$-intuitionistic fuzzy subgroup and the $(\in \wedge q,\in )$-intuitionistic fuzzy subgroup. We also show that $A$ is a $(\in ,\in )$-intuitionistic fuzzy subgroup of $G$ if and only if, for any $a\in (0,1]$, the cut set $A_a$ of $A$ is a 3-valued fuzzy subgroup of $G$, and $A$ is a $(\in ,\in \vee q)$-intuitionistic fuzzy subgroup (or $(\in ,\in \vee q)$-intuitionistic fuzzy subgroup) of $G$ if and only if, for any $a\in (0,0.5]$(or for any $a\in (0.5,1]$), the cut set $A_a$ of $A$ is a 3-valued fuzzy subgroup of $G$. At last, we generalize the $(\in ,\in )$-intuitionistic fuzzy subgroup, $(\in ,\in \vee q)$-intuitionistic fuzzy subgroup and $(\in \wedge q,\in )$-intuitionistic fuzzy subgroup to intuitionistic fuzzy subgroups with thresholds, i.e., $(s,t]$-intuitionistic fuzzy subgroups. We show that $A$ is a $(s,t]$-intuitionistic fuzzy subgroup of $G$ if and only if, for any $a\in (s,t]$, the cut set $A_a$ of $A$ is a 3-valued fuzzy subgroup of $G$. We also characterize the $(s,t]$-intuitionistic fuzzy subgroup by the neighborhood relations between a fuzzy point $x_a$ and an intuitionistic fuzzy set $A$.     

Assessment of working conditions in two different semiconductor manufacturing lines: Effective ergonomics interventions

This article examines two manufacturing lines producing semiconductors using different technology concepts, namely Conventional Line (CL) and Lean Production Line (LPL). Both lines manufacturing the same products were compared using various factors, including working conditions, task risks and dangers of the job, and physical body stress. Ergonomic approaches were adopted in the investigation of the two lines. Survey questionnaires were administered to 30% of the workers, and multiple statistical tests were used to determine crucial predictors and to investigate the interactions between the factors. This research has shown that improved ergonomics factors will lead to better working conditions and thus increased job satisfaction. The observed ergonomic differences of these two production lines are compared, and appropriate managerial remedial action is recommended. The interventions to both the lines should reduce accident rates, minimize waste of resources, improve work effectiveness, and provide a better working environment that enhances employees' morale and maximizes productivity and profits. © 2010 Wiley Periodicals, Inc.