Window Fill Rate with Compound Arrival and Assembly Time

2018 ◽  
pp. 677-683
Author(s):  
Michael Dreyfuss ◽  
Yahel Giat
Keyword(s):  
Fill Rate ◽  
Assembly Time

Match Day Reveals Slip In Psychiatry Fill Rate

2006 ◽  
Vol 34 (4) ◽  
pp. 1-76
Author(s):  
JOYCE FRIEDEN
Keyword(s):  
Fill Rate

Family Medicine Fill Rate Turned Upward This Match

2006 ◽  
Vol 36 (7) ◽  
pp. 54
Author(s):  
JOYCE FRIEDEN
Keyword(s):  
Family Medicine ◽  
Fill Rate

scholarly journals Chitosan-Based Adhesive: Optimization of Tensile Shear Strength in Dry and Wet Conditions

2021 ◽  
Vol 2 (1) ◽  
pp. 110-120
Author(s):  
Maisa Abdelmoula ◽  
Hajer Ben Hlima ◽  
Frédéric Michalet ◽  
Gérard Bourduche ◽  
Jean-Yves Chavant ◽  
...  
Keyword(s):  
Molecular Weight ◽  
Shear Strength ◽  
Bond Strength ◽  
Water Resistance ◽  
Tensile Shear Strength ◽  
Tensile Shear ◽  
Spread Rate ◽  
Assembly Time ◽  
Deacetylation Degree ◽  
Dry And Wet Conditions

Commercial adhesives present a high bond strength and water resistance, but they are considered non-healthier products. Chitosan can be considered as an interesting biosourced and biodegradable alternative, despite its low water resistance. Here, its wood bonding implementation and its tensile shear strength in dry and wet conditions were investigated depending on its structural characteristics. Firstly, the spread rate, open assembly time, drying pressure, drying temperature, and drying time have been determined for two chitosans of European pine double lap specimens. An adhesive solution spread rate of 1000 g·m−2, an open assembly time of 10 min, and a pressure temperature of 55 °C for 105 min led to a bond strength of 2.82 MPa. Secondly, a comparison between a high molecular weight/low deacetylation degree chitosan and a lower molecular weight/higher deacetylation degree chitosan was conducted. Tests were conducted with beech simple lap specimens in accordance with the implementation conditions and the conditioning treatments in wet and dry environments required for thermoplastic wood adhesive standards used in non-structural applications (EN 204 and EN 205). The results clearly revealed the dependence of adhesive properties and water resistance on the structural features of chitosans (molecular weight and deacetylation degree), explaining the heterogeneity of results published notably in this field.

Ontological Knowledge Representation and Inference Rules for MTM Decision Support System

2014 ◽  
Author(s):  
Rahul Renu ◽  
Gregory Mocko
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Knowledge Representation ◽  
Support System ◽  
Time Estimation ◽  
Time Measurement ◽  
Inference Rules ◽  
Assembly Time ◽  
Time Estimates ◽  
Definition Of

The objective of the research presented is to develop and implement an ontological knowledge representation for Methods-Time Measurement assembly time estimation process. The knowledge representation is used to drive a decision support system that provides the user with intelligent MTM table suggestions based on assembly work instructions. Inference rules are used to map work instructions to MTM tables. An explicit definition of the assembly time estimation domain is required. The contribution of this research, in addition to the decision support system, is an extensible knowledge representation that models work instructions, MTM tables and mapping rules between the two which will enable the establishment of assembly time estimates. Further, the ontology provides an extensible knowledge representation framework for linking time studies and assembly processes.

Automated Navigation of Method Time Measurement Tables for Automotive Assembly Line Planning

2013 ◽  
Author(s):  
Rahul Renu ◽  
Matthew Peterson ◽  
Gregory Mocko ◽  
Joshua Summers
Keyword(s):  
Software Tool ◽  
Controlled Vocabulary ◽  
Prototype System ◽  
Assembly Process ◽  
Line Planning ◽  
Assembly Time ◽  
Study Results ◽  
Automotive Assembly ◽  
Cad Models ◽  
Assembly Procedure

Assembly process sheets are formal documents used extensively within automotive original equipment manufacturers (OEMs) to document and communicate assembly procedure, required tooling, contingency plans, and time study results. These sheets are authored throughout the vehicle life-cycle. Further, various customers use these sheets for training, analyzing the process, and line-balancing. In this research, the primary focus is the time studies analysis that is completed using knowledge contained within the assembly process sheets. In this research, a method and software tool are developed to utilize coupling between part descriptions and process descriptions for assembly time studies. The method is realized through the development of a standardized vocabulary for describing work instructions, a mapping from work instructions to MTM codes, and a tool for extracting relevant part information from CAD models. The approach enables process planners to establish part-process coupling, author work instructions using the controlled vocabulary, to estimate assembly time. A prototype system is developed and tested using examples from an automotive OEM.

Reasoning: Source of Variability in the Boothroyd and Dewhurst Assembly Time Estimation Method

2012 ◽  
Author(s):  
Essam Namouz ◽  
Joshua D. Summers ◽  
Gregory M. Mocko
Keyword(s):  
Engineering Students ◽  
Large Range ◽  
Estimation Method ◽  
Time Estimation ◽  
Handling Time ◽  
Time Estimate ◽  
Time Analysis ◽  
Assembly Time ◽  
Time Estimates ◽  
Initial Results

This paper evaluates the effect of making a subjective decision in a design for assembly time analysis. An example is found in the first set of questions for estimating handling time of a part the user chose “parts are easy to grasp and manipulate” as opposed to “parts present handling difficulties”. The subjectivity is explored through a study of assembly time estimates generated by a class of mechanical engineering students in the time analysis of a clicker pen based on the Boothroyd and Dewhurst estimation method. The assembly times calculated by the class ranged from a minimum of 23.64 seconds to a maximum of 44.89 seconds (range of 21.25 seconds). This large range in results serves as motivation in determining the effect that answering a subjective decision has on the resulting assembly time estimate. Initial results indicate that not answering the first level of subjective questions will result in assembly time estimate within 15% of the time had the subjective question been answered. The probability density plots of the time estimates also indicates that 63% of the time, the estimated assembly time without making the subjective decision will fall within the normal distribution had the subjective decision been made. This provides evidence that there is an opportunity to reduce the amount of subjective questions that a user must answer to estimate the assembly time of a product.

assembly time

2000 ◽  
pp. 67-67
Author(s):  
Martin H. Weik
Keyword(s):  
Assembly Time
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