Search Results

Future planetary extravehicular activities (EVAs) will go beyond what was experienced during Apollo. As mission duration becomes longer, inevitably, the astronauts on the surface of the Moon and Mars will actively plan and re-plan their own sorties. To design robust decision support aids for these activities, we have to first characterize all the different types of excursions that are possible. This paper describes a framework that organizes parameters and constraints that define a single planetary EVA. We arrived at this framework through case studies: by reviewing the EVA lessons learned during Apollo, conducting an observational study of excursions in a Mars-analog environment, and applying part of the framework to a prototype path planner for human planetary exploration.

One of the goals of designing engineering systems is to maximize the system's reliability. A reliable system must satisfy its functional requirements without failure throughout its intended lifecycle. The typical means to achieve a desirable level of reliability is through preventive maintenance of a system; however, this involves cost. A more fundamental approach to the problem is to maximize the system's reliability by preventing failures from occurring. A key question is to find mechanisms (and the means to implement them into a system) that will prevent its system range from going out of the design range. Functional periodicity is a means to achieve this goal. Three examples are discussed to illustrate the concept. In the new electrical connector design, it is the geometric functional periodicity provided by the woven wire structure. In the case of integrated manufacturing systems, it is the periodicity in scheduling of the robot motion.

Future human space exploration includes returning to the Moon and continuing to Mars. Essential to these missions is each planetary extravehicular activity, or EVA, where astronauts and robotic agents will explore lunar and planetary surfaces. Real-time decision support systems will help these explorers in efficiently planning and re-planning under time pressure sorties. Information and functional requirements for such a system are recommended and are based on on-going human-computer collaboration research.

New three-dimensional printing technology (3DP) developed at MIT was tried as a manufacturing method to fabricate ceramic preforms for a discontinuously reinforced metal matrix composites. Minor modifications to the “legacy” 3DP technology allowed to produce such preforms successfully. Preforms were then infiltrated with liquid aluminum resulting in composite materials as strong as produced via conventional methods. Net shape connecting rod preforms were 3D-printed and used to produce composite connecting rods without building any molds or tooling using novel Tool-less Mold™ technology.

A one-dimensional model has been developed for the species and energy transfer over a thin (0.1-0.5 mm) layer of liquid fuel present on the wall of a spark-ignition engine. Time-varying boundary conditions during compression and flame passage were used to determine the rate of methanol vaporization and oxidation over a mid-speed, mid-load cycle, as a function of wall temperature. The heat of vaporization and the boiling point of the fuel were varied about a baseline to determine the effect of these characteristics, at a fixed operating point and lean conditions (ϕ = 0.9). The calculations show that the evaporation of fuels from layers on cold walls starts during flame passage, peaking a few milliseconds later, and continuing through the exhaust phase.

Many vehicle-dynamics models exist to study the motion of a vehicle. Most of these models fall into one of two categories: very simple models for basic analyses and high-order models consisting of many degrees-of-freedom. For many scenarios, the simple models are not adequate. At the same time, for many vehicle handling and braking studies, the high-order models are more complex than necessary. This paper presents a model that includes the dynamics that are relevant to studying vehicle handling and braking, but is still simple enough to run in near real-time. The model was implemented in such a way that it is easily customized for a particular study. Predictions from this simplified model were compared against a high-order model and against actual vehicle test data. The simulations indicate a close agreement in the results.

Numerical calculations of the fuel spray structure from a high-pressure swirl injector were used to enable the interpretation of experimental observations obtained in hot, hollow-cone fuel sprays issued into sub-atmospheric-pressure environments. The experiments show that the spray becomes narrower, more compact, but with a relatively long penetration depth. Model input parameters, including the droplet size distribution, early vapor production, and initial cone angle, were modified to determine which spray characteristics are important in recreating observed spray structures. A very small mean droplet diameter is needed to recreate the experimentally observed structure of the high-temperature, low-pressure sprays. Vapor addition to the emerging spray is then required to increase the axial penetration and provide the observed vapor core.

Low volume manufacturing has become increasingly important for the automotive industry. Globalization trends have led automakers and their suppliers to operate in developing regions where minimum efficient scales can not always be achieved. With proper maintenance, standard cast iron stamping tools can be used to produce millions of parts, but require large investments. Thus at high production volumes, the impact of the tooling investment on individual piece costs is minimized. However, at low volumes there is a substantial cost penalty. In light of the trends towards localized manufacturing and relatively low demands in some developing markets, low cost stamping tools are needed. Several alternate tooling technologies exist, each of which require significantly lower initial investments, but suffer from greatly reduced tool lives. However, the use of these technologies at intermediate to high volumes requires multiple tool sets thus eliminating their cost advantage.

Recent industry trends have resulted in growing interest among automakers in low to medium volume manufacturing. The expansion of automobile production into developing economies and the desire to produce specialized vehicles for niche markets have pressed the automakers to find cost effective solutions for manufacturing at low volumes, particularly with regard to sheet metal forming. Conventional high volume stamping operations rely heavily on achieving minimum scale economies which occur at about 200,000 parts per year. These scale economies are mainly dictated by the efficient use of the standard, expensive cast iron dies. These dies can cost well over one million dollars depending on the part, and in return offer tool lives over 5 million strokes. Die investment can be reduced by changing the stamping process technology. Hydro-mechanical forming has been proposed as a promising low volume alternative to conventional stamping.

This paper presents an Axiomatic Design framework for manufacturing system design and illustrates how lean cellular manufacturing can achieve volume flexibility. Axiomatic Design creates a design framework by mapping the functional requirements of a system to specific design parameters. Volume flexibility is often neglected as a requirement of manufacturing systems. Very few industries are fortunate enough to experience stable or predictable product demand. In reality, demand is often volatile and uncertain. It is important that manufacturing system designers are aware of manufacturing system types which can accommodate volume flexibility and follow a structured design methodology that assures that all requirements are met by the system.

A design framework based on the principles of lean manufacturing and axiomatic design was used as a guideline for designing an automotive component manufacturing system. A brief overview of this design decomposition is given to review its structure and usefulness. Examples are examined to demonstrate how this design framework was applied to the design of a gear manufacturing system. These examples demonstrate the impact that low-level design decisions can have on high-level system objectives and the need for a systems-thinking approach in manufacturing system design. Results are presented to show the estimated performance improvements resulting from the new system design.

This session keynote paper presents a framework for designing and deploying production systems. The framework enables the communication and determination of objectives and design solutions from the highest level to the lowest level of a manufacturing enterprise. The design methodology ensures that the physical implementation, called Design Parameters (DPs), meets the objectives or Functional Requirements (FRs) of the production system design. This paper presents a revolutionary approach to determine the objectives and the implementation of a “lean” production system design for a manufacturing business as guided by the design axiom of independence.

The linked cell system gives both reduced cost and volume flexibility. The characteristics of the linked cell system are a consequence of decoupling the operators from the machines, using standard work in process between the cells and by integrating the information system with the cell and system design. By decoupling the operators from the machines the capacity can be increased/decreased in small increments by using more or fewer operators in the cell. The information system is integrated with the linked cell design by the use of a Heijunka box. The Heijunka is used to level production and to initiate the pace of production as a result of pulling withdrawal kanban at a standard time interval. This standard time interval is called the pitch of production. The kanban cards give information about what to produce, when to produce, when to make changeovers but they also give information to control the material replenishment.

Lean production has greatly influenced the way manufacturing systems should be designed. One important aspect of lean production is takt time. Takt time relates customer demand to available production time and is used to pace the production. This paper applies the manufacturing system design and deployment framework to describe the impact of takt time on both the design and the operation of a manufacturing system. The goal of this paper is to illustrate the relevant relationships of takt time to overall system design.

In a recent paper (Hoult & Meador, [1]) a novel method of estimating the costs of parts, and assemblies of parts, was presented. This paper proposed that the metric for increments of cost was the function log (dimension/tolerance). Although such log functions have a history,given in [1], starting with Boltzman and Shannon, it is curious that it arises in cost models. In particular, the thermodynamic basis of information theory, given by Shannon [2], seems quite implausible in the present context. In [1], we called the cost theory “Complexity Theory”, mainly to distinguish it from information theory. A major purpose of the present paper is to present a rigorous argument of how the log function arises in the present context. It happens that the agrument hinges on two key issues: properties of the machine making or assembling the part, and a certain limit process. Neither involves thermodynamic reasoning.

The Cu-zeolite (CuZ) SCR catalyst enables higher NOx conversion efficiency in part because it can store a significant amount of NH3. “NH3 storage control”, where diesel exhaust fluid (DEF) is dosed in accord with a target NH3 loading, is widely used with CuZ catalysts to achieve very high efficiency. The NH3 loading actually achieved on the catalyst is currently estimated through a stoichiometric calculation. With future high-capacity CuZ catalyst designs, it is likely that the accuracy of this NH3 loading estimate will become limiting for NOx conversion efficiency. Therefore, a direct measurement of NH3 loading is needed; RF sensing enables this. Relative to RF sensing of soot in a DPF (which is in commercial production), RF sensing of NH3 adsorbed on CuZ is more challenging. Therefore, more attention must be paid to the “microwave resonance cavity” created within the SCR assembly. The objective of this study was to develop design guidelines to enable and enhance RF sensing.

With the recent advancement in sensing and controller technologies architecture design of an autonomous driving system becomes an important issue. Researchers have been developing different sensors and data processing technologies to solve the issues associated with fast processing, diverse weather, reliability, long distance recognition performance, etc. Necessary considerations of diverse traffic situations and safety factors of autonomous driving have also increased the complexity of embedded software as well as architecture of autonomous driving. In these circumstances, there are almost countless numbers of possible architecture designs. However, these design considerations have significant impacts on cost, controllability, and system reliability. Thus, it is crucial for the designers to make a challenging and critical design decision under several uncertainties during the conceptual design phase.

This paper describes a post-race analysis of team KOMMIT EVT’s electric motorcycle data collected during the 2016 Pikes Peak International Hill Climb (PPIHC). The motorcycle consumed approximately 4 kWh of battery energy with an average and maximum speed of 107 km/h and 149 km/h, respectively. It was the second fastest electric motorcycle with a finishing time of 11:10.480. Data was logged of the motorcycle’s speed, acceleration, motor speed, power, currents, voltages, temperatures, throttle position, GPS position, rider’s heart rate and the ambient environment (air temperature, pressure and humidity). The data was used to understand the following factors that may have prevented a faster time: physical fitness of the rider, thermal limits of the motor and controller, available battery energy and the sprocket ratio between the motor and rear wheel.

Hybrid powertrains with multiple sources of power have generated new control challenges in the automotive industry. Purdue University's participation in EcoCAR 2, an Advanced Vehicle Technology Competition managed by the Argonne National Laboratories and sponsored by GM and DOE, has provided an exciting opportunity to create a comprehensive test-bench for the development and validation of advanced hybrid powertrain control strategies. As one of 15 competing university teams, the Purdue EcoMakers are re-engineering a donated 2013 Chevrolet Malibu into a plug-in parallel- through-the-road hybrid-electric vehicle, to reduce its environmental impact without compromising performance, safety or consumer acceptability. This paper describes the Purdue team's control development process for the EcoCAR 2 competition.

MIT Lincoln Laboratory is tasked by the U.S. Federal Aviation Administration to investigate the use of the NEXRAD polarimetric radars* for the remote sensing of icing conditions hazardous to aircraft. A critical aspect of the investigation concerns validation that has relied upon commercial airline icing pilot reports and a dedicated campaign of in situ flights in winter storms. During the month of February in 2012 and 2013, the Convair-580 aircraft operated by the National Research Council of Canada was used for in situ validation of snowstorm characteristics under simultaneous observation by NEXRAD radars in Cleveland, Ohio and Buffalo, New York. The most anisotropic and easily distinguished winter targets to dual pol radar are ice crystals.