Changing Paths: The Impact of Manufacturing Offshore on Technology Development Incentives in the Optoelectronics Industry

This paper presents a case study of the impact of manufacturing offshore on the technological trajectory of the firm and the industry. It looks in particular at the optoelectronics industry. The paper uses a combination of simulation modeling and qualitative research methods to develop grounded theory. The results suggest that firms face an important dilemma. In the case of optoelectronic firms, they are able to reduce short-term costs by manufacturing offshore; however, manufacturing offshore creates a combination of cost and knowledge constraints which limit the firms’ ability to pursue critical innovations. These results are also of interest to those concerned with trade policy. The interest here is two fold. First, the optoelectronics industry is of strategic importance in the evolution of industrial technology and thus is important to national policy. The paper’s principal finding that manufacturing offshore reduces incentives for innovation raises serious questions about the appropriateness of an offshore manufacturing policy in the long run. Second, the case challenges more generally conventional theories of trade, particularly their underlying assumptions about the long term dynamic effects which work through technological change. This case raises the troublesome question of whether these effects might be generally perverse and reduce or possibly eliminate the gains from trade over the long term

Design for Location: The Impact of Manufacturing Offshore on Technology Competitiveness in the Optoelectronics Industry

Atlanta Conference on Science and Innovation Policy 2009This presentation was part of the session : Globalization of Science and InnovationM.I.T. Microphotonics Cente

Modeling methods for complex manufacturing systems : studying the effects of materials substitution on the automobile recycling infrastructure

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Materials Science and Engineering, 1999.Includes bibliographical references (p. 237-241).Classically, technical cost models have been constructed using commercial spreadsheet problems. Spreadsheets, however, are not well suited to construct models of industrial systems, especially those where variable configurations of operation steps arc of interest. In light of this, a methodological framework and complementary computer tool were developed to address the existing impediments to system modelinb. This tool parametrizes the components of a system model and of spreadsheet based TCMs. Here, parametrization means creating both data structures which describe each system part and procedures which emulate the behavior and interrelationship of those parts. Using this strategy, a tool was created which successfully permits definition and manipulation of any real configuration, ensures consistent application of model formulae, provides a mechanism for appropriate and conveniently audited linking of variable values, and affords extensive auditing. This modeling tool was applied against a real-world case study of the automobile recycling infrastructure. For this system, concerns exist regarding how it will sustain as vehicles continue to decline in mass and change in composition. To reveal this, a process-based cost model of the automobile recycling system was created and used to I) expose retiring fleet compositions which pose a problem for recyclers and 2) evaluate strategies for using the system's waste, automobile shredder residue (ASR). The system model was run against retired fleets made up of three vehicles: predominantly steel, aluminum intensive, and polymer composite intensive (CIV). Results indicated that the current recycling system maintains profitability except when presented with a 100% CIV fleet. Also, the material value within a vehicle containing an aluminum structure, closures, chassis, and engine block would be sufficient to prompt extensive dismantling, consuming the bulk of the shredder's feedstock. For a similar vehicle without the aluminum chassis, shredders would have to offer 18¢/kg. for hulks, to preserve their profitability. Of the ASR processing technologies investigated, pyrolysis seems the most promising. Pyrolysis achieves profitability at a landfill price of $50/ton. In contrast, mechanical separation and selective precipitation require landfill prices of$70/ton.by Randolph E. Kirchain Jr.Ph.D

Quantifying the effects of product family decisions on material selection: A process-based costing approach

Product designers must continually assess trade-offs among various performance attributes and cost. Materials choice can play an important role in that decision-making process. Product platforms are used to meet the demand for increased product variety, while also managing costs. Because of their interdependent effects, it is possible that platforming strategies may alter preferred material choice. This paper examines the interrelationship of these early stage design choices through the application of process-based cost modeling. A case study is detailed concerning two alternative material options for an automotive instrument panel beam: a die-cast magnesium design and a conventional design (i.e., discrete stamped steel components) which allows for more component sharing than the integrated magnesium design. The effects of component sharing on product family costs are analyzed. It is shown that the magnesium design is less competitive in platformed scenarios.Materials selection Cost Automobile Case study Product families

Analyzing uncertainty in a comparative life cycle assessment of hand drying systems

Purpose: The goal of this study is to evaluate and compare the environmental impact (with a focus on global warming potential) of five hand drying systems: hands-under (HU) dryers, high-speed hands-under (HSHU) dryers, high-speed hands-in (HSHI) dryers, cotton roll towels, and paper towels. Another objective is to incorporate uncertainty into this comparative life cycle assessment (LCA) as a means of understanding the statistical robustness of the difference between the environmental impacts of the hand drying systems. Methods: We conducted a life cycle assessment in accordance with the ISO 14040/14044 standards using data primarily from publicly available reports. As part of the study, we performed a parameter uncertainty analysis for multiple scenarios to evaluate the impact of uncertainty in input data on the relative performance of products. In addition, we conducted a probabilistic scenario analysis of key drying system parameters in order to understand the implications of changing assumptions on the outcomes of the analyses. Results and discussion: The scope of the analyses enabled us to draw robust conclusions about the relative environmental performance of the products. We can say with a high degree of confidence that the high-speed dryers have a lower impact than paper towels and cotton roll towels. Differentiating the performance of the hand dryers requires being more specific about framing assumptions. Under certain conditions, the HSHI dryer is expected to have a lower impact than the HU and HSHU dryers. However, under other conditions, one cannot say that the HSHI dryer is clearly better than the other dryers. We cannot differentiate the performance between the HU dryer, cotton roll towels, and paper towels. Conclusions: This work demonstrates the importance of going beyond traditional uncertainty analyses for comparative LCAs that are used for assertions of relative product environmental impact. Indeed, we found instances where the conclusions changed as a result of using the probabilistic scenario analysis. We outline important elements that should be included in future guidance on uncertainty analyses in comparative LCAs, including conducting parameter and scenario uncertainty analyses together and then using the outcomes to guide selection of parameters and/or choices to analyze further.Dyson (Firm

Is Economic value an Effective Proxy for Embodied Energy and Environmental Impact in Material Systems?

This paper uses economic value metrics to evaluate the retention of value of secondary materials and provides a framework for characterizing value throughout a material and product life-cycle. These economic value metrics are compared with analogous life cycle assessment metrics in order to determine the conditions under which economic value effectively represents environmental impact for EoL material recovery decision-makers. A comparison of these metrics using several different material types indicates that there is a strong correlation between LCA metrics and economic value metrics for most of the materials studied. However, there were a few cases in which the economic value metrics were poor indicators of the LCA metrics

Supply and demand in the material recovery system for cathode ray tube glass

This paper presents an analysis of the material recovery system for leaded glass from cathode ray tubes (CRTs). In particular, the global mass flow of primary and secondary CRT glass and the theoretical capacities for using secondary CRT glass to make new CRT glass are analyzed. The global mass flow analysis indicates that the amount of new glass required is decreasing, but is much greater than the amount of secondary glass collected, which is increasing. The comparison of the ratio of secondary glass collected to the amount of new glass required from the mass flow analysis indicates that the material recovery system is sustainable for the foreseeable future. However, a prediction of the time at which the market for secondary glass will collapse due to excess capacity is not possible at the moment due to several sources of uncertainty

A Methodology for Robust Comparative Life Cycle Assessments Incorporating Uncertainty

We propose a methodology for conducting robust comparative life cycle assessments (LCA) by leveraging uncertainty. The method evaluates a broad range of the possible scenario space in a probabilistic fashion while simultaneously considering uncertainty in input data. The method is intended to ascertain which scenarios have a definitive environmentally preferable choice among the alternatives being compared and the significance of the differences given uncertainty in the parameters, which parameters have the most influence on this difference, and how we can identify the resolvable scenarios (where one alternative in the comparison has a clearly lower environmental impact). This is accomplished via an aggregated probabilistic scenario-aware analysis, followed by an assessment of which scenarios have resolvable alternatives. Decision-tree partitioning algorithms are used to isolate meaningful scenario groups. In instances where the alternatives cannot be resolved for scenarios of interest, influential parameters are identified using sensitivity analysis. If those parameters can be refined, the process can be iterated using the refined parameters. We also present definitions of uncertainty quantities that have not been applied in the field of LCA and approaches for characterizing uncertainty in those quantities. We then demonstrate the methodology through a case study of pavements

Selection of Lightweighting Strategies for Use Across an Automaker's Vehicle Fleet

Vehicle lightweighting, or mass reduction, via materials substitution is a common approach to improve fuel economy. The many subsystems in a vehicle, choices of materials, and manufacturing processes available, though, lead to numerous paths to achieving the mass reduction and identifying the best ones for an automaker to implement can be a challenge. In this paper, that challenge is addressed through the development of a selection model designed to inform the lightweighting strategy decision for an automaker's fleet. The model, implemented with a genetic algorithm, identifies the strategies that enable an automaker to optimize the net present value of its cash flow, as well as to meet its CAFE obligations over the coming years. A case study of various strategies implemented in three vehicles over a three-year timeframe is used to demonstrate application of the genetic algorithm selection model and contrast it to an alternative period-by-period search implementation