Aggregate production process design in global manufacturing using a real options approach

A computer aided engineering system for development of catalytic processes

In today’s economy, new technologies rapidly emerge in the durable goods market. Therefore, it is paramount for manufacturing companies to optimize product introduction time for their second-generation product (SGP), which is an upcoming product in the production line, when profitability is at stake. The main factors affecting this timing are technology advancements and changes in customer tastes, which make determining an optimal introduction time for a product a challenging task. The main goal of this research is to find the optimal product introduction time for the SGP that maximizes the net present value (NPV) over a given period while product life cycle (PLC), pricing, and advertising are explicitly being taken into consideration. Demand for each product contains two regimes life cycle, and each regime is defined by a geometric Brownian motion (GBM). Each GBM has a drift rate and volatility. Moreover, there is a correlation between different regimes for different products. Correlated GBMs are discretized using a lattice approach. The Bass model is used to determine demand parameters including drift, volatility, and correlation, while dynamic programming is used to optimize NPV. Flexibilities, such as expansion, contraction, and switching, are identified between two products. Examples are provided to show the applicability of the developed models. Accordingly, the results show as the drift rate, volatility, and initial demand for a first-generation product (FGP) increase, the SGP introduction time has to be delayed. Furthermore, results demonstrate that in decreasing pricing policy, the SGP has to be introduced as early as the FGP. In increasing-decreasing pricing policy, as the increasing pricing rate is increasing, the SGP introduction time is delayed. When the advertising budget percentage increases, the NPV increases up to a certain level and then it will be saturated. Major contributions of this thesis are as follows: first, investigating the product introduction time by integrating marketing and manufacturing aspects; second, developing a model to incorporate the flexibility and production cost of the system for determining the optimal product introduction time. Third, the value of the product introduction time is expressed in terms of dollar value and this would help managers to make decisions easily. The models developed in this research can be used as practical tools for manufacturers to find the optimal product introduction time (PIT) and also the research can be used as a guideline to introduce the second-generation PIT.

In order to attain the true integration of computer-aided design and computer-aided manufacturing not only is a smooth flow of information required, but also decision making for both product design and process design must be synthesized. In this paper an integrated design process is proposed in which decisions concerning both product design and process design are simultaneously made. According to the proposed design procedures, an integrated optimization problem is formulated. This optimization is expressed as a multiobjective optimization problem which produces many Pareto optimum solution sets corresponding to combinations of materials used for parts. The algorithm for solving the problem is also presented. The proposed method is applied to designing a cylindrical co-ordinate robot, thereby demonstrating the effectiveness of conducting a simultaneous process through product design and process design.

Biomass utilisation is identified as a promising solution to minimise society’s dependency on fossil fuels for energy generation. By employing the concept of integrated biorefinery, biomass can be converted into power, heat and value-added products in a sustainable and efficient way. To date, biomass can be converted into a spectrum of products with the availability of various biomass conversion pathways. Due to the substantial amount of potential products and conversion technologies, design of chemical products and processing routes in integrated biorefinery has become more challenging. Furthermore, consumer-driven chemical product design has gained magnificent attention in chemical industry, owing to the shifting of market from commodity products to high-value-added products. As a result, the task of chemical product design that is traditionally dedicated to chemists has nowadays become a multifaceted process that requires collective efforts from various fields. In this work, a framework is proposed to facilitate the decision-making involved in the overall chemical product design and production process by integrating four major organisational units of an enterprise: corporate unit, business unit, research and development (R&D) unit and production unit. The corporate unit is responsible for the enterprise goal line setting for the entire chemical product design and production process, the business unit performs detailed analysis on the existing market, the R&D unit is in charge of the design of chemical product that fulfils the customers’ needs while the production unit produces the chemical product. As a whole, the cooperation between these major organisational units of an enterprise design product that fulfils product needs, determines conversion pathways to produce the product from biomass and identifies product demand and price while fulfilling the enterprise goals. To illustrate the proposed methodology, a case study on the design of dry-cleaning solvent from palm-based biomass is presented.

Enterprise design is embodied by the notion of integrating the processes of product design, manufacturing process design, and organization design to enhance manufacturing competitiveness. However, because of cognitive and computational limitations, the integration of the enterprise design activities based on large and complex enterprise models is not efficacious. In this paper, we show how to achieve an efficacious integration by promoting a common decision support model across the enterprise and using approximate-cooperative formulations of individual design decisions. The preliminary embodiment of a flywheel produced in a forging process is used to illustrate this perspective.

This work addresses the optimum design of a phosphoric acid (PA) production process under uncertainty, both from an economic and environmental perspective. A design and optimization framework is employed that utilizes generic process modules to enable systematic process flowsheet development and to facilitate interconnectivity among the utilized processing components. This is coupled with a systematic method of incorporating uncertainty into the process design and optimization, hence, enabling a realistic representation of industrial conditions during the PA process design stages. The integrated design of PA production processes and downstream phosphogypsum utilization processes is further proposed, in the form of the Ammonium Sulfate (AS) production process, as a means of mitigating the environmental impact of the PA production process associated with phosphogypsum. The case studies, presented to illustrate the proposed developments, highlight the significant impact of considering uncertainties in the design of optimum PA process schemes as well as generate useful insights regarding the synergies developed in the integrated PA and AS process design.

The real options approach has been used within environmental economics to investigate the impact of uncertainty on the optimal timing of control measures to minimise the impacts of invasive species, including pests and diseases. Previous studies typically model the growth in infected area using geometric Brownian motion (GBM). The advantage of this simple approach is that it allows for closed form solutions. However, such a process does not capture the mechanisms underlying the spread of infection. In particular the GBM assumption does not respect the natural upper boundary of the system, which is determined by the maximum size of the host species, nor the deceleration in the rate of infection as this boundary is approached. We show how the stochastic process describing the growth in infected area can be derived from the characteristics of the spread of infection. If the model used does not appropriately capture uncertainty in infection dynamics, then the excessive delay before treatment implies that the full value of the option to treat is not realised. Indeed, when uncertainty is high or the disease is fast spreading, ignoring the mechanisms of infection spread can lead to control never being deployed. Thus the results presented here have important implications for the way in which the real options approach is applied to determine optimal timing of disease control given uncertainty in future disease progression.

Production process design is a critical stage in product development to ensure time and cost efficiency. This study designs the production process of an adjustable study chair intended for elementary school students. The approach includes process modeling using an Operation Process Chart (OPC), cost estimation with the full costing method, and process flow simulation using Promodel. The OPC reveals 27 operation activities and 20 inspections required to assemble one unit. The total production time recorded is 1 hour and 34 minutes. The estimated production cost per unit is IDR 515,806, covering raw materials, labor, machinery, and overhead. Simulation results indicate workload imbalance at the assembly station, which may become a production bottleneck. These findings serve as a basis for improving work scheduling, resource allocation, and overall production efficiency

The recent joint issue of the American Journal of Public Health and the American Journal of Preventive Medicine highlighted the potential of integrating public health and primary care. The key message of this issue is that this integration is promising, timely, and urgently needed in order to measurably improve the US community's health in the 21st century. At the same time authors tempered their expectations. Multiple, promising-though often unsustainable-attempts have been made in the past.(1) (Am J Public Health. Published online ahead of print August 16, 2012: e1. doi:10.2105/AJPH.2012.300977)

In this work, alternative evaporation processes for PLA production were designed with economic assessment. The suggested processes are the multiple-effect evaporation (MEE) process and thermal vapor recompression (TVR)-assisted evaporation process. First, the MEE process can efficiently reuse waste heat by additional column installation, thereby reducing the steam energy consumption. The proposed MEE process involves five columns, and after the evaporation in each column, the waste heat of the emitted vapor is reused to heat steam in the reboiler of the next column. Second, the suggested TVR-assisted evaporation process utilizes an additional steam ejector and recovers waste heat from the emitted vapor by increasing the pressure using high-pressure driving steam at the steam ejector. Each alternative process was modeled to predict the steam energy consumption, and to determine the cost-optimal process; the total annualized cost (TAC) of each alternative process was calculated as evaluation criteria. In the simulation results, the alternative processes using MEE and TVR reduced the steam consumption by 71.36% and 89.97%, respectively, compared to the conventional process. As a result of economic assessment, the cost-optimal process is the alternative process using TVR and the TAC can be decreased by approximately 90%.

The number of products benefiting from micro components in the market is increasing, and consequently, the demand for well-matched tools, equipment and systems with micro features is eventually increasing as well. During the design process of micro products, a number of issues ap- pear which are inherent due to the down scaling or physical phenomena dominating in the micro range but negligible in the macro scale. In fact, some aspects in design for micro manufacturing are considerably different compared to the de- sign procedure taken at the macro level. Identifying the differ- ences between design considerations at micro compared to macro scale, and defining potential guidelines based on them, provides an opportunity to modify the conventional design methodologies towards becoming micro specific. In this pa- per, the need for a micro-oriented approach for designing mi- cro products which has not been investigated hitherto studied. For this purpose, an additional step named "Rules To Consider" (RTC) is added to the conventional design method- ologies.Thisstepisconstituted based onthe feedbacks gained during analyzing the different iterations of the design. The knowledge obtained during the design process of a micro product can be added to the RTC unit, and this unit becomes enriched progressively in design process of similar micro products and supplemented to the conventional design meth- odologies to be served as a micro-oriented design methodol- ogy. Inorder to present the application ofRTC unit, the design process of a micro heat exchanger is investigated. Manufacturability and functional performance are considered as evaluation criteria, and the lessons learned from each de- sign iteration and evaluation are employed in the subsequent design proposals until an acceptable design is achieved. Thermal performance of the heat exchangers is evaluated using finite element (FE) simulation of the conjugate heat transfer. The design proposals are optimized in terms of geo- metricaldimensions,andasensitivityanalysisisconductedon the mass flow rate and heat generation power in the heat source. Finally, the designs with higher thermal performance and manufacturability are introduced. The result of the ther- mal analysis reveals the fact that the presence of the fins and modification of their dimensions as well as the constituent material for fabricating the micro heat exchanger do not sig- nificantly improve the thermal performance of the micro heat exchangers. This is an interesting outcome which can result in considerable reduction of the manufacturing costs by simpli- fying the geometrical design of the heat exchanger. The micro-specificdesignconsiderationswhich are extracted from the design process of the micro heat exchanger are added to the RTC unit and can be applied as guidelines in design pro- cess of any other micro heat exchanger. In other words, the current study can provide a useful guideline in design for manufacturing of micro products.

Design for manufacturing and assembly (DfMA) has been widely applied to support the decision-making process in offsite construction. With a DfMA approach, cost estimation requires taking product design and production processes into consideration. Current studies conduct cost estimation built upon quantity take-offs. However, they do not provide a vocabulary to relate cost estimates to offsite construction processes. This paper presents a new domain ontology, Offsite Housing Ontology (OHO) using the NeOn methodology framework to support cost estimation considering products, resources, and production processes. OHO semantically defines offsite construction domain terminology and relationships. This supports a unified model, required for efficient collaborative design management. The efficiency and effectiveness of the OHO approach are demonstrated in a real-world DfMA scenario through the development of a Knowledge-Based Engineering tool to automate cost estimation. The approach can be adapted and extended to accommodate a very wide range of offsite housing, delivering important optimization and automation benefit from DfMA solutions.

An industrial example of FE supported development of a new product

Electronic Manufacturing Services (EMS.) companies are in a highly competitive environment where investment in technology plays a significant role in the company's performance. The equipment efficiency is directly converted to revenue. The equipment efficiency decays over time; keeping the equipment represents a loss in productivity, and renewing the equipment requires an additional cost. There is a continuous decision process to determine the optimal time to replace the old equipment with a new one. Traditionally, the optimal time to renew is when the machine's revenue matches the cost. This paper studies the renewal decision using a real options approach, adding the uncertainty factor. The variables are modeled as Geometric Brownian Motions. We provide a literature review of renewal real options and describe the models we use. The one-factor model considers the revenue as stochastic; the two-factor model considers the revenue and cost as stochastic; the technological improvement models extend the two-factor model to include a premium in revenue for replacing the equipment. An overview of the electronic manufacturing dynamics is described; we select a product whose manufacturing process depends on machines. We provide a methodology for the model's implementation and how to determine the parameters; the results are compared to the deterministic approach. Finally, we discuss the models' advantages, disadvantages, and limitations.

Identification in a Duopoly: A Real Options Approach