INTEGRATION BETWEEN PRODUCT DESIGN AND SUPPLY CHAIN WITH CONSIDERATION FOR SUSTAINABILITY
Open Access
- Author:
- Olson, Elizabeth Christine
- Graduate Program:
- Industrial Engineering
- Degree:
- Master of Science
- Document Type:
- Master Thesis
- Date of Defense:
- None
- Committee Members:
- Gul Kremer, Thesis Advisor/Co-Advisor
Gul Kremer, Thesis Advisor/Co-Advisor - Keywords:
- supply chain
design
sustainability
carbon footprint - Abstract:
- Sustainability and carbon footprint (CF) reduction are becoming increasingly important concepts for companies to incorporate into their business practices. More consumers are aware of their impact on the environment and are pressuring companies to produce sustainable products that have a lower carbon footprint. Given that the international average CF caused by manufacturing products in 2001 was 13% of the entire CF, and the fact that consumers purchase more manufactured goods in wealthier nations, efforts towards producing more sustainable products are prime areas for concentration. It is anticipated that the government will impose cap and trade restrictions on greenhouse gas (GHG) emissions to keep the pollution from companies regulated. Some companies are trying to record and cut back on their GHG emissions before any laws are enacted so that they are less likely to incur the possible fines, or more likely to keep and expand their customer base by becoming more “green”. It is important that product design be considered concurrently with the manufacturing of a product and its supply chain. A poorly designed product increases costs for redesign and slows it’s release to consumers. The design stage should consider sustainability of products with additional sustainability criteria. When these criteria are considered early, there is more flexibility to change the product design using parts from various suppliers with minimal cost. This way, businesses can mitigate emissions across the whole supply chain, rather than only in their own plant. The research in this thesis is an extension of a previous dissertation where the author proposed a graph-theory based optimization approach for simultaneous optimization of product and supply chain design. The previous dissertation used Design for Assembly (DfA) criteria to initially order 64 different concepts of bicycles from easiest to hardest to assemble. It chose the best scoring DfA concept and created a model with an objective function to minimize the total cost of processing, transportation and inventory for the finished bike concept. The model accomplished this objective by choosing which supplier would be used for each bicycle component. This thesis extends the prior work to include the consideration of cradle to gate manufacturing processes to improve sustainability. The product is examined from the manufacturing stages of the parts, to the full assembly of the finished product before it is shipped to a warehouse, store or consumer. It also adds CF as an additional criterion with relevance to: (1) the way in which the product is processed, (2) the material from which the product is made, and (3) the transportation type and distance that the product must be shipped to its final destination. Each of these criteria is measured in the amount of CO2 equivalent gases emitted and is included in the product optimization. The modified model was run: (1) as a minimization problem for single objectives, (2) with an equal weighted objective, (3) with a non-preemptive multiple objective, and (4) as a single objective maximization. Since each of the objectives of cost, lead-time, and carbon footprint are dependent on each other, this brings about an unavoidable tradeoff situation. Results for all of the runs are shown as well as the components, modules, and suppliers according to the model results. As a general trend, when one objective is low, the others will be low as well. Conversely if an objective is very high, the others will be on the high end too. This model should serve as an example for companies to use on their own products to regulate cost, lead-time, and CF simultaneously and choose the best suppliers and components.