Moulded pulp is a paper‐based packaging solution that is fully biodegradable and has been growing in demand due to environmental considerations. While demand has been growing, many moulded pulp packaging designs are based on the experience and knowledge of the package designer, which can lead to avoidable design issues. To solve this issue, this paper introduces a moulded pulp packaging design method using topology optimization. Topology optimization provides a systematic way to find the conceptual optimum design by minimizing strain energy. Taking the results of the topology optimization and implementing a superimpose method, the design process can be more efficient than the conventional design method. As a result, the proposed method provides a design that reduces the maximum stress of the packaging structure. With the reduction in stress, an exhaustive search method is then used to reduce the thickness of the package to decrease material usage while maintaining stress reduction.
Packaging has an important role in protecting products during the distribution process. Therefore, it is essential for the packaging designer to evaluate the packaging even after the design implementation. While every new packaging design needs to go through a series of physical tests to ensure it delivers the product to the customer safely, it is not uncommon to encounter packaging failures after the design implementation. Redesigning a completely new package and redoing these tests is very expensive and a time‐consuming process. Therefore, an alternative evaluation method is needed to enhance efficiency while maintaining evaluation quality. The main purpose of this paper is the evaluation of package performance during distribution using customer reviews. Sentiment analysis (SA) is implemented to identify the positive or negative sentiment from customer reviews. Moreover, the proposed method utilizes an in‐house library containing packaging related words (Pack‐List) to identify the reviews concerning the packaging. As a result, this method provides a systematic approach to detect problems by analysing customer reviews as feedback to a defective packaging product. By using the results of SA with Pack‐List, a percentage of negative and positive reviews are calculated to examine the packaging performance during distribution. Then, the percentage of failure over various months and years is examined to identify how time affects the packaging failure. Next, a word cloud of negative sentences is created to show the most mentioned issue. With the proposed method, packaging designers can identify packaging problems in the early stages and keep track of the packaging performance.
In this paper, a non-probabilistic based topology optimization method under an external load uncertainty is presented. In traditional topology optimization problems, external loadings that apply to structures are always assumed as deterministic, but an external loading with uncertainties is very common in many practical engineering applications. In this paper, load uncertainty is described as an unknown-but-bounded model and the maximum possible strain energy based topology optimization formulation under an uncertain load is solved for the worst case condition. This optimization problem can be rewritten as a two-level optimization problem: the upper level optimization problem is a deterministic topology optimization under a critical loading of the worst structure response, and the lower level optimization problem is to determine the critical loading corresponding to the worst structure response. The challenge of the lower level optimization problem is on its non-convexity which makes many gradient based search methods ineffective. To overcome this issue, the lower level optimization problem is reformulated based on the KKT optimality conditions as an inhomogeneous eigenvalue problem and is solved for the critical loading corresponding to the worst structure response. After the worst loading case is identified, the upper level problem can be solved through the existing gradient based optimization algorithms. The effectiveness of the proposed topology optimization under unknown-but-bounded external loading uncertainty is demonstrated through a few numerical examples.
The Life Cycle Assessment (LCA) is a method to measure the environmental impact of a product’s life stages from the cradle to the grave, and is widely used for packaging sustainability. Although many successful applications using LCA have been reported, the current state of LCA tools still has many limitations. For example, it is difficult to select the best design among the LCA results of design sets. Moreover, the LCA tool cannot implement a decision maker’s preference into the process easily. To overcome these limitations, we developed a decision making tool using LCA for packaging sustainability. First, Pareto Active Set Selection (PASS) method is proposed to find Pareto Front of packaging options. Additionally, Design Preference Function (DPF) is introduced to implement the designer’s preference for selecting the best packaging options. Case studies are presented to demonstrate this decision making tool.
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