Purpose -This research was conducted to study benefits of a concept, known as lean manufacturing, which elicits organizations to do more with less effort, time, space, and equipment by eliminating waste. Because lean implementation involves finances, dedication, and cultural change in business, there is a need to assess a company's lean initiative. Design/methodology/approach -A comprehensive lean assessment tool is designed targeted for use by manufacturing companies. Research of lean principles and practices was conducted through lean organizations, trade publications, manufacturing web sites, professional articles, textbooks, lean exhibitions, and non-profit lean organizations. Findings -This led to the development of a lean survey questionnaire delivered to 143 lean companies and lean consultants for authentic input. Based on the response, survey participation met a goal of 95 percent accuracy with 15 percent error. Completed surveys were compiled and analyzed for fundamental practices of lean organizations. Answers to the survey were assigned numerical values based on lean significance, and a lean assessment model was developed based on Excel. The lean assessment model was fine-tuned and programmed to output a numerical and descriptive lean assessment grade. It was tested for soundness by inputting mock lean and traditional company answers into the model. Output results from the model correlated with the input. Originality/value -Lean thinking philosophy and lean manufacturing methods and principles were exhaustively researched to make a successful lean organization. The research led to the development of a visual indicator, the Lean Thinking Management Wheel. This model to assess lean thinking manufacturing initiatives unique and has a great potential to use industry wide.

An effective least squares support vector machine (LS-SVM) based approach was developed to predict the surface roughness in machined surface. The real AISI4340 steel and AISID2 steel data set was used to conduct the experiments. The analysis of variance (ANOVA) was used to validate the assumption of normal distribution, as well as the independent distribution of the errors. For the neural networks model, with 70%, 15%, and 15% of data as training, validation, and testing data, the best validation error is 0.0097343. The training error is 9.08888e-4 and the testing error is 1.09510e-1 accordingly. NN methods also discovered the correlation between the predicted surface roughness (Ra) and the actual surface roughness in the form of predicted Ra ~= 0.41*Actual Ra + 0.2. The LS-SVM performance was also compared to the analysis of variance (ANOVA) method, and neural networks model trained by Levenberg-Marquardt algorithm. The experimental results showed that the proposed LS-SVM algorithm produced a determination coefficient of D = 0.9439, which is higher than the ANOVA and NN results of 0.1917 and 0.7266.

Purpose – The purpose of this paper is to develop a tool design for assembly and disassembly using rating factors. Design engineers need an automated tool to effectively analyze the ease of assembly and disassembly of the products or subassemblies. A good assembly design helps in easier disassembly and thus makes it easier to service, repair and maintain. Reuse and recycling aspects are given importance in the present days due to environmental regulations. Designers now use the life cycle design of the products. This creates an environment for the successful application of design for manufacturing, assembly and disassembly tools. This paper addresses some of those issues. Design/methodology/approach – The analysis of a product design for ease of assembly/disassembly depends largely on whether the product is to be assembled/disassembled manually, with automation or a combination of these. For example, the criteria for ease of automatic feeding and orienting are much more stringent than those for manual handling of parts. The new design for assembly/disassembly (DFA/DFD) evaluation tool explained here enables the designer to review the existing design. This paper examines the existing techniques in the area of DFA/DFD and suggests a new methodology based on rating factors. Excel is used to create the interface for the user. Other popular methods were examined such as Boothroyd-Dewhurst, Lucas. Access, reuse, removal, tool, task and time method and assembly score method (Poli) were used as a base for this study. Findings – The end result of this research is a new approach linked to assembly/disassembly rating score. Originality/value – The new DFA/DFD evaluation tool enables the designer to review the existing DFA and DFD difficulties.

It is suggested by many scholars that if the goal of engineering education is to produce engineers who can critically design and create, then providing students with early opportunities to engage in creative engineering design is important. While basic design is focused on the development of new products for the individual, working towards a more sustainable world demands greater attention to designing for and with communities. Improving design education and examining design-learning outcomes requires a kind of targeted approach that could match the best practices to personalize student learning. Design is complex and design includes balancing the needs of multiple stakeholders. However, there is a gap in the preparation of design education that will be needed in a challenging environment. This paper reviews the history of design thinking in the engineering curriculum. Design thinking education starts with an understanding of its importance with socioeconomic relevance. Through observation and empathy, mapping the designer uses the listening and learning tools for mapping users unarticulated needs, working in a team environment. The designer takes time to think carefully why a certain project is considered and details which aspects of machine learning application can be applied from functional to complete success for the end users. The availability of powerful virtual reality methodologies, have made it possible to consider the realistic needs and visualize scenarios and to explore the design alternatives with new ideas before full scale resource allocation on new ideas. Mid-to-advanced level courses with experimental assignments require that students apply through experimentation the principles and concepts learned in foundation courses. The basic design tools such as axiomatic thinking, theory of inventive problem solving, design iteration and simulation using hardware-in-the loop are discussed with case studies. Consideration of product sustainability with the thoughts of design for disassembly and disposal has emerged as a major part of design thinking. Senior engineering courses center on cross and interdisciplinary design and capstone experiences so that students experience fully guided practice of device design and problem solving, simulating what they are likely to experience in the world. This paper examines the critical issues of design thinking in a curriculum from observation, empathy mapping, validation of the idea, and improvement of idea by virtual reality and machine learning, optimization of the idea by tools such as axiomatic design, hardware in the loop simulation, and finally examining product sustainability causes.

Increasing balance confidence in older individuals is important towards improving their quality of life and reducing activity avoidance. Here, we investigated if balance confidence (perceived ability) and balance performance (ability) in older adults were related to one another and would improve after balance training. The relationship of balance confidence in conjunction with balance performance for varied conditions (such as limiting vision, modifying somatosensory cues, and also base of support) was explored. We sought to determine if balance confidence and ability, as well as their relationship, could change after several weeks of training. Twenty-seven healthy participants were trained for several weeks during standing and walking exercises. In addition, seven participants with a higher risk of imbalance leading to falls (survivors of stroke) were also trained. Prior to and after training, balance ability and confidence were assessed via the Balance Error Scoring System (BESS) and Activities Specific Balance Confidence (ABC) Scale, respectively. Both groups showed improvements in balance abilities (i.e., BESS errors significantly decreased after training). Balance confidence was significantly higher in the healthy group than in the stroke group; however, ABC results reflected that balance confidence did not significantly increase after training for each. The correlations between balance ability and balance confidence were explored. Encouragingly, healthy participants displayed a negative correlation between BESS errors and ABC (i.e., enhancements in balance confidence (increases in ABC Scale results) were related to improvements in balance ability (decreases in BESS errors)). For the stroke participants, despite improvements in balance ability, our results showed that there was no relation to balance confidence (i.e., no correlation between BESS errors and ABC) in this group.