Platform Planning Research Articles

Distribution of Blood Glucose and Prevalence of Diabetes Among Centenarians and Oldest-Old in China: Based on the China Hainan Centenarian Cohort Study and China Hainan Oldest-Old Cohort Study

Importance: There was little data on the distribution of blood glucose levels and diabetes prevalence for centenarians and the oldest-old. Objective: The aim of this study is to analyzed the distribution of blood glucose and diabetes prevalence for centenarians and oldest-old in China:Based on the China Hainan Centenarian Cohort Study (CHCCS) and China Hainan Oldest-old Cohort Study (CHOCS). Design, setting and participants A total of 1002 centenarians and 798 oldest-old were enrolled from 18 cities and counties in Hainan Province (one of the longevity provinces). Main Outcomes and Measures: The fasting blood glucose was tested and prevalence of diabetes was calculated. Results: The average age of centenarians was 102.77±2.55 years old, 82.0% were women. The average age of the oldest-old was 84.99±4.01 years old, 59.9% were women. The average blood glucose of centenarians was 5.12±1.44mmol/L and 4.80±1.27mmol/L, and more than 70% were between 3.00mmol/L and 5.99mmol/L. There was no statistical difference between different genders and age groups. A total of 9.5% of centenarians had diabetes and 8.1% had IFG. A total of 11.4% of the oldest-old had diabetes and 4.4% had IFG. Abdominal obesity and TG levels may be associated with diabetes prevalence. The corresponding ORs were 1.517(1.083-2.125) and 1.473(1.089-1.943) respectively of abdominal obesity among centenarians and the oldest-old respectively, and corresponding ORs 1.182(1.081-1.316) and 1.162(1.009-1.699) respectively of abdominal obesity among centenarians and the oldest-old respectively Conclusions and Relevance: In summary, the results based on CHCCS with the largest sample among centenarians and CHOCS showed that the blood glucose level and the prevalence of diabetes were at a lower level than those of adults or younger elderly. Funding Statement: This work was supported by National Natural Science Foundation (81703285,81773502,81703308), Beijing Nova Program (Z181100006218085), Excellent youth project (2018-yqpy-003); 3+1 project; National Clinical Research Center for Geriatrics Diseases（NCRCG-PLAGH-2017017）,Medical big data research project of PLA General Hospital (2018MBD-029, 2018MBD-030); National key research and development project (2016YFC1303603, 2018YFC2000400); National Science and technology resource sharing service platform plan project (YCZYPT[2018]07) Declaration of Interests: The authors declare that there is no duality of interest associated with this manuscript. Ethics Approval Statement: This study was approved by the Biomedical Ethics Committee of Chinese PLA general hospital, and written informed consent with signature or fingerprint was obtained from each respondent.

Disaster prevention platform plan by AI

Disaster prevention platform plan by AI

Information architecture for the implementation of a technological platform that manages research production in higher education institutions

Scientific communication and diffusion is one of the challenges of higher education institutions, related to the implementation of strategies of free access to the scientific and technological productivity of the teachers and researchers of the institutions, which allow to increase the visibility and impact of the research, for which a model of information architecture of the technological platform for the management of the investigative production of teachers and researchers was designed, under an environment focused on satisfying the information needs of the users that allows to organize, to group and to visualize the information by means of metadata. The research is of exploratory-descriptive type, through which the products of science, technology and innovation that should be visible in the technological platform were identified, generating as a result an architecture model-view-controller, with data storage in a relational database, which has access through a RESTful API made in Java, the views and controllers were made in HyperText markup language and JavaServer pages respectively. MySQL was used as a relational database engine to store information and MYSQL Workbench as a platform for the construction of the relationship model between entities, tables and columns; which will be used as a framework for the design, planning and implementation of the technological platform.

The Mechanism of Mica on Protecting NSAIDs Induced Small Intestinal Mucosal Barrier Injury via ncRuPAR-PAR2 Pathway

Objective: The study was to detect the role of ncRuPAR and Protease activated receptor (PAR)2 in the mechanism of Non-steroidal anti-inflammatory drugs(NSAIDs) induced small intestinal mucosal barrier injury. And to clarify the possible mechanism of mica in treatment NSAIDs induced small intestinal disease. Methods: Caco-2 cells were cultured and divided into 6 groups: control group, diclofenac sodium group, control RNAa group, ncRuPAR RNA activation (RNAa) group, diclofenac sodium + mica group, diclofenac sodium + FSLLRY-NH2 group. 40 μmol/L diclofenac sodium treatment for 24 hours to establish NSAIDs induced small intestinal epithelial cell injury model, 10% mica-containing serum treatment for 24h, 100uM PAR2 blocker FSLLRY-NH2 treatment for 24h. Blank vector or ncRuPAR overexpression vector were transfected into cells for 72h. Then Transwell assay were performed to detect cell permeability, qPCR were used to detect RNA expression of PAR2 and ncRuPAR, and western blot were performed to detect PAR2, occludin and claudin-1 expression. Result: NSAIDs-induced small intestinal epithelial cell injury model was successfully built. Compared with the control group, ncRuPAR and PAR2 were up-regulated, occludin and claudin-1 were down-regulated, cell permeability were increased in diclofenac sodium group (P 0.05). Compared with the control RNAa group, overexpression of ncRuPAR significantly up-regulated the expression of ncRuPAR and PAR2, down-regulated the expression of occludin and claudin-1, and increased cell permeability (P<0.01). Conclusion: When NSAIDs induced small intestinal injury occurs, ncRuPAR activation could up-regulate PAR2, causing the destruction of intestinal epithelial cell tight junction and the increase of intestinal epithelial cells permeability. Mica-containing serum has a similar effect as PAR2 blocker, which could antagonize the above-mentioned damage process and play a role in protecting the mechanical barrier function of the intestinal mucosa. Funding Statement: This research was supported by funding from Zhejiang Provincial Natural Science Foundation of China under Grant No.LY18H030001； the Medicine and Health Science and Technology Plan Projects in Zhejiang province(2017KY413), Traditional Chinese Medicine Science and Technology Plan of Zhejiang Province(2017ZA089, 2016ZB071, 2015ZZ012, 2014ZA030); National Natural Science Foundation of China (81573760);Medical Health Platform Plan Projects of Zhejiang Province (2015RCA020); Zhejiang Provincial Natural Science Foundation of China (LY16H030010). Declaration of Interests: The authors state: There is no conflict of interest. Ethics Approval Statement: Not required.

Platforms planning and process optimization for biofuels supply chain

Sustainable biofuel supply chain is a key to sustainable manufacturing and the future of production. Greener production is now becoming an order qualifier for the global competition. Modeling biofuel supply chains that achieve economic, social, and environmental feasibility is a challenge. This article develops biofuel platform planning and optimization that unifies biofuel product, production process and networks design into an umbrella of sustainable supply chain planning. A design of biofuel supply chain networks under various production paths is considered. The modeling results show that an optimum region of composition ratio between rice straws and waste cooking oils can be set within the range from 0% to 50%. Bio-diesel is favored over ethanol by occupying over 40% of the total biofuel outputs. However, ethanol yield is 99.1% and therefore it is sufficient to be directly mixed with gasoline at final depots. In terms of social contribution, it is estimated that the supply chain contribution to the case country GDP is about 0.17%. Looking at the above statistics, future research on global economic impacts and competitiveness of biofuel production is suggested.

Anti-Suicidal Efficacy of Repeated Ketamine Infusions in Depression with Suicidal Ideation

Background: Suicide is a tremendous public health crisis around the world and is demanded urgent intervention. Most people who die by suicide suffer from some forms of mental illness, especially mood disorders. Previous studies found that Ketamine intervention could rapidly reduce suicidal ideation. The current study is aim to assess the anti-suicidal efficacy of repeated ketamine infusions for Chinese depressed suicidal patients. Methods: In the current study, 112 unipolar and bipolar depressive patients with current suicidal ideation received six ketamine infusions during a 12-day period. Hamilton Depression Rating Scale (HAMD) was measured at baseline, 4 hours and 24 hours after each infusion, two-week naturalistically follow-up. Findings: 59 (53.6%) relief of suicidal ideation (HAMD-SI=0) after first infusion and 71 (73.2%) after six infusions. Anti-suicidal response rate in low SI group were higher than high SI group (F1,1401=56.81, p<0.001). Moreover, anti-suicidal response at 24 hours after first infusion was significant predictor of response at 24 hours after sixth infusion (b=2.263, <0.001). At 24 hours after sixth infusion, correlation between changes in suicidal ideation and depression was 0.32 (p=0.001), accounting for 9.0% in the variance of suicidal ideation change. Interpretation: We confirmed that six repeated ketamine infusions were effective in generating a rapid response of suicidal ideation, with a large sample size. Reductions in suicidal thoughts following ketamine infusions were associated with, but partially independent of, the improvement in depression. Registration Number: (ChiCTR-OOC-17012239) Funding Statement: This work was supported by the National Key Research and Development Program of China (grant number 2016YFC0906300), the National Natural Science Foundation of China (grant number 81801343, 81801345), the International Communication Foundation Science and Technology Commission of Shanghai Municipality (grant number: 16410722500) and Guangzhou Municipal Psychiatric Disease Clinical Transformation Laboratory (grant number 201805010009), Key Laboratory for Innovation platform Plan, Science and Technology Program of Guangzhou, China. The funding source had no role in the study design, analysis or interpretation of data or in the preparation of the report or decision to publish. Declaration of Interests: The authors declare no competing financial interests or potential conflicts of interest. MW was previously involved in a clinical trial on ketamine in treatment resistant depression in collaboration with Janssen Pharmaceuticals (trial identifier: DRK3527). This study was unrelated to the current study and MW declares no conflict of interest. Ethics Approval Statement: The study was conducted at the Affiliated Brain Hospital of Guangzhou Medical University (Guangzhou Huiai Hospital) and approved by local ethics committee.

Data-Driven Platform Design: Patent Data and Function Network Analysis

A properly designed product-system platform seeks to reduce the cost and lead time for design and development of the product-system family. A key goal is to achieve a tradeoff between economy of scope from product variety and economy of scale from platform sharing. Traditionally, product platform planning uses heuristic and manual approaches and relies almost solely on expertise and intuition. In this paper, we propose a data-driven method to draw the boundary of a platform-system, complementing the other platform design approaches and assisting designers in the architecting process. The method generates a network of functions through relationships of their co-occurrences in prior designs of a product or systems domain and uses a network analysis algorithm to identify an optimal core–periphery structure. Functions identified in the network core co-occur cohesively and frequently with one another in prior designs, and thus, are suggested for inclusion in the potential platform to be shared across a variety of product-systems with peripheral functions. We apply the method to identify the platform functions for the application domain of spherical rolling robots (SRRs), based on patent data.

Aquaporins 1, 3 and 8 Expression and Cytokines in Irritable Bowel Syndrome Rats' Colon via cAMP-PKA Pathway

Background: Irritable bowel syndrome (IBS) is one of the most common gastrointestinal (GI) disorders. The cAMP-PKA pathway plays a key role in mediating cell responses to various stimuli both of which might play an important role in IBS. Objective: Our research was to detect the mechanism of IBS rat models via cAMP-PKA pathway so as to further detect the mechanism of IBS. Methods: IBS rats were built by stress and the conditioned stimulus. The study was divided into 3 groups( control group, model group, forskolin group ). The expressions of AQP1, AQP3, AQP8 and CREB(Serl33) in the colon of rats were detected by immunohistochemical technique. The expressions of AQP1, AQP3, AQP8, IL-1β,TGF β and TNF α in the colon were detected by PCR technique. Results: The IBS rats were built successfully. The expressions of AQP1, AQP3, AQP8 and CREB(Serl33) were down-regulated in the colon of IBS rats and were up-regulated with the intervention of the activator of AMP(p<0.05). The expressions of IL-1β TGF β and TNF α were up-regulated in the colon of IBS rats and were down-regulated with the intervention of the activator of AMP(p<0.05). Conclusions: The release of inflammatory cytokines, the activation of the immune system and liquid water metabolic abnormalities are the mechanisms of IBS via cAMP-PKA pathway. Funding Statement: This research was supported by Zhejiang Provincial Natural Science Foundation of China under Grant No.Y18H030008; and the Fund of Medicine and health science and technology plan projects in Zhejiang province (2017179719); Traditional Chinese medicine science and technology plan of Zhejiang province (2017ZA089); Traditional Chinese medicine science and technology plan projects of Zhejiang province (2016ZB071); and National Natural Science Foundation of China (81573760); and Traditional Chinese medicine science and technology plan projects of Zhejiang province (2015ZZ012); and medical health platform plan projects of Zhejiang province (2015RCA020); Zhejiang Provincial Natural Science Foundation of China (LY16H030010). Conflict of Interest: We have no conflict of interest. Ethics Approval Statement: This study was reviewed and approved by the Medical ethics committee of Zhejiang University.

An optimization model for low carbon oriented modular product platform planning (MP3)

Consumers, industry, and government entities put more focus on the global warming. With this point in view, enterprises have started to take into account of the low carbon idea to develop products. Recently, lots of firms are using the Modular Product Platform Planning (MP3) between product generations for the rapid update of products with lesser production costs and time to market. Traditionally, MP3 mainly concerns on module sharing between product generations in modular planning, but pays no attention to the environmental concern which becomes an important design criterion due to the rising awareness of environmental protection. In this paper, an optimization model for low carbon oriented MP3 is presented. To support low carbon oriented MP3, this article proposed a probability approach to evaluate the scheme of modular planning for MP3. Meanwhile, a measurement method for low carbon performance of modular planning is provided. Then, an optimization model for low carbon oriented MP3 is formulated to determine the modular planning in pursuit of maximizing the low carbon performance of the product with controlling the implementation probability of MP3. Furthermore, an Adaptive Memetic Algorithm (AMA) is developed for solving the optimization problem. Finally, a case study is proposed to validate the effectiveness of the proposed approach.

RL-based path planning for an over-actuated floating vehicle under disturbances

This paper investigates the use of reinforcement learning for the path planning of an autonomous triangular marine platform in unknown environments under various environmental disturbances. The marine platform is over-actuated, i.e. it has more control inputs than degrees of freedom. The proposed approach uses a high-level online least-squared policy iteration scheme for value function approximation in order to estimate sub-optimal policy. The chosen action is considered as the desired input to a fast and efficient low-level velocity controller. We evaluate our approach in a simulated environment, including the dynamic model of the platform, the dynamics and limitations of the actuators, and the presence of wind, wave, and sea current disturbances. Simulation results are presented that demonstrate the performance of the proposed approach. Despite the model dynamics, the actuation dynamics and constrains, and the environmental disturbances, the presented results are promising.

Dynamic Planning for Product Platform and Module Based on Graph Theory

Aiming at the problem of platform planning and module identification in product family design, modular theory, implementation methods and objectives are studied in mass customization(MC), and a dynamic planning model is established for product platform and module. Firstly, the versatility and physical consolidation of existing variants are analyzed and expressed using directed and undirected graphs. And then a dynamic planning algorithm, in which the platform threshold and the module boundary parameters are set dynamically based on market demands, is proposed in product platform and module design. Secondly, potential parts are extracted for more variant products in product family design. Finally, the effectiveness of the proposed approach was demonstrated by the dynamic planning for parts of different humidifiers.

Applying DEMATEL to assess TRIZ’s inventive principles for resolving contradictions in the long-term care cloud system

PurposeThe purpose of this paper is to find the key innovative principles for evaluating the long-term care (LTC) cloud system by exploring contradictory and complex points in its development.Design/methodology/approachThe theory of inventive problem solving (TRIZ) and the decision-making trial and evaluation laboratory (DEMATEL) approaches are integrated to resolve complex contradictions in the system. The heuristic reasoning of TRIZ is applied to obtain innovation principles for an LTC cloud mining system. However, the importance and feasibility of these innovative principles require further assessment. In this study, DEMATEL is employed to clarify the complex relationships among the principles and evaluate their key influences.FindingsThis paper identifies six primary contradictions and derives 25 innovative principles for the resolution of these conflicts. Further analysis confirms three key innovative principles. First, the government should consider the overall planning of the cloud system platform, followed by the participation of other medical and LTC institutions. Second, the information capability of LTC institutions should be unified by recording the pathology data of care recipients to create an information exchange system. Third, LTC institutions should act in cooperation with medical institutions to provide professional medical capabilities.Originality/valueThe contributions of this paper are two-fold. First, this study provides an integrated methodology integrating the TRIZ and DEMATEL approaches to resolve LTC problems. Second, this research identifies the key innovative principles for developing an LTC cloud system in Taiwan.

Lessons Learned: Transfer of the High-Definition Circulating Tumor Cell Assay Platform to Development as a Commercialized Clinical Assay Platform.

Planning and transfer of a new technology platform developed in an academic setting to a start-up company for medical diagnostic product development may appear daunting and costly in terms of complexity, time, and resources. In this review we outline the key steps taken and lessons learned when a technology platform developed in an academic setting was transferred to a start-up company for medical diagnostic product development in the interest of elucidating development toolkits for academic groups and small start-up companies starting on the path to commercialization and regulatory approval.

A method for product platform planning based on pruning analysis and attribute matching

Product platform planning can greatly support product variant design, which is of great help to the implementation of mass customization (MC). In most of product platform planning methods, product modules and product families have been usually preplanned before products are designed, which would not make full use of the existing product resources. In this paper, we propose a method for product platform planning using the existing product data in product lifecycle management (PLM) database. The proposed method introduces two key technologies, i.e., pruning analysis and attribute matching. The pruning analysis is used to find out the sharing parts of different product families, which constitutes the basic framework of product platform; the attribute matching is used to classify product modules into different categories according to their sharing degrees, which reveals the relationships of different product modules and forms the association rules of product platform. The effectiveness of the proposed method is verified by the product data in the PLM database of a valve company. The proposed method greatly improves the reuse rate of existing product resources, providing an effective and fast way for enterprises to implement the MC strategy.

Modular product platform configuration and co-planning of assembly lines using assembly and disassembly

Formation of products platforms is carried out during the planning stage and very often separately from the planning of corresponding assembly lines. There is a dearth of literature which considers the different aspects of fully integrating platform design, product family formation, assembly line design, delayed product differentiation, and new concepts of mass customization. A Modular Product Platform Configuration model which uses assembly and disassembly for configuring product variants and Co-Planning of products platforms (MPCC) and their assembly Lines is presented. It is used to co-plan the common platform components and the associated product families simultaneously with the planning of its corresponding mixed-model assembly line. Using both assembly and disassembly to customize the product family platform in order to generate product variants is not commonly discussed in literature. It is defined as the formation of platforms for use to derive multiple products by including many components not shared by every product. The platform is then customized by assembling or disassembling components to form different product variants. The model is formulated using mixed integer mathematical programming to minimize the number of assembly stations and cycle time. Two case studies are used for verification and demonstration. They illustrated the ability of the MPCC model to integrate the planning of product platform, product families and the number of assembly stations required to assemble and disassemble components from mass-assembled product platforms to derive new product variants.

Bi-objective optimization for low-carbon product family design

Consumers, industry, and government entities are becoming increasingly concerned about the issue of global warming. With this in mind, manufacturers have begun to develop products with consideration of low-carbon. In recent years, many companies are utilizing product families to satisfy various customer needs with lower costs. However, little research has been conducted on the development of a product family that considers environmental factors. In this paper, a low-carbon product family design that integrates environmental concerns is proposed. To this end, a new method of platform planning is investigated with considerations of cost and greenhouse gas (GHG) emission of a product family simultaneously. In this research, a low-carbon product family design problem is described at first, and then a GHG emission model of product family is established. Furthermore, to support low-carbon product family design, an optimization method is applied to make a significant trade-off between cost and GHG emission to implement a feasible platform planning. Finally, the effectiveness of the proposed method is illustrated through a case study. We present a new planning method of product platform, called low-carbon product family design.We establish a bi-objective optimization model that minimizes costs and greenhouse gas emission of a product family.An optimization method is proposed to solve the bi-objective optimization problem.Our case study shows that there is a tradeoff between cost and GHG emission in product platform planning.

Technical service platform planning based on a company’s competitive advantage and future market trends: A case study of an IC foundry

Developing a unique competitive advantage while simultaneously complying with future trends has emerged as a solid strategy for securing a leading technology production position in the global marketplace. Prior studies have suggested the development of a framework for analyzing technical service platforms and valid conjoint methodologies. A reliable technical service platform planning can generate a variety of services to provide customers with many options and choices. Meanwhile, concurrent planning can enhance customer satisfaction by integrating diversified products and technologies. A multi-step approach is proposed to organize technological service platforms while incorporating corporate strengths and technological forecasting during platform development. In addition, scenario analysis is conducted as a decision support system for top managers. Therefore, enterprises can allocate resources in strategic planning so as to advance in the future. A case study of three-dimensional integrated circuit (3D-IC) technological service platform planning in the semiconductor industry demonstrates the advantages of the proposed methodology. We evaluated six alternatives to ensure the compliance of our research with market demands. Results show our method can enable enterprises to address both existing and potential customer requirements, develop more innovative services that meet different market segments, and achieve economy of scale. We show how decision makers can determine feasible alternatives while using scenario analysis to offer solutions in the future under uncertainty. Using our method, company strengths can be extended well in the future through this integration of design and forecasting.

Optimality Analysis of Sensor‐Target Geometries for Bearing‐Only Passive Localization in Three Dimensional Space

Optimality analysis of sensor to target observation geometry for bearing-only passive localization is of practical significance in engineering and military applications and this paper generalized predecessors’ researches in two-dimensions into three dimensional space. Based on the principles of Cramer-Rao lower bound (CRLB), Fisher information matrix (FIM) and the determinant of FIM derived by Cauchy-Binet formula, this paper configured the optimal observation geometry resulted from maximizing the determinant of FIM. Optimal observation geometry theorems and corresponding propositions were proved for N ≥ 2 sensors in three dimensions. One conjecture was proposed, i.e., when each range of N( N ≥ 4) sensors to the single target is identical, configuring the optimal geometry is equivalent to distributing N points uniformly on a unit sphere, which is one of the worldwide difficult problem. Studies in this paper can provide helpful reference for passive sensor deployment, route planning of detection platform and so on.

New Modular Product-Platform-Planning Approach to Design Macroscale Reconfigurable Unmanned Aerial Vehicles

The benefits of a family of macroscale reconfigurable unmanned aerial vehicles to meet distinct flight requirements are readily evident. The reconfiguration capability of an unmanned-aerial-vehicle family for different aerial tasks offers a clear cost advantage to end users over acquiring separate unmanned aerial vehicles dedicated to specific types of missions. At the same time, it allows the manufacturer the opportunity to capture distinct market segments, while saving on overhead costs, transportation costs, and after-market services. Such macroscale reconfigurability can be introduced through effective application of modular product-platform-planning concepts. This paper advances and implements the Comprehensive Product Platform Planning framework to design a family of three reconfigurable twin-boom unmanned aerial vehicles with different mission requirements. The original Comprehensive Product Platform Planning method was suitable for scale-based product-family design. In this paper, important modifications to the commonality matrix and the commonality constraint formulation in Comprehensive Product Platform Planning are performed. These advancements enable the Comprehensive Product Platform Planning to design an optimum set of distinct unmanned-aerial-vehicle modules, different groups of which could be assembled to configure twin-boom unmanned aerial vehicles that provide three different combinations of payload capacity and endurance. The six key modules that participate in the platform planning are 1) the fuselage/pod, 2) the wing, 3) the booms, 4) the vertical tails, 5) the horizontal tail, and 6) the fuel tank. The performance of each unmanned aerial vehicle is defined in terms of its range per unit fuel consumption (miles/gallon). It is found that, when the average unmanned-aerial-vehicle performance (miles/gallon) and the commonality among the unmanned-aerial-vehicle variants are simultaneously maximized, a one-third reduction in the number of unique modules is accomplished at a 66% compromise in performance. On the other hand, when simultaneously maximizing performance and minimizing costs, the best tradeoff unmanned-aerial-vehicle-family designs provide a remarkable 26% reduction in cost for a 6% compromise in performance. In this case, the cost savings are attributed to both material reduction and increased module sharing across the three unmanned-aerial-vehicle variants. It is also observed that, among the best tradeoff unmanned-aerial-vehicle families, the individual unmanned aerial vehicles are most likely to share the horizontal tail and tail booms, and are least likely to share the wing.

A Method for Green Modular Design Considering Product Platform Planning Strategy

Green modular product design plays one of the most important roles to create products with less environmental impact targeting the sustainable society. Nevertheless, traditional green modular design has the risk of losing the use of strategy of product platform planning. And this strategy is widely employed by company in order to shorten time to market and reduce costs. Aiming at the problem, a modular design method is proposed in this paper considering not only the environmental impact of product but also product platform planning strategy. The instability index of component is first presented to evaluate the change likelihood of component in future generations. Based on the instability index, the calculation method for the probability of product platform planning between product generations is illustrated. Next, a mathematical formulation for green modular design with consideration of product platform planning strategy is given. Moreover, for obtaining an optimal design scheme, a genetic algorithm is employed to conduct modular optimization. Finally, the effectiveness of the proposed method is demonstrated through a case study.