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Laparoscopic liver resection (LLR) for hepatocellular carcinoma (HCC) remains controversial, especially for tumors larger than 5 cm. We compared the short- and long-term outcomes of laparoscopic and open liver resection (OLR) for large HCC.Patients with large HCC after curative hepatectomy were enrolled. To compare the short-term outcomes, propensity score matching (PSM) and inverse probability treatment weighting (IPTW) were performed to reduce the effect of confounding factors, respectively. Subsequently, Cox-regression analyses were conducted to identify the independent risk factors associated with decreased recurrence-free survival (RFS) and poor overall survival (OS).There were 265 patients enrolled in the final analysis: 146 who underwent OLR and 119 who underwent LLR. There was no significant difference between the OLR and LLR groups according to PSM and IPTW analysis (all P 0.05). Multivariable analysis revealed that LLR was not independently associated with poorer OS (HR 1.15, 95% CI 0.80-1.67, P = 0.448) or RFS (HR 1.22, 95% CI 0.88-1.70, P = 0.238).There were no significant differences in perioperative complications or long-term prognosis between LLR and OLR for large HCC, which provides evidence for standard laparoscopic surgical practice with adequate surgeon experience and careful patient selection.

Orthopedic bone plates are most commonly used for bone fracture fixation for more than 100 years. The bone plate design had evolved over time overcoming many challenges such as insufficient strength and excessive plate–bone contact affecting the blood circulation. However, it is only made of two materials, either stainless steel (AISI 316L) or titanium (Ti–6Al–4V). There are two main limitations of metallic bone implants, namely stress shielding and the problem of malocclusion caused by the displacement of the fracture site during healing. To overcome the two problems, a new bone plate design with the incorporation of auxetic structures is proposed in this work. This study aims to use auxetic structure section in the bone plate that would decrease the stiffness of the region, thereby mitigating the stress-shielding effect and at the same time act as a deformable section to enable intra-operative bending for effective alignment while having enough bending strength and stiffness. Two different auxetic structures namely re-entrant honeycomb and missing rib structures were considered. The auxetic structure incorporated bone plates were designed, finite element analysis was done, fabricated using direct metal laser sintering technique, and tested. The results indicate that the re-entrant honeycomb structure incorporated bone plates serve as an effective bone design compared to the conventional bone plate design, in terms of stress shielding and intra-operative bending while offering similar mechanical and bending strength.

Energy-efficient manufacturing is playing an important role in addressing worldwide problems like air pollution, climate change, and energy crisis. Despite of the close relationship between process planning and scheduling, existing research efforts often consider energy efficiency-related issues by treating them separately and sequentially. This may cause various problems such as unbalanced resource allocation and infeasible production solutions, thus limiting their potential application. To advance the current state of the art in this area, this paper investigates energy-efficient integration of process planning and scheduling. Specifically, a mixed-integer linear programming model is firstly developed to formulate this problem mathematically. Subsequently, to solve more realistic large-sized problems, a heuristic-based two-stage approach is proposed. Stage 1 and Stage 2 aim at minimizing the total tardiness and reducing the total energy consumption, respectively. A realistic case study shows that the proposed two-stage approach works more efficiently and effectively than a modified genetic algorithm from existing literature. Through instructive modification of the solution space, the proposed approach can effectively reduce the total tardiness and total energy consumption; meanwhile the machining cost of individual process plans can also be kept at low level throughout the searching process. Results show that the proposed approach can allocate the machining resources in a more reasonable manner. As such, this paper may be a valuable supplement to existing efforts aiming at developing energy-efficient manufacturing techniques.

3D printing and particularly fused deposition modelling (FDM) is widely used for prototyping and fabricating low-cost customised parts. However, present fused deposition modelling 3D printers have limited nozzle condition monitoring techniques to minimize nozzle clogging errors. Nozzle clogging is one of the significant process errors in fused deposition modelling 3D printers, and it affects the quality of prototyped parts in terms of mechanical properties and geometrical accuracy. This paper proposes a dynamic model for current-based nozzle condition monitoring in fused deposition modelling, which is briefly described as follows. First, all the process forces in filament extrusion of the fused deposition modelling were identified and derived theoretically, and theoretical equations of the feed rolling forces and flow-through-nozzle forces were derived. In addition, the effect of the nozzle clogging on the current of extruding motor were identified. Second, based on the proposed dynamic model, current-based nozzle condition monitoring method was proposed. Next, sets of experiments on FDM machine using polylactic acid (PLA) material were carried out to verify the proposed theoretical model, and the results were analysed and evaluated. Findings of the present study indicate that nozzle clogging in FDM 3D printing can be monitored by sensing the current of the filament extruding motor. The proposed model can be used efficiently for monitoring nozzle clogging conditions in fused deposition modelling 3D printers as it is based on the fundamental process modelling.

Improving energy efficiency has been one of main objectives in modern manufacturing enterprises. Various approaches aiming at efficient energy management have been proposed/developed, among which minimizing energy consumption by energy-sensible production scheduling techniques has emerged as a promising one. However, reported workshop models are quite simple and unrealistic. This paper studies a more realistic workshop model called ultra-flexible job shop (uFJS). In an uFJS, the sequence among operations for a job can be changed within certain constraints. To formulate this energy-efficient scheduling problem, a mixed-integer linear programming model was developed. To deal with large-sized problems, a specially designed genetic algorithm (GA) was subsequently proposed and implemented. Numerical results showed the proposed GA worked with decent effectiveness and efficiency. Finally, several comparative studies are carried out to further demonstrate its efficacy in terms of energy efficiency improvement. The advantage of the uFJS as compared to other relative simple workshop models is also shown. By considering the flexibility in operation sequencing in each job, the uFJS effectively integrates process planning and scheduling in discrete parts manufacturing system, thus providing a much larger solution space for more energy-efficient solutions. It therefore provides an excellent platform for decision-makers when developing energy-efficient techniques and strategies

Biomimicry is a desirable quality of tissue engineering scaffolds. While most of the scaffolds reported in the literature contain a single pore size or porosity, the native biological tissues such as cartilage and skin have a layered architecture with zone-specific pore size and mechanical properties. Thus, there is a need for functionally graded scaffolds (FGS). EHD-jet 3D printing is a high-resolution process and a variety of polymer solutions can be processed into 3D porous scaffolds at ease, overcoming the limitations of other 3D printing methods (SLS, stereolithography, and FDM) in terms of resolution and limited material choice. In this paper, a novel proof of concept study on fabrication of porous polycaprolactone-based FGS by using EHD-jet 3D printing technology is presented. Organomorphic scaffolds, multiculture systems, interfacial tissue engineering, and in vitro cancer metastasis models are some of the futuristic applications of these polymeric FGS.

Mechanical systems with adaptable functions are versatile in functionalities and compact in physical structure than ordinary ones, hence are useful in many industrial and agricultural applications. One aspect of design analysis for these systems is the analysis of functional coupling degree among the adaptable functions, because this is a measurement of how compact and material-effective (thus cost-effective) the systems are. Existing work on functional coupling is mainly oriented to multiple-function systems rather than adaptable-function systems, where the former owes multiple functions without the need of adjustment or replacement of system components. The purpose of this paper is to investigate the methodologies for the evaluation of functional coupling and component importance of adaptable-function systems, so as to provide support for the development of this kind of mechanical systems. To this end, the function-component dependency is investigated first by exploiting the methods for design change propagation, whereby a change possibility matrix is proposed and calculated, and a function-component incidence matrix is developed. Based on the incidence matrix, the functional coupling degree is evaluated to measure the coupling between individual functions, and a comprehensive coupling degree is evaluated to measure the functional coupling of the entire system. These results are then used for the evaluation of component utilization and component importance. Finally, a design case of an adaptable-function juicing machine is studied to illustrate the proposed methods as well as the related concepts.

Product Lifecycle Management (PLM) is recognized as one of the most effective approaches for better, fast and cheaper product development and management. Mass customization is one of the key technologies in PLM to provide tailored product to end customers with the cost of mass production. Characterized by short production lead-time and dynamic customer requirements with low batch size and high variety, tooling product families are facing the challenge of high production cost. New technology with modular feature-based design to manufacturing collaboration to satisfy the needs of mass production with low cost in tooling industry is developed in this study. A corresponding prototype system is demonstrated to show the efficiency of the technology developed.

Bamboo shoots grow quickly through the rapid elongation of internodes. In order to verify whether DNA methylation affects bamboo shoot elongation, we compared DNA methylation levels at five developmental stages of bamboo (Phyllostachys praecox), including young bamboo shoot of 40-cm at length (S1), bamboo shoot of 2-cm at length (S2), young leaf (Y1), leaf (Y2), and aging leaf (M), by using amplified fragment length polymorphism (AFLP) based on KpnI/MseI and Acc65I/MseI platforms. The polymorphism ratio of methylated to unmethylated DNA sites in bamboo shoot (S1 and S2) was higher than that in leaf (Y1, Y2 and M). The polymorphism ratio of methylated to unmethylated DNA sites in S2 was highest (32%). Our results suggest that DNA methylation changed greatly at bamboo growing stages, especially in stage of rapid elongation of internodes.

This paper addresses the methodology development for achieving one of the important functions in automated process planning: automated determination of sequence of machining operations for prismatic parts containing various types of form features. A framework of using the case-based reasoning approach to support learning capability in operation sequencing is first proposed. The methodology to accomplish various issues in case-based operation sequencing is then discussed. In particular, the following issues are considered: 1. Representation of operation sequencing cases. 2. Indexing and retrieval of operation sequencing cases. 3. Adaptation of operation sequencing cases. Finally, the implementation issues are addressed and the learning functions of the intelligent operation sequencing system are demonstrated.

This paper introduces a case-based process planning system PROCASE which generates new process routines through learning from existing process routines. In contrast to traditional rule-based systems, the process planning knowledge of the PROCASE is represented in terms of cases instead of production rules. The planning basically comprises case retrieving and case adaptation rather than chaining applicable rules together to form process plans. The advantages are, first, the system is cheaper to build as it saves the expense of knowledge acquisition. Second, the system is able to advance its knowledge automatically through planning practice. Third, it is robust, because the reasoning is not based on pattern matching but similarity comparison. PROCASE has three modules: the retriever, the adapter and the simulator. It is supported by a feature-based representation scheme which naturally serves as the case indices for case retrieving and adaptation. The retriever uses a similarity metric to retrieve an old case which is the most similar case, among all old ones, to the new case. The adapter is then activated to adapt the process plan of the retrieved case to fit the needs for the new case. The simulator is used to verify the feasibility of the adapted plan. PROCASE is implemented on a Silicon Graphics IRIS workstation using C++ . An example is given to demonstrate how the process routine is generated by the system proposed by the authors.