The current business environment requires every organization or company to achieve optimal performance and maintain it. Innovation capability and open innovation practices play a critical role in improving organizational performance. However, their role in improving Small and Medium Enterprises (SMEs)’s performance, especially during the COVID-19 pandemic, still needs to be identified further. Thus, this study conducts empirical research elaborating intrinsic factors of innovation capability, as well as the influence of open innovation on organizational efforts, i.e., how SMEs achieve optimal performance during the COVID-19 pandemic. In this research model, 206 respondents were gathered and given a reearch questionnaire. The respondents are the owner of batik SMEs located in several regions in Indonesia. PLS-SEM is used to test the data, and the result of this study shows that all hypotheses developed in this study are accepted, i.e., SMEs’ innovation capability and open innovation practices significantly influence financial and operational performance. The results show that in batik SMEs, the ability to innovate and open innovation, especially open entry innovation, can facilitate greater organizational performance. Therefore, batik SMEs woud benefit from initiatives and opportunities that improve their abilities in open innovation.
The need to integrate the design and machining stages has become an important issue since the introduction of the Computer-Integrated Manufacturing (CIM) concept. The development of the Computer-Aided Process Planning (CAPP) system has been recognized to have made a significant contribution toward fulfilling the requirement for an integrated planning system. This paper reviews the development of the CAPP system, particularly for the metal removal process. Previous reviews on CAPP are gathered and discussed to show the evolution stage of CAPP in general. Main research topics that contribute to the CAPP system development are shown. Six elements of the CAPP system are identified as the most important tasks in generating a process plan. These elements consist of: (1) model convention, (2) manufacturing operation selection, (3) manufacturing resource selection, (4) cutting condition selection, (5) tool path selection, and (6) setup selection. Six elements for the development of CAPP that contribute to process planning for metal removal process are discussed. The evolution stages of each element easily show the involvement of several tools in order to support the corresponding element. For further guidance, the methods of comprehending the involvement of manufacturing information in CAPP are discussed. Knowledge structuring and logic reasoning are the main organizational steps that can be used to describe the CAPP data architecture of manufacturing information. Further, the examples of full-scale CAPP in actualizing machining process planning are presented. Finally, key technologies for future development of CAPP are discussed.
A new methodology to automate machining operation planning is proposed. A new machining operation plan is reconfigured from past case data or past machining operation data stored in the database. Machining information, e.g. cutting tool, cutting conditions, tool path pattern, is associated with a machining feature. A machining feature is recognized from the 3D CAD model of the finished shape. Sets of machining information are stored as the past case data with their 3D CAD models. In order to generate a new machining operation plan of a new product, machining features are recognized based on topological relationship of the 3D CAD model first. Then, each of machining feature is compared with machining features contained in 3D CAD models stored as the past case data quantitatively in terms of shape, size and material. Finally, the most similar machining feature is selected as the reference one. The machining information associated with the reference machining feature can be applied for each machining feature recognized in the new product. Finally, the NC program to perform a new machining operation is generated automatically. The usability and effectiveness of this proposed system to save time and effort of human operator was verified through a case study.
A unique machining knowledge has led to several different perspectives between planners and operators as regards in designing a machining process plan. All precedents have shown the need to maintain a suitable machining process plan. Commercial Computer-Aided Design (CAD) and Computer-Aided Manufacturing (CAM) systems have facilitated the manipulation of 3D models to generate a machining process plan. The open Advanced Programming Interfaces (APIs) are also helpful in tailoring decision support systems to determine process plans. This study proposes an emergent system to generate flexible machining process plans. The proposed system considers the integration between design and manufacturing perspective to produce relevant machining process plan. The generation of process plans begins by considering the total removal volume of the raw material, estimating the removal features, thus analyzing and ordering several candidates of machining process plans. The total machining time and number of setups from each machining process plan candidate is analyzed and evaluated. Eventually, the proposed system is tested using several prismatic 3D models of a workpiece to show the outcomes.
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