Classification of research and applications of the computer aided process planning in manufacturing systems

The Computer Aided Process Planning (CAPP) systems are recently developed in manufacturing engineering to provide links between Computer Aided Design (CAD) and Computer Aided Manufacturing (CAM) systems. The CAPP systems are developed by considering the different issues of computer applications in production engineering. Optimization techniques can be applied to the CAPP to increase efficiency in part production processes. The energy consumption of part production process can be analyzed and optimized using the CAPP systems in order to increase added value in the part manufacturing process. Also, artificial neural networks as well as cloud manufacturing systems can be applied to the CAPP systems to share advantages of the different CAPP systems in different industry applications. Flexible process planning systems are developed using dynamic CAPP in order to cope with product varieties in process of part production. To develop potential energy saving strategies during product design and process planning stages, the advanced CAPP systems can be used. In this paper, a review of Computer Process Planning systems (CAPP) is presented and future research works are also suggested. It has been observed that the research filed can be moved forward by reviewing and analyzing recent achievements in the published papers.

Production–operation management. The chosen aspects

The aim of the e-book is to present the theoretical, cognitive and practical aspects of the essence and complexity of operational management in a production company. The presented modern production methods together with the challenges and problems of contemporary enterprises should better help to understand the issues of sustainable development, with particular emphasis on waste. The book consists of six chapters devoted to relevant and topic issues relating to the core business of an industrial enterprise. Chapter 1 The nature of the industrial enterprise is an introduction to further considerations and deals with the essence of the basic aspects of the company. Both popular and less known definitions of an enterprise, its features, functions and principles of operation are presented. An important part of the chapter is the presentation and formulation of strategic, tactical and operational goals. Moreover, the division of enterprises is presented with the use of various criteria and the features of the industrial market, which make it distinct. Chapter 2 The operational management evolution and its role in the industrial enterprise discusses the evolution and concept of production and operational management. The management levels were also presented, indicating their most important functions. An integral part of the chapter is the essence of the production system, viewed through the prism of the five elements. Chapter 3 Functions and role in operations management presents the issues concerning the organization of production processes, production capacity and inventory management. This part also presents considerations on cooperation and collaboration between enterprises in the process of creating value. Chapter 4 Traditional methods used in operational activities focuses on methods such as benchmarking, outsourcing, core competences, JIT, MPR I and MRP II, as well as TQM and kaizen. Knowledge of these methods should contribute to understanding the activities of modern enterprises, the way of company functioning, the realization of production activities, as well as aspects related to building a competitive position. Chapter 5 Modern methods used in production-operations management discusses the less common and less frequently used production methods, based on a modern and innovative approach. In particular, it was focused on: Shop Floor Control and cooperative manufacturing, environment-conscious manufacturing (ECM) and life-cycle assessment ( LCA), waste management and recycling, Electronic Data Interchange (EDI), virtual enterprise, World Class Manufacturing (WCM), Quality Function Deployment (QFD) and House of Quality (HOQ), theory of constraints (TOC), Drum Buffer Rope (DBR), group technology (GT) and cellular manufacturing (CM), Demand Chain Management and competitive intelligence (CI). In the last section discusses: the role of sustainable statistical process control and Computer-Aided Process Planning in context formatting of information management. Chapter 6 Problems of sustainable development and challenges related to production and operations management describes the problem and challenges related to production and operations activities. In particular, attention was paid to the threats related to changes in global warming, the growing scale of waste, or the processes of globalization. It was pointed out that the emerging problem may be both a threat and a chance for the development of enterprises. An integral part of the chapter are also considerations on technical progress, innovation and the importance of human capital in operational activities.

A Genetic Crow Search Algorithm for Optimization of Operation Sequencing in Process Planning

Computer-aided process planning represents the main link between computer-aided design and computer-aided manufacturing. One of the crucial tasks in computer-aided process planning is an operation sequencing problem. In order to find the optimal process plan, operation sequencing problem is formulated as an NP hard combinatorial problem. To solve this problem, a novel genetic crow search approach (GCSA) is proposed in this paper. The traditional CSA is improved by employing genetic strategies such as tournament selection, three-string crossover, shift and resource mutation. Moreover, adaptive crossover and mutation probability coefficients were introduced to improve local and global search abilities of the GCSA. Operation precedence graph is adopted to represent precedence relationships among features and vector representation is used to manipulate the data in the Matlab environment. A new nearest mechanism strategy is added to ensure that elements of machines, tools and tool approach direction (TAD) vectors are integer values. Repair strategy to handle precedence constraints is adopted after initialization and shift mutation steps. Minimization of total production cost is used as the optimization criterion to evaluate process plans. To verify the performance of the GCSA, two case studies with different dimensions are carried out and comparisons with traditional and some modern algorithms from the literature are discussed. The results show that the GCSA performs well for operation sequencing problem in computer-aided process planning.

Design of Integrated Computer Aided Process Planning and Bill of Material in Industry 4.0 Environment

Computer aided process planning (CAPP) has been widely used as an application that is able to plan the process in manufacturing with computer technology supporting. In its implementation, the process planning stage often requires complete data/information input regarding manufacturing products that will go through several process and operations. In the assembly process for example, before planning what process and operations will be carried out on a parts, the assembler must know the specifications and product structure, so that the assembly planning process becomes directed. The purpose of this research is to perform the design of integrated computer aided process planning and bill of material as the product structure that can support the planning process activities in manufacturing area and also suitable with industry 4.0 environment whereas the rapid changes in the information and communication technologies have broken the boundaries between virtual reality and the real world.

Novel Integration of CAPP in a G-Code Generation Module Using Macro Programming for CNC Application

In the modern manufacturing industry, the role of computer-aided process planning (CAPP) is becoming increasingly crucial. Through the application of new technologies, experience, and intelligence, CAPP is contributing to the automation of manufacturing processes. In this article, the integration of a proposed CAPP system that is named as BKCAPP and G-code generation module provides a completed CAD–CAPP–CNC system that does not involve any manual processing in the CAM modules. The BKCAPP system is capable of automatically performing machining feature and operation recognition processes from design features in three-dimensional (3D) solid models, incorporating technical requirements such as the surface roughness, geometric dimensions, and tolerance in order to provide process planning for machining processes, including information on the machine tools, cutting tools, machining conditions, and operation sequences. G-code programs based on macro programming are automatically generated by the G-code generation module on the basis of the basic information for the machining features, such as the contour shape, basic dimensions, and cutting information obtained from BKCAPP. The G-code generation module can be applied to standard machining features, such as faces, pockets, bosses, slots, holes, and contours. This novel integration approach produces a practical CAPP method enabling end users to generate operation consequences and G-code files and to customize specific cutting tools and machine tool data. In this paper, a machining part consisting of basic machining features was used in order to describe the method and verify its implementation.

Adaptive data-driven modular control approach to computer aided process planning for manufacturing spiral bevel and hypoid gears

Machine setting modification has been an increasingly important access to the accurate flank manufacturing geometric accuracy control for spiral bevel and hypoid gears. More recently, machine setting driven integration of the theoretical design and the actual gear manufacturing is gaining more and more attention. In this paper, the traditional machine setting modification is extended to the case when higher-order component of the prescribed ease-off flank topography is investigated in form of high-order polynomial expression. Moreover, the actual gear manufacturing and general measurement are integrated into an adaptive data-driven high-order machine setting modification. In particular, this modification method is used to perform adaptive modular control for computer aided process planning (CAPP). Here, a data-driven operation and optimization is developed for adaptive high-order modification. It mainly includes: (i) Polynomial fitting and its optimization by using overall interpolation based on energy method, (ii) Data-driven ease-off flank parametrization based on the fastest descent Newton iteration method, (iii) adaptive control strategy by considering the sensitivity analysis, and (iv) Levenberg-Marquardt (L-M) based approximation for high-order machine setting modification. Given numerical test can verify the proposed method.

Evolution of Computer-Aided Process Planning for Hybrid Additive/Subtractive Process

The hybrid process, which integrates two or more different processes such as additive manufacturing and subtractive manufacturing, has gained appreciable considerations in recent years. This process exploits the benefits of individual processes while overcoming their limitations. Lately, the combination of additive, subtractive, and inspection methods is a valuable conglomeration, considering its potential to produce complicated components precisely. Certainly, computer-aided process plan (CAPP) provides a crucial link among different processes and is essential to avail the benefits of hybridization. However, a valuable process plan can only be achieved through the optimization of its different elements. Therefore, the objective of this work is the accomplishment of an optimized CAPP to fabricate parts in the shortest time employing the hybrid additive, subtractive, and inspection processes. In this work, mathematical models have been developed to optimize part orientation as well as minimize additive and subtractive times. Additionally, the genetic algorithm has been employed to obtain the best path with minimum inspection time. The feasibility and capability of the proposed approach as well as the optimized CAPP for the hybrid process have been demonstrated through a case study.