J.

Electrical Systems 20-5s (2024): 253-270

1
Nandkishor Computer Aided Process Planning for
Marotrao Sawai
Sheet Metal Cutting Operations in the
2
Avinash
Mankar Manufacturing Industry
3
Amol Rasane
4
Chandrmani
Yadav
5
Ravi Shankar
Rai

Abstract: - This paper describes computer-aided process planning for sheet metal cutting operations. The two designs to production stages
that is highlighted are sheet metal processing and machining. There are four modules in this object's system. Virtual factory environments,
feature-based designs, process planning, and process-based feature mapping. Feature-based design is utilized for the conception, modeling,
and representation of the components for manufacturing applications. Whenever it involves sheet metal cutting operations in the
manufacturing sector, computer-aided process planning, is extremely important for streamlining manufacturing procedures. The provides
a general introduction to computer-aided process planning as it relates to sheet metal cutting, emphasizing its importance in boosting
productivity, saving costs, and raising product quality. The main goal of computer-aided process planning for sheet metal cutting is to
integrate computer technology, CAD/CAM systems, and sophisticated algorithms to automate and streamline the planning process. Based
on design requirements, material characteristics, and production limitations, this method enables manufacturers to produce exact and ideal
cutting plans. To create blanking and piercing holes, stamped or punched die are utilized in generative shape design; the generative
computer-aided process planning system is created in C++ and used in various case studies presented in the present work. The application
of computer-aided process planning for sheet metal cutting has several advantages, including greater output, less material waste, shortened
lead times, and improved competitiveness in the industrial sector. The potential of computer-aided process planning to revolutionize sheet
metal cutting operations, making them more efficient and cost-effective while ensuring high-quality final products is highlighted in the
present research.

Keywords: Future Base Design, Process Planning, Sheet Metal Processing, Computer-Aided Process Planning, Sheet Metal
Die

I. INTRODUCTION

The complete structure of the die assembly portion makes it challenging to automate the production process
quantitative chain. These modifications have had significant effects on geometric modelers, feature modelers,
future-based applications, etc. These changes are mostly the result of advances in computer hardware, graphics,
and information technology as a whole. There are various software tools available for each concurrent engineering
segment, such as CAD, CAC, CAPP, CAM, etc. The application of the principle of computer-aided process design
is code, which uses symbols, text, and numbers to send information about parts into a computer to create a database
of expert component information. In addition, staff members learn how a computer recognizes input to a control
system, uses a process control library to compute logical analyses of parts and parameters, and creates the
necessary files. Its primary function is to create machining processes that utilize computers to finish the production
of parts, with the parts drawings on blanks being processed into the necessary parts [1]. The production process
takes a long time and needs a process planner with experience who is familiar with the manufacturer's workshop.
The human analysis in this part is what results in the errors. The user developed a product with features that did
not remain true to the original idea. Automated process planning systems are the focus of research because they
reduce errors and save time. The relevance and significance of metal forming processes in manufacturing

1 1,4Department of Mechanical Engineering, Sandip Institute of Technology and Research Centre, Nashik, Maharashtra, India.
2Department of Mechanical Engineering, Guru Nanak Institute of Technology, Nagpur, India.
3PVG’s College of Engineering and S.S. Dhamankar Institute of Management, Dindori road, Nashik, Maharashtra, India.
5Department of Automation and Robotics Engineering, Sandip Institute of Technology and Research Centre, Nashik, Maharashtra, India.

Corresponding author: sawai.nm@gmail.com

Copyright © JES 2024 on-line : journal.esrgroups.org

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industries have been steadily growing, principally because of their material, energy, and cost-effectiveness. Recent
developments in tools, materials, and design, which significantly increase the mechanical qualities and tolerances
of the products, further emphasize this point. Additionally, metal forming has evolved in recent years to focus on
producing in a net shape to cut down on the need for additional machining processes and to lower overall
production costs. As a result, in metal forming, both process planning and tool design are crucial and challenging
jobs [2]. When producing sheet metal parts with two or more operations in one station, combination dies are used.
When two or more sheet metal operations, such as forming, drawing, extruding, embossing, etc. are combined or
with the various cutting operations, such as blanking, piercing, trimming, broaching, and parting off, combination
dies are used to produce the sheet metal parts. Die block, die gages, stripper, stripper plate, punch, punch plate,
rear plate, blank holder, die-set, and fasteners are just a few of the parts that make up a compound die [3]. CAPP
is a very efficient technology for discrete producers that have a large number of products and process stages.
Implementing GT or FT classification and coding is the initial stage. There is software that supports both GT and
CAPP that is obtainable commercially. As a result, many businesses can benefit from GT and CAPP with little
expense or risk. The competitive edge of a manufacturer increased through the effective use of these tools. The
manufacturing landscape is changing due to technological advancements, which are resulting in paperless
manufacturing environments where computer-automated process planning will play a crucial role. Cost reductions
are supporting connections between CAD and CAPP developers and making access to manufacturing data easier
in multivendor systems, which are the two causes of this effect. The process-planning component required
automation as manufacturing and design accepted computers [4].

Especially in sheet metal cutting processes, computer-aided process planning, or CAPP, is essential in
contemporary manufacturing industries. The planning and execution of sheet metal cutting processes are
streamlined and optimized through the use of sophisticated computer technologies. This introduction will give a
general overview of CAPP about sheet metal cutting processes, emphasizing its importance, advantages, and
essential elements. The manufacturing sector has made extensive use of computer-aided process planning,
particularly for sheet metal cutting operations. To increase productivity, cut costs, and guarantee constant, high-
quality production, it blends technical innovation with process optimization. The incorporation of CAPP is crucial
for maintaining competitiveness and satisfying the demands of contemporary production as the manufacturing
sector continues to change.

II. MANUFACTURING OF COMPOUND DIE ASSEMBLY

Die assembly parts must reduce scraps while yet being challenging geometrically. The punch is the most crucial
component of the die for both blanking and piercing. These strengthen the ability to determine the material
thickness while manufacturing with a sheet metal punch and die block while forgetting clearance. Display a die
block assembly as an example of Die Assembly and its part as shown in Figure 1. These particular places
manufacturing are subject to a certain mode of operation. The surface demands turning, milling, and accessibility
procedures. These factors, together with low production volumes, prevent the mechanical software industry from
creating automated process planning software. The numerical chain of production becomes disconnected as a
result of this residue.

Figure 1. Die Assembly

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FROM THE SPECIFICATION TO THE FINISHED PRODUCT:

Process planning's placement in the process is essential to understanding possible CAPP software. According to
the starting point, "Figure 2" depicts two main sequencing options. The initial step involves specifying the
intended product, followed by design (CAD), process planning (CAPP), manufacturing (CAM), prototyping, and
quality control to ensure that the product meets the supplied specification. The remanufacturing of an existing
product is the second sequence that frequently occurs in the die manufacturing industry. The parts of older die
assemblies absent of models, therefore when a part needs to be replaced we go through the digitization and model
reconstruction of the part to acquire the CAD model. Then we continue with the first sequence.

The process-planning operator's main responsibility is to gather the data needed to generate the tool trajectory.
The operator frequently separates his method into two main parts: roughing and finishing, where roughing takes
a considerable amount of time and finishing requires an intuitive approach.

III. LITERATURE REVIEW

Automation of production planning, control, and process planning processes is highly valued by modern
manufacturing companies. Due to the competitiveness of the global market, manufacturing decisions must be
produced rapidly and with desirable outcomes. It is essential to have the right expertise and information to select
the most suitable manufacturing method and its features. The role of process planning can assist in choosing the
proper procedures and their sequencing. The set of techniques and principles used to convert design information
into manufacturing process-oriented data is known as process planning [1]. A CAD modeling tool that utilizes the
Python-AutoCAD API and functions within the AutoCAD environment was conceived and developed. All of the
design parameters for the compound die are calculated using this tool. As the design inputs change, this tool
parametrizes the component and updates it. By including numerical data and taking into consideration appropriate
industry standards on the back end, a valid model is built for industrial use. A variety of compound dies are created
using an approach that partially relies on advanced parametrization techniques while fully utilizing fundamental
design principles. The time needed for human modeling is decreased by this automated design method [2].The
management can decrease the amount of time that machine was kept waiting and idle by properly implementing
process planning. The machine is operating with the least amount of waiting and idle time if the CNC lathe is
used to accomplish the turning operation rather than, a turret lathe machine. In light of the mechanical properties
of the raw material and the design of the finished product, process planning gives the process planner information
on the tools and machines that are appropriate for a process. The present research has focused on integrating
process planning and machining parameter selection to produce a part with a lower cost and higher production
rate. The Computer-Aided Process Planning function can considerably aid in the construction of generative and
variant systems with the required precision due to the use of algorithms, expert systems, and databases [3]. The
feature recognition and design by features approaches are both used in computer-aided process planning or CAPP.
The construction of a model by design features is based on the introduction of protrusion features and the
elimination of depression features, compared to a design by machining features, which are based on the removal
of depression features from a raw block [4].The features are explained by a collection of established rules and
practices that describe how the features operate throughout activities like insertion, update, and deletion.
Procedural features are defined by two categories of parameters connected by rules in addition to their solid
representation: Position in the default coordinate system is the first characteristic of a design. Then, using
coincidence restrictions with the parent feature's face, children's features are added. A local coordinate system is
used to guarantee the orientations. The hierarchical structure that is systematically built during the design is the
result of such a modeling process. Declarative feature-based modeling entails the definition of generic
characteristics with spatially related geometry [5].

These connections, or relations, exist between fundamental solids or low-level entities (points, lines, faces, and
planes). They define relationships like parallelism, coincidence, and perpendicularity. They were employed to
explain the connections between and within features' elements. These components are considered the actual parts
of the features or virtual components like planes or symmetry axes [6]. The presented work proposes that the
inadequate recognition of manufacturing features is the primary cause of CAPP Software failures. A geometric
feature is connected to a manufacturing feature through its production method. Manufacturing features (MF) are

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identified using a variety of techniques, including topological, heuristic, volumetric, and other less significant
ones. The later methods, however, frequently run into issues like multiple recognition and non-ending loops [7].
The technology-driven method known as computer-aided process planning, or CAPP, automates and optimizes
the planning of manufacturing processes by using computer systems and software. When it comes to sheet metal
cutting operations, CAPP is crucial in simplifying the process from design to production, which improves
accuracy, cost-effectiveness, and efficiency. CAPP systems use input data including component geometry,
material parameters, and production needs to automatically generate process plans for sheet metal cutting. By
reducing the need for human participation, this automation minimizes errors and expedites the planning process
[8]. CAPP optimizes the cutting process in terms of material consumption, tool selection, cutting parameters, and
sequencing by using algorithms and optimization techniques. Improved production decreased waste, and better
resource utilization result from this. By removing human error and unpredictability from manual planning
approaches, CAPP guarantees accurate and consistent process planning. This lowers the possibility of scrap or
rework and produces items of a higher caliber. Design data and process plans can be transferred directly between
CAPP and computer-aided design (CAD) and computer-aided manufacturing (CAM) systems [9]. A smooth
process from design conception to final production is made possible by this connection. Systems from CAPP are
made to adapt to modifications in product designs, materials, and manufacturing specifications. Their ability to
promptly provide updated process plans enables enterprises to effectively adapt to changing market conditions
and consumer requests. CAPP helps reduce costs in sheet metal cutting processes by enhancing machine
utilization, decreasing scrap, and optimizing material usage. It also aids in locating chances for cost- and
efficiency-cutting initiatives. Manufacturers may produce high-quality sheet metal components with faster lead
times and cheaper manufacturing costs by implementing CAPP, which offers them a competitive edge. It enables
businesses to keep one step ahead of the competition and better satisfy client requests. In the manufacturing sector,
computer-aided process planning plays a crucial role in improving the productivity, precision, and financial
viability of sheet metal cutting operations. Its integration, automation, and optimization skills boost
competitiveness, quality, and productivity. [10]

In manufacturing, particularly in sheet metal cutting operations, effective process planning is essential, and
computer-aided process planning (CAPP) is a key component in attaining this effectiveness. The best possible use
of resources, including personnel, equipment, and materials, is guaranteed by effective process planning.
Manufacturers can create cutting plans with CAPP that maximize machine use, limit material waste, and cut down
on production downtime. Production costs are directly impacted by efficient process planning [11]. CAPP assists
firms in decreasing production costs by maximizing resource consumption, minimizing scrap, and expediting the
cutting process. The market's profitability and competitiveness are increased by this cost decrease. Processes that
are well-planned provide goods that are more consistent in quality. CAPP makes sure that sequencing, tool
choices, and cutting parameters are optimized for every unique sheet metal component, producing products that
reliably meet or surpass quality standards. The amount of time needed to manufacture sheet metal components is
decreased by effective process planning. Manufacturers can create cutting plans more rapidly and precisely with
CAPP, which reduces lead times from design to production. Companies are able to react to customer requests and
market developments more quickly thanks to this agility [12]. The overall efficiency of sheet metal cutting
operations is enhanced by streamlined procedures and optimized cutting plans. By automating tedious work,
removing human error, and accelerating decision-making, CAPP systems free up operators' time to concentrate
on value-added tasks and boost throughput. Success in the dynamic manufacturing world of today requires
adaptability. Manufacturers may swiftly adjust to changes in production requirements, such as design adjustments,
new product releases, or variations in demand, thanks to efficient process planning facilitated by CAPP [13].
CAPP offers a smooth workflow from design to production by integrating with computer-aided design (CAD)
and computer-aided manufacturing (CAM) systems. Lead times are shortened, data consistency is guaranteed,
and teamwork between the design and manufacturing departments is improved because to this connection.
Manufacturing processes are guaranteed to adhere to industry standards, laws, and client requirements through
effective process planning. [14].

In the manufacturing sector, sheet metal cutting operations are essential procedures that are used to shape and size
flat metal sheets into the necessary forms. Numerous industries, including the automotive, aerospace, construction,
electronics, and appliance sectors, depend on these procedures. The manufacturing process has undergone a

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revolution due to the huge improvement in the efficiency and precision of sheet metal cutting processes brought
about by the progress of Computer-Aided Process Planning (CAPP) [15]. In the automobile industry, sheet metal
cutting procedures are widely utilized to fabricate structural parts, chassis components, and car body panels.
Cutting path optimization, material waste reduction, and improved cut precision are all made possible by CAPP
systems, which raise manufacturing efficiency and improve product quality [16]. Sheet metal cutting operations
play a crucial role in the aerospace manufacturing industry in the production of fuselage panels, wings, and engine
parts. Aerospace producers may create intricate cutting patterns with CAPP software, which guarantees excellent
dimensional accuracy and adherence to the stringent tolerances needed for aerospace applications [17]. In the
construction business, sheet metal cutting activities are essential for creating building components like structural
supports, cladding panels, and roofing sheets. CAPP systems facilitate smooth interaction with other building
processes, reduce manufacturing lead times, and optimize material consumption [[18]. Sheet metal cutting is used
in the electronics manufacturing industry to create heat sinks, brackets, and enclosures for electronic equipment.
Electronics producers may meet the strict design criteria of electronic products, increase product consistency, and
streamline the production process with CAPP technology [19]. CAPP systems assist appliance manufacturers in
automating process planning, optimizing material usage, and achieving uniformity in component fabrication.
Sheet metal cutting operations are critical to the production of appliances like refrigerators, washing machines,
and ovens where metal components are integral to the product design [20]. Operations involving the cutting of
sheet metal are essential in many manufacturing sectors since they provide the framework for the production of a
vast array of goods. These processes have been transformed by the incorporation of computer-aided process
planning, which provides producers with cutting-edge instruments to improve productivity, accuracy, and cost-
effectiveness. Sheet metal cutting operations and CAPP technologies will continue to be essential for fostering
innovation and competitiveness in the manufacturing industry as industries change [21].

For sheet metal cutting, traditional or manual process planning approaches require understanding the design
specifications and requirements given by engineers or designers. This entails analyzing CAD models or
engineering drawings to retrieve the data required for manufacturing. Choosing the right kind and thickness of
sheet metal for a given job depends on its specifications. At this point, elements including cost, corrosion
resistance, and material strength are taken into account. Organizing the component placement on the sheet metal
will reduce material waste and increase cutting effectiveness. To arrange the elements in a way that maximizes
material consumption, this may include applying templates or human computations. Deciding which cutting
technique is best for a given material type, thickness, tolerance, and production volume. Shearing, laser, plasma,
and water jet cutting are common techniques for cutting sheet metal. Selecting the right dies or cutting instruments
for the chosen cutting technique. This involves choosing the appropriate laser or blade settings depending on the
thickness and characteristics of the material. This entails taking into account elements like cutting tool access,
part geometry, and reducing setup time in between operations. Designing or choosing clamping mechanisms and
fittings to safely retain the sheet metal while cutting operations are being performed. Fixtures lower the possibility
of cutting errors by ensuring precise and consistent sheet metal positioning. To guarantee that the cut pieces fulfill
the required tolerances and quality requirements, quality control procedures should be planned. In order to confirm
surface polish and dimensional accuracy, this may entail putting inspection protocols in place both before and
after the cutting process. Recording the process plan, this includes the order of activities, cutting settings, tooling
requirements, and quality control methods. This documentation guarantees uniformity in production and acts as a
guide for operators. For each step of the planning process, these manual process planning techniques mostly rely
on the knowledge and experience of manufacturing engineers or technicians. Even though they work well, these
techniques might not be as efficient or automated as computer-aided process planning systems, and they can take
more time [ 22].

The process of manual planning can be laborious, involving the manual execution of calculations, layout planning,
and tool selection by engineers or technicians. This procedure may cause production to sluggishly supply parts to
customers, resulting in increased wait times. Manual planning procedures are more prone to human mistake, which
can result in inaccurate layout planning, tool selection, or process sequencing. These mistakes may lead to
components that don't satisfy dimensional tolerances, scrap, or rework. The utilization of material or cutting
techniques may not be fully optimized by manual planning approaches. Instead of using cutting-edge optimization
algorithms to enhance material consumption and cutting efficiency, engineers may rely on expertise or rules of

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thumb. Manual planning techniques might not be able to swiftly adjust to modifications in the specifications of
the design, the availability of materials, or the timeline for production. This may result in inefficiencies and make
it more challenging to fulfill specialized or low-volume order requests from customers. Engineers' or technicians'
knowledge and experience are crucial to manual planning. This could be a problem in settings where it is difficult
to transmit knowledge or if there is a shortage of competent workers, like in remote industrial sites or rapidly
changing workforces. It could be difficult to gradually enhance the process repeatedly using manual planning
techniques. It can be difficult and less successful to discover areas for improvement and make changes without
the use of data collecting and analysis technologies. Different planners or shifts may not plan the same way while
using manual procedures, which can cause variances in cutting quality, resource consumption, and production
efficiency. Whereas manual planning techniques have long been the norm in sheet metal cutting, they are proving
to be less appropriate in contemporary industrial settings where quicker response times, increased accuracy, and
more adaptability are required. When combined with sophisticated optimization algorithms and modeling tools,
automated process planning systems provide a number of benefits that help overcome these constraints and raise
the general effectiveness and caliber of sheet metal cutting operations [23].

The use of computer technology to aid in the planning of production processes is known as computer-aided process
planning, or CAPP. Using software tools to automate and optimize the planning of cutting processes for sheet
metal production is known as CAPP in the context of sheet metal cutting. Geometric data for sheet metal
components can be imported into CAPP systems using computer-aided design (CAD) software or manually
entered. The most suitable cutting techniques are chosen with the help of CAPP systems, taking into account the
material qualities, thickness, and design specifications. Common cutting techniques for sheet metal include
mechanical, waterjet, plasma, and laser cutting. Taking into account variables like material type, thickness, and
required cutting precision, CAPP systems assist in the selection of the proper cutting tools. The CAPP program
maximizes cutting efficiency and reduces material waste by optimizing the part arrangement on the sheet. This
involves the use of nesting algorithms to organize pieces in a way that reduces waste and maximizes material
utilization. Based on the material qualities, thickness, and chosen cutting method, CAPP systems calculate the
ideal cutting parameters, such as feed rate, power, and speed of cutting. In order to hold the sheet metal securely
during cutting operations and ensure accuracy and safety, CAPP systems may be used to help design fixtures or
clamps. To guarantee that the completed parts fulfill predetermined tolerances and quality requirements, CAPP
systems might include quality control procedures. Estimates of manufacturing costs related to the intended cutting
activities are provided by CAPP systems, which account for personnel, machine utilization, material costs, and
other pertinent variables. CAPP systems simplify the sheet metal cutting process, increase productivity, cut down
on material waste, and improve the overall quality of made components by automating and optimizing these
planning processes [24].

Computer-Aided production (CAM) and Computer-Aided Design (CAD) systems were integrated, strengthening
the bond between CAPP and the design and production process. More precise process planning could be made
possible by the direct transfer of geometric data from CAD models into CAPP systems. Optimization algorithms
were first included into CAPP systems to increase the effectiveness of process planning. Optimization methods
were used to optimize material use, cutting parameters, and tool trajectories, including neural networks, simulated
annealing, and genetic algorithms. By acquiring advanced reasoning skills, knowledge-based CAPP systems have
developed to be able to integrate expert knowledge and adjust to various industrial circumstances. These systems
could manage intricate decision-making procedures and offer process planning solutions that are more precise and
contextually aware. CAPP systems have undergone additional transformation with the introduction of Industry
4.0 technologies, such as cloud computing, big data analytics, and the Internet of Things (IoT). Process plans and
production schedules can now be dynamically adjusted and optimized by CAPP systems using real-time data from
sensors and production equipment. Process optimization and manufacturing outcome prediction are made more
accurate with the integration of digital twins and virtual simulation [25].

CAPP systems minimize human error and rely less on manual intervention by automating time-consuming
planning processes. CAPP systems can find the most effective process designs by using optimization algorithms.
This reduces cycle times, minimizes material waste, and improves resource efficiency. Modern CAPP systems
are able to adjust to shifting production needs as well as differences in designs, materials, and manufacturing
limitations, which increase production's flexibility and agility. CAPP systems may make data-driven decisions

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through integration with data analytics, which promotes manufacturing process optimization and continuous
improvement. CAPP systems make it easier to put quality control procedures into practice by guaranteeing that
manufactured parts adhere to quality standards and tolerances, which lowers the amount of scrap and rework.
Process planning is optimized, expenses are decreased, quality is improved, and overall productivity and
efficiency are increased through the use of CAPP systems in modern manufacturing [26].

When it comes to producing sheet metal components, computer-aided process planning (CAPP) technologies are
essential for streamlining operations, increasing productivity, and guaranteeing correctness. Computer-Aided
Design (CAD) software and CAPP systems are frequently connected to allow for the direct import of sheet metal
component geometric designs. The smooth transfer of design data made possible by this integration makes
automated process planning possible. In order to recognize geometric features in the imported CAD models, such
as holes, cuts, bends, and other machining features, CAPP systems use feature recognition algorithms. This aids
in the design's automatic extraction of pertinent manufacturing data. A material database with details on several
kinds of sheet metal materials, including their physical characteristics like thickness, tensile strength, and bend
allowance, is frequently included. The cutting parameters and tool choices are optimized with the use of this
information. CAPP systems suggest appropriate cutting methods and procedures based on the features and
material attributes that have been detected. This could involve shearing, waterjet cutting, plasma cutting, or laser
cutting, depending on the kind of material, thickness, and level of accuracy required. Based on the chosen cutting
method, the characteristics of the material, and the limitations of the design, CAPP systems provide optimal tool
paths for cutting operations. These tool paths prevent accidents and overcuts, maximize material utilization, and
reduce production time. CAPP systems frequently incorporate nesting optimization algorithms to maximize
material consumption and minimize waste. These algorithms take into account material grain direction and cutting
constraints to determine the most efficient way to arrange the components for cutting within the available sheet
metal stock. Their cost estimation functionality enables firms to project production costs by taking into account
several elements like labor costs, material consumption, machine runtime, and tooling charges. CAPP systems
might have simulation features that allow users to see the cutting process in virtual form before it is actually
produced. This aids in the early detection of possible problems like collisions, inefficient tool paths, or material
deformation, enabling corrections. A manufacturing system's production scheduling, inventory control, and
quality control can all be easily integrated with MES to facilitate data interchange, allowing real-time
manufacturing process monitoring and coordination. Customization options are commonly offered by CAPP
systems, enabling the process planning workflow to be tailored to unique production requirements and
preferences. Because of its adaptability, producers can customize the system to fit their own manufacturing needs
and limits. Through process planning automation, cutting parameter optimization, and improved accuracy and
efficiency in sheet metal fabrication, CAPP systems for sheet metal cutting optimize the manufacturing process
from design to production [27].

To effectively plan and optimize the cutting process, sheet metal cutting uses computer-aided process planning
(CAPP), which combines a number of different approaches and algorithms. These algorithms are used to optimize
the cutting path in order to reduce waste material and examine the geometric qualities of the sheet metal pieces.
This calls for the use of methods like polygonal approximation, convex hull algorithms, and geometric
decomposition. The optimal cutting path that reduces production costs, material waste, and cutting time is
determined using optimization algorithms. To address the optimization challenge, methods like particle swarm
optimization, simulated annealing, and genetic algorithms are frequently used. By decomposing complicated
optimization issues into smaller, more manageable subproblems, dynamic programming approaches can solve
them. Dynamic programming can be used in sheet metal cutting to determine the best order of cuts that will save
total production time or cost. For difficult optimization issues, heuristic methods are employed to swiftly uncover
near-optimal solutions. Proximate neighbor, greedy algorithms, and tabu search are a few of the techniques that
can be utilized to quickly provide workable cutting plans. AI and machine learning: CAPP systems can learn from
past cutting data and optimize the cutting process because to developments in artificial intelligence and machine
learning. Various methodologies, including reinforcement learning, supervised learning, and neural networks, can
be utilized to enhance the precision and effectiveness of the cutting programs. Cutting plans must meet all needs
and limitations of the manufacturing process, including those related to machines, tools, and materials. To this
end, constraint satisfaction algorithms are designed and implemented. Cutting plans that are feasible and satisfy

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all of the required constraints can be created by applying strategies like constraint propagation and backtracking.
CAPP systems can efficiently plan and optimize the sheet metal cutting process by utilizing these approaches and
algorithms, which will minimize material waste and boost manufacturing efficiency while also lowering
production costs [28].

The utilization of diverse software tools and technologies is part of Computer-Aided Process Planning (CAPP)
for sheet metal cutting, which aims to maximize manufacturing process preparation and execution. •CAD software
is essential to CAPP because it offers tools for developing sheet metal parts and producing intricate digital models.
The data from these models is used as input for later stages of process planning. Toolpaths and NC (Numerical
Control) codes for sheet metal cutting operations are produced using CAM software using CAD models as a basis.
It makes it possible to convert design specifications into instructions for manufacturing. Using nesting software,
sheet metal components are arranged on a bigger sheet in an optimal way to reduce waste and enhance material
efficiency. It takes into account variables including cutting limitations, material qualities, and part geometry. The
structural behavior of sheet metal components under several loading scenarios is simulated and analyzed using
FEA software. It supports process planning and design optimization by assisting in the prediction of deformations,
stresses, and failure spots. Software for simulating the cutting process simulates the cutting process and forecasts
results like tool wear, surface finish, and material removal rates. It helps in choosing the right cutting tools and
optimizing the cutting parameters. Coordinate measuring machines (CMMs) and laser scanners are examples of
optical measurement devices that are used for precise quality control and inspection of sheet metal components.
They guarantee that parts made in accordance with design standards. Order tracking, production scheduling,
inventory management, and process planning are just a few of the manufacturing operations components that ERP
software incorporates. It gives you visibility into and authority over the whole manufacturing process. An
integrated ecosystem for computer-aided process planning and execution in sheet metal cutting operations is
formed by these technologies and software applications. Manufacturers may cut costs and lead times while
optimizing their operations, increasing productivity, and improving product quality by skillfully utilizing these
technologies [29].

The Internet of Things (IoT), cloud computing, and artificial intelligence (AI) are some of the Industry 4.0
technologies that are transforming industrial process planning, including sheet metal cutting. Sheet metal cutting
machines and equipment include embedded Internet of things devices like sensors and actuators. These gadgets
gather data in real time about material qualities, machine performance, and environmental factors. Predictive
maintenance is made possible by data from IoT devices, which enables manufacturers to plan maintenance work
ahead of time, minimize downtime, and lower the chance of unplanned equipment breakdowns. Additionally, IoT
data feeds AI predictive analytics algorithms, allowing for enhanced process planning decision-making based on
real-time insights. Process planning for sheet metal cutting uses artificial intelligence (AI) technology, such as
machine learning and deep learning, to optimize cutting parameters, tool trajectories, and material utilization. In
order to find patterns, correlations, and the best cutting tactics, AI systems examine massive datasets of historical
production processes. Artificial intelligence (AI)-powered predictive analytics forecast production problems,
suggest process enhancements, and maximize scheduling for higher output and efficiency. The time and effort
needed for manual planning tasks is decreased by using AI-enabled virtual assistants and expert systems to help
engineers create efficient process plans. For managing massive volumes of data produced in process planning and
production, cloud computing infrastructure offers scalable processing and storage resources. Cloud-based
software solutions provide for smooth communication and coordination across distant teams participating in
process planning by facilitating collaboration and data sharing. Engineers may access and interact with design and
production data from any location, using any internet-connected device, with cloud-based CAD/CAM software.
High-performance computation for complicated simulations is made possible by cloud-based modeling and
simulation tools, which assist engineers in validating design choices and streamlining cutting operations. The
incorporation of these Industry 4.0 technologies into sheet metal cutting process planning improves manufacturing
operations' competitiveness, efficiency, and agility. Manufacturers may meet changing market needs and
production requirements while optimizing resource utilization, minimizing waste, and improving product quality
by utilizing real-time data, predictive analytics, and advanced optimization algorithms [30].

The development of computer-aided process planning for sheet metal cutting operations is accelerating due to
advancements in automation, strategies for optimization, and interaction with other manufacturing technologies.

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This field still has a lot of potential for boosting productivity, cutting costs, and minimizing environmental effects
in the manufacturing sector. Future research and development, however, continue with a focus on solving difficult
geometries and sustainability challenges. By automating the creation of process plans, CAPP is essential in
bridging the gap between design and manufacturing. The integration of CAPP in sheet metal cutting operations
aims to minimize costs, reduce lead times, and improve overall production efficiency. The difficulties in cutting
sheet metal, like material deformation, tool wear, and geometric complexity, are frequently discussed in literature.
In order to overcome these obstacles and maximize the cutting operation, researchers stress the importance of
precise process planning. Research comparing CAPP systems to conventional process planning techniques reveals
the benefits of the latter, such as fewer human errors, quicker planning cycles, and flexibility in response to design
modifications. A lot of research highlights how computer-aided manufacturing (CAM) and computer-aided design
(CAD) systems should be integrated for smooth data interchange. A recurring element in CAPP's sheet metal
cutting processes is the utilization of virtual prototyping and simulation tools. These solutions minimize errors
and save scrap by enabling the confirmation of suggested process strategies before to actual execution. Several
case studies highlight the effective application of CAPP in actual production settings, exhibiting increases in
output, cost savings, and quality enhancement. Applications are used in many different industries, such as
electronics, automotive, and aerospace. The literature acknowledges issues with data interoperability, standards
requirements, and integrating new technologies like AI and the Industrial Internet of Things (IIoT). The creation
of intelligent CAPP systems that can self-learn and adjust to changing industrial settings may be one of the future
research paths.

A substantial body of research targeted at enhancing the efficacy and efficiency of manufacturing processes is
reflected in the literature on computer-aided process planning for sheet metal cutting operations. Together, the
incorporation of cutting-edge technology, optimization strategies, and practical case studies advances CAPP in
the field of sheet metal cutting. Scholars persistently investigate novel approaches for ingenuity and tackle
obstacles to augment the potential of these systems inside the manufacturing sector.

RESEARCH GAP

The domain of computer-aided process planning (CAPP) in sheet metal cutting procedures has witnessed
noteworthy progressions; yet, there exist multiple study lacunae that present prospects for additional investigation
and ingenuity. Numerous CAPP systems in use today concentrate on conventional sheet metal cutting techniques.
To optimize the planning process for these methods, research is needed that blends cutting-edge technologies like
waterjet, plasma, and laser cutting into CAPP systems. Although some CAPP systems optimize for a single goal,
such maximizing productivity or lowering manufacturing costs, there isn't much study on multi-objective
optimization that takes into account variables like cost, time, energy usage, and material use all at once. To create
CAPP systems that can dynamically modify process plans in response to changes in material qualities, equipment
capabilities, and production schedules, as well as adapt to shifting production environments, research is required.
While some CAPP systems use AI and machine learning methods, more research should be done to create
intelligent systems that can anticipate future needs, learn from historical data, and offer adaptive process planning
solutions. Research on CAPP systems that take into account waste reduction, energy efficiency, and
environmental effect in addition to conventional manufacturing goals is necessary, as the focus on sustainable
manufacturing methods grows. Enhancing user acceptance and adoption in manufacturing environments can be
achieved by including interactive elements and intuitive user interfaces to improve the usability and accessibility
of CAPP systems. The integration of ergonomic elements, user input, and human factors engineering principles
into the design of CAPP systems can be the main emphasis of this research. Interoperability and data interchange
are hampered by the absence of standardization in data formats and communication protocols between CAPP
systems and industrial equipment. This gap might be filled by research initiatives aimed at creating industry
standards and procedures for the smooth integration of CAPP systems with other manufacturing systems. By
filling in these research voids, CAPP systems for sheet metal cutting operations in the manufacturing sector could
become more effective, adaptable, and long-lasting.

Role of CAPP in Sheet Metal Cutting

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Metal cutting are automated by CAPP. This covers tool selection, tool path generation, process selection, and
feature identification. By automating monotonous and formulaic operations, CAPP drastically cuts down on the
amount of time needed for process planning, enabling quicker production turnaround. Algorithms are used by
CAPP systems to automatically identify geometric features, like curves, slots, and holes, in sheet metal designs.
By increasing accuracy and decreasing the possibility of human error while recognizing crucial elements for the
cutting operation, automated feature identification helps. CAPP makes use of information about the sheet metal
component, such as material characteristics and design requirements, to choose the best cutting procedures in an
intelligent manner. CAPP assists in maximizing the choice of cutting methods, minimizing material consumption,
by taking component geometry and material limits into account. Databases with details on available cutting tool
options are frequently integrated into CAPP systems. This makes it possible to choose tools effectively based on
cost, cutting speed, and tool life. When recommending equipment that guarantee the best cutting performance, the
system takes into account the unique characteristics of the sheet metal material. When creating optimum tool
paths, CAPP considers variables such as part geometry, cutting speed, and material thickness. CAPP systems'
algorithms make sure that tool trajectories are made to stay clear of obstacles and collisions, which could harm
the cutting tools or workpiece. The manufacturing plan is guaranteed to be in line with the original design thanks
to CAPP's seamless data transfer integration with Computer-Aided Design (CAD) systems. Integrating with
Computer-Aided Manufacturing (CAM) systems guarantees a seamless shift from the planning phase to the shop
floor's real output. CAPP systems are able to swiftly modify the process plan and tool routes in response to changes
in the design. Whether cutting sheet metal for custom parts or large production, CAPP makes it possible to arrange
these processes efficiently. By streamlining the cutting process, CAPP reduces material waste and lowers costs.
CAPP ensures precise and efficient planning, which helps to maintain a constant level of quality in the completed
sheet metal goods. The time-consuming, manually performed process planning procedures associated with sheet.
The process plan, tooling information, and other pertinent details are generated in detail by CAPP system.

IV. METHODOLOGY

The planning and execution of sheet metal cutting processes can be optimized using methodology. Here is a
detailed procedure:

Data Input and Acquisition:To collect every necessary detail, such as CAD models of the sheet metal
components, data on material qualities, details on cutting tools, and production specifications.

Geometric Analysis: Examine the sheet metal components' geometries to determine the best cutting techniques,
such as laser, plasma, or water jet cutting.

Material Properties Analysis: Identify the sheet metal's material characteristics, such as thickness, hardness, and
tensile strength, as these have an impact on the cutting procedure.

Tool Selection: Select the right cutting tools based on the characteristics of the material, the geometry of the item,
and the cut quality you want. Consider into account elements like tool life and wear.

Cutting Parameters Determination:Based on the chosen cutting tool and material characteristics, define cutting
parameters including cutting speed, feed rate, and depth of cut.

Process Simulation: To visualize and enhance the cutting process, use computer simulations. Potential problems
like collisions, distortions, or overheating are easily identified through simulations.

Optimization: Use optimization techniques to reduce cost, production time, and material waste. Algorithms like
genetic algorithms, simulated annealing, or mathematical programming are used in optimization.

Quality Assurance: Ensure that the final cut components adhere to specifications by putting in place quality
control methods. Inspections, measurements, and feedback loops might be involved.

Interaction with CAD/CAM: Ensure smooth interaction with CAD and CAM systems to allow for automatic
updates if a design is modified and effective data transmission.

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Sustainability Considerations:When planning the process, take sustainability concerns into account, such as
lowering material waste and energy consumption. Make cutting paths more efficient to reduce scrap.

Documentation and Reporting: Keep thorough records of the process planning, including the choice of tools,
cutting parameters, and quality control processes. Produce reports for accountability and future use.

Deployment and Monitoring:Implement the CAPP system at the manufacturing facility and continually check
on how it is performing. Correct any problems or discrepancies right away.

Security and Data Protection:Implement security measures to safeguard sensitive CAPP system data, such as
CAD models and cutting settings.

Scalability: Determine that the CAPP system is scalable in responding to changes in production volume and
complexity.

This methodology emphasizes a holistic approach that incorporates numerous factors, from initial data collecting
through continual improvement and compliance with industry standards. It is designed for computer-aided process
planning for sheet metal cutting operations in the manufacturing industry. It seeks to enhance the cutting procedure
in terms of efficacy, cost, and quality control.

BENEFITS OF CAPP IN SHEET METAL CUTTING

The amount of time needed to plan sheet metal cutting processes is greatly decreased by CAPP's automation of
labor-intensive, typically manual process planning applications. CAPP makes it possible to quickly adjust to
design modifications, guaranteeing that the process plan is current and applicable for the duration of the production
cycle. By enhancing the precision of recognizing crucial geometric characteristics in CAPP, automated feature
detection lowers the possibility of human error. By producing standardized and consistent process plans, CAPP
systems reduce manufacturing process variances and guarantee consistent product quality. Material waste is
reduced and material utilization is raised when CAPP optimizes cutting processes while taking material limits into
account. When companies use resources efficiently, they may maximize the yield from their raw materials, which
lowers costs. CAPP systems help in minimizing tool wear, improving tool paths for effective sheet metal cutting,
and choosing the right cutting tools. Cutting parameters like feed rate and speed are optimized by CAPP to
decrease production time and increase efficiency. Process planning automation generates tool paths more quickly,
resulting in shorter lead times for sheet metal cutting operations. A more flexible and responsive manufacturing
environment is supported by CAPP, which makes it possible to respond to customer requests quickly and
effectively. By guaranteeing that the planned processes adhere to production standards and design specifications,
CAPP helps to maintain consistent quality. Because CAPP is automated, there is a lower possibility of mistakes
and flaws in the production process, which improves the overall quality of the product. Integration with CAD
lowers the possibility of inconsistencies in the manufacturing process by ensuring consistency between design
data and process plans. A smooth workflow is promoted by CAPP's connection with CAM, which guarantees
effective communication between the planning and manufacturing phases. Reductions in scrap and rework
expenses are a result of optimized material use and process planning, which lowers total costs. Cost-effectiveness
is achieved by businesses through the use of CAPP, which facilitates more effective resource management,
including labor, materials, and time. CAPP offers manufacturing operations flexibility by facilitating the effective
planning of both bespoke, one-off components and mass production. CAPP systems may adjust to a variety of
design specifications, meeting a broad range of applications for sheet metal cutting. CAPP systems produce
thorough documentation, giving analytical, quality assurance, and auditing teams a traceable record of the
planning process. Organizations can use the documentation to examine past data, pinpoint problem areas, and
apply ongoing process improvements.

FLOW CHART OF METHODOLOGY

This flowchart ensures an organized approach to production by providing a structured overview of the procedures
involved in CAPP for sheet metal cutting operations in the industrial sector. The chart of Methodology is shown
in Figure 2.

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Figure 2. Flow chart of Methodology

CAPP ASSISTANCE SOFTWARE:

This software is used to develop and prepare CAD parts for production and process planning. To analyze a CAD
model, we will first describe the conventional process planner method. The presentation of the detailed
methodology will come after that, following which we will present the CAPP functions that were produced as
well as the perspectives on our work that are represented in Figure 3.

Figure 3. CAPP Assistance

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THE OPERATOR'S STRATEGY:

The operator's approach is based on intuition and uses topologically discontinuous multiple levels of reasoning,
as shown in Figure 4.

• The operator determines the die assembly by considering the part as its entirety. Then he tries to formulate an
alternative definition.

Figure 4. Part of Die (Operator Approach).

• The operator then evaluates each face of the component individually. He considers the likely manufacturing
operation tool combination while evaluating the surface's geometry.

• The operator evaluates the component in terms of places. It selects a group of features and imagines how they
would chain together.

MANUFACTURING APPROACH:

The operator suggests extracting manufacturing features using two levers.

• EMF stands for elementary manufacturing features, which are simple manufacturing features connected to a
single face.

• High-level manufacturing features connected to a chain of faces are known as manufacturing features (MF).

• Geometrical enrichment was identified before MF extraction. Identification of the planar that has particular
production methods is the key output of the final step.

• The explanation of the sharpness and geometry of the punch edges (linear, round, and other).

These characteristics affect the selection of industrial operators.

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Figure 5. Part of Die (Manufacturing Approach)

The following step basic manufacturing characteristics Extraction investigates the information from the first
action and computer technology information connected to the face. At this point, we are studying the face and
length of the punch's manufacturing: face milling and turning, or another method, for the square or rectangular
punch and turning for the circular punch. At some borders of the suggested production directions, there is going
to be incorrect manufacturing. As a result of this stage, the face will become an elementary manufacturing feature
(EMF) that connects the face to its technological characteristics.

Manufacturing feature identification is the third and last phase. A high-level manufacturing feature will therefore
be represented by the sequence in this step; one such manufacturing feature (MF) is the face of the manufacturing
fixture, as shown in Figure 5.

DESIGN FEATURE:

The CAP approach requires the technological understanding required to automate the tool trajectories and process
planning trades. Process planners use different software than mechanical designers. The neutral geometrical
modeling format may, and most likely be used to build the CAD model.

ELEMENTARY MANUFACTURING FEATURE:

The ability of a face to be made utilizing a particular manufacturing operation mode will be investigated. The
latter will suggest a set of manufacturing directions made up of manufacturing access. The tool dimensions are
next to be taken into account. The study is based on knowledge standards that condense the expertise of planners.

The following characteristics are applicable to EMF:

• Manufacturing Accessibility: A set of manufacturing access constituted of manufacturing direction is

provided based on experimentation performed on planar, cylindrical surfaces.

• Manufacturing Mode: Using the information on manufacturing accessibility, determine whether the faces
can be manufactured. Face milling is one of the production procedures that can be used.

• Manufacturing Tools: In this step, the prospective manufacturing tools will be identified. A standard tool
is identified by its diameter and cutting length.

UTILIZED SOFTWARE:

The CAD/CAM software is presented to the user as a toolbar with a variety of options. The different assembly
components are completed in a short period. The geometrical representation of model and its parts manufacturing
details are illustrated in Figure 6 and Figure 7 respectively.

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The following methods of exploiting these software outcomes exist:

• Manufacturing View,

• Knowledge-Based Rules,

• Feature Models, and

• 3D Visualization.

Figure 6. Finalized View After Functions in Geometry.

Figure 7. Pictorial View of Part for Manufacturing Process.

PROCESS PLANNER:

The process planner benefits from the following when using this software:

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• The analysis and understanding duration of the section declined significantly using this software.

• These programs provide an effective tool for geometrical recognition, and the later module's visual output
assists in developing a production fixture.

• The latter module allows the workshop CNC machine to be chosen for use.

• Significantly minimize human error.

• The development of manufacturing strategies is facilitated by the manufacturing function.

• These programs support every step of the process, from requirements to manufacture.

V. CONCLUSIONS:

In the manufacturing industry, sheet metal cutting operations are optimized and streamlined with the help of
computer-aided process planning (CAPP). Below are some important findings about the beneficial effects and
effects of CAPP for sheet metal cutting:

• CAPP software automates a variety of process planning tasks, minimizing errors and manual work. It enables
quick and precise selection of the best cutting techniques, equipment, and settings, increasing production
efficiency.

• CAPP can assist in avoiding material waste and lowering production costs by optimizing the cutting process.
It assists in deciding on the most economical cutting methods and the best nesting configurations to maximize
material efficiency.

• CAPP systems allow for exact control of the cutting parameters, which leads to increased accuracy and
repeatability in sheet metal cutting processes. Better product quality and less rework result from this increased
precision.

• Process planning is speed up through automation through CAPP, enabling quicker responses to client demands
and shorter lead times.

• CAPP systems are flexible enough to accommodate changes in production demands or design specifications.
They make it possible for cutting operations to be quickly reconfigured reducing downtime and also assuring
responsiveness to changing manufacturing conditions.

• CAPP lessens the need for labor-intensive manual computations and judgments. Automated decision support
systems ensure consistency in planning and reduce errors.

In summary, computer-aided process planning (CAPP) greatly improves the speed, accuracy, and adaptability of
sheet metal cutting operations in the industrial sector. It is a useful tool for contemporary manufacturers trying to
stay competitive and satisfy client demands because of the way it integrates with other design and manufacturing
technologies. This paper presents a manufacturing process with significantly shorter lead times, greater quality,
and consequently more cost-effective manufacturing planning and processes.

FUTURE SCOPE

Future developments and trends in a number of areas are probably going to be included in the scope of CAPP for
sheet metal cutting operations:

• CAPP systems should be able to work more easily with other Industry 4.0 elements including big data analytics,
cyber-physical systems, and the Internet of Things (IoT). Real-time monitoring and adjustments to the production
process may be made possible by this integration.

• By using machine learning and artificial intelligence (AI) to learn from past data and optimize process planning
according to several parameters, CAPP can be improved. Planning techniques that are more effective and flexible
may result from this.

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• AI-powered generative design generates a multitude of design possibilities according to predetermined

standards. This could lead to creative and efficient designs for sheet metal cutting that take manufacturing
limitations and material usage into account.

• Future CAPP systems might have more advanced simulation features that would enable manufacturers to model
and replicate every step of the sheet metal cutting process in virtual prototype form. This can assist in locating
and resolving possible problems prior to the start of actual production.

• Cloud computing can help various manufacturing supply chain stakeholders collaborate on process planning and
data sharing. Enhancements in coordination, efficiency, and communication may result from this.

• The production process's automation can be improved by integrating robotic devices for sheet metal cutting. To
facilitate the programming and synchronization of robotic cutting systems, CAPP systems might need to change.

• The increasing demand from consumers for personalized items may require CAPP systems to modify in order
to manage the intricate planning and optimization of sheet metal cutting operations for one-of-a-kind and
customized designs.

• A greater emphasis on integrating sustainability factors into CAPP in an effort to maximize material efficiency,
cut waste, and lessen the environmental effect of sheet metal cutting operations may be seen.

• CAPP systems may need to adapt in order to ensure compliance with changing manufacturing standards and
regulations, particularly those pertaining to safety, quality, and environmental impact.

• User interface and usability improvements can increase the accessibility of CAPP systems to a wider range of
users, including those without extensive technical expertise.

Remember that the manufacturing landscape is constantly changing due to technology breakthroughs, and industry
demands and new technologies will probably have an impact on the future extent of CAPP for sheet metal cutting
operations.

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