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The purpose of this paper is to study the effect of the height and diameter of the dies as well as work‐piece dimensions, on stresses and strains on dies in the forging process. This helps in developing a better understanding of the effect of process parameters. As a result, the manufacturing task could be accomplished with minimal number of trials.

After determining the most influencing parameters on the forging process, the mechanical part is drawn, size of initial billet and shape of punch and die are also determined to build a finite‐element model to represent the process. Several outputs are taken as an indication for die wear and process performance. Finally, a computer numerical control (CNC) code to manufacture the selected die is generated.

It was found that when the die diameter increases, the effective stress decreases. On other hand, it was found that the work required to finish the forging process is highly affected by the dimensions of work‐piece. Therefore, it is possible to save power if work‐piece dimensions are adjusted.

This paper was meant to be a universal step or guide in developing a computer aided design/computer aided manufacturing (CAD/CAM) system to design, simulate, and manufacture molds for the forging process using a statistical method.

The purpose of this paper is to develop an innovative information hiding algorithm.

The proposed algorithm is based on image histogram statistics. Cumulative‐peak histogram regions are utilized to hide multiple bits of the secret message by performing histogram bin substitution. The embedding capacity, otherwise known as payload, and peak signal to noise ratio (PSNR), as well as security, are the main metrics used to evaluate the performance of the proposed algorithm.

According to the obtained results, the proposed algorithm shows high embedding capacity and security at comparable PSNR compared with existing hiding information techniques.

The simplicity, security, random distribution of embedding pixels, and on‐demand high capacity are the key advantages of the proposed approach.

The purpose of this paper is to develop an innovative information hiding algorithm.

The proposed algorithm is based on image histogram statistics. Cumulative‐peak histogram regions are utilized to hide multiple bits of the secret message by performing histogram bin substitution. The embedding capacity, otherwise known as payload, and peak signal to noise ratio (PSNR), as well as security, are the main metrics used to evaluate the performance of the proposed algorithm.

According to the obtained results, the proposed algorithm shows high embedding capacity and security at comparable PSNR compared with existing hiding information techniques.

The simplicity, security, random distribution of embedding pixels, and on‐demand high capacity are the key advantages of the proposed approach.