Planning of a make-to-order production process in the printing industry

Abstract

Offset printing is a common method to produce large amounts of printed matter. We consider a real-world offset printing process that is used to imprint customer-specific designs on napkin pouches. The production equipment used gives rise to various technological constraints. The planning problem consists of allocating designs to printing-plate slots such that the given customer demand for each design is fulfilled, all technological and organizational constraints are met and the total overproduction and setup costs are minimized. We formulate this planning problem as a mixed-binary linear program, and we develop a multi-pass matchingbased savings heuristic. We report computational results for a set of problem instances devised from real-world data.

Customer Satisfaction is Part of Industrial Business Excellence in the Industrial Revolution Era 4.0

“…Suatu perusahaan yang berusaha untuk menggapai keunggulan dari pesaing adalah hal yang wajar. Perusahaan yang terintegrasi dan komprehensif dalam pengelolaan suatu industri akan mencapai keunggulan yang kompetitif dalam mempertahankan perusahaan [81], [82]. Ketika suatu perusahaan bersaing dengan perusahaan lain, maka posisi perusahaan tersebut akan mencapai titik kompetitif tertingginya dan akan menghasilkan situasi strategis [83].…”

Minimizing setups and waste when printing labels of consumer goods

“…The authors propose a nonlinear and a linear MIP formulation together with a simulated annealing-based solution heuristic. An overview of further solution approaches to and extensions of this problem is given by Baumann et al (2015) who denote this class of problems as the cover-printing problem (CPP).…”

“…Additionally, the corresponding production lot-sizes have to be determined that finally establish the printing blocks. Again, Baumann et al (2015) give an overview over this stream of the literature.…”

“…If necessary, a fractional run length is rounded up to the next higher integer number. This algorithm is a major building block to design two heuristic solution procedures for the original JSP where J can also exceed L. Baumann et al (2015) present a practical application where customer-specific designs j of napkin pouches are printed using a single machine with L = 7 slots l per offset printing plate s. Alike the JSP, the setup costs for the necessary runs of the different printing plates s have to be minimized together with the run-time-dependent costs of waste. However, in extension to the JSP, several further technical constraints have to be considered like, for example, that colors of napkins and the potential occurrence of white borders restrict the allocation of designs to slots, that slots must not remain empty and that a single design may not be allocated to several plates.…”

“…Obviously, the BBP is most closely related to the JSP. It is another extension of the JSP, but with less restrictions than Baumann et al (2015). In addition to the JSP, merely the further constraints that a slot may not remain empty and that a single item can only be produced in a single run are necessary.…”