Mixed-model production is the manufacture of similar products on a single assembly line (see Fig. 1). This assembly technique is gaining popularity in a multitude of production environments. Benefits of this include: reduced investment costs, reduced fluctuation in production due to customer demand, and smaller production facilities. For some world-class manufacturers, mixed-model production also causes increased commonality amongst products on each assembly line thus leading to reduced inventory levels and number of stock-keeping units (SKU). However, a systematic approach is lacking in most companies leading to an increase in human assembly errors due to the increase in process complexity. In response, many companies focus on automation, lean-manufacturing, and JIT parts delivery along with other forms of technology and error-proofing devices. Unfortunately, there are two problems with this approach. First, how does a company with low production volume justify the investment in automation, technology, and error-proofing devices to alleviate these types of errors? Second, employing these fixes after the problems exist leads to sub-optimal designs. With product life-cycles shrinking (Shibata, 2001) and development times shortening even more severely (see Fig. 2), companies cannot afford to fix problems after they find them in production. Companies need to address the problem in the design stage. The authors propose a multi-phase approach to managing mixed-model assembly errors in low to mid-volume assembly environments. First, companies should employ mixed-model FMEA during preliminary design to drive commonality and eliminate errors at the systems level. Second, a geometry-based comparison function based off CAD system data that can identify similar parts during detailed design is needed. An automated comparison technique alerts the designer to potential assembly problems of individual parts. Third, when parts must be physically similar, this information must be transferred to manufacturing so appropriate technologies are employed to error-proof the assembly operation.
Implementation of a standard work routine using Lean Manufacturing tools: A case Study
