Smartville: An Integrated Supply Chain Case Study (4)

Measuring and Assuring Partners’ Performance: Structuring-in Quality

Integrated suppliers provide their finished products to the main assembly line via conveyor. We assume this process requires suppliers to register order receipt and subsequent dispatch, as this would allow downstream work centres foreknowledge. This data would also be used to chart progress, calculate the mean processing times of the various work centres, and ultimately provide estimations of entire lead time (Taylor, 2001). The information system will also record supplier inventory, and depletion levels should trigger outward calls for replenishment, which will come directly from Tier 2 suppliers.

In their responses to the initial RFP,[1] suppliers would have provided quality assurance statements and liability pledges covering event of quality shortfall. Their involvement in the design of Smartville and their ongoing integrated role relative to MCC means that stakes in production are shared and ramifications of quality issues will directly impact upon all. Such investment by suppliers at the outset necessitates their continuing supportiveness, which means quality assurance is highly incentivized. Supplier relations are seldom of issue, due to the supplier’s ab initio involvement in the MCC manufacturing concept.

Furthermore, the information system allows MCC to observe time and place of failure or flow interrupt, and then trace that event back to a work centre and possibly even to an individual within that work centre. And, since MCC workers perform main assembly, they are in physical proximity to integrated suppliers and likely capable of detecting a percentage of sub-quality components during the fitting process.

Measurement

The following are standard performance measurements and quality checking methods (Waller, 2003; Slack et al, 2006):

  • Benchmarking
  • Metrics
  • Inspections
  • Information[2]

For quality measurement, modules could be routinely selected for testing. For example, every fifteenth rear drive module could be taken from the assembly line and subjected to test procedures matching material and capability of made modules against blueprint parameters to ascertain degree of congruence. Similarly, entire completed units (finished cars) could be ordered, created, and then assessed by a quality team for defects. Such a process would also test the overall efficiency of the system, including the information system. Proven troublesome combinations of customizable options could also be logged into the system to help identify, isolate, and improve points in the chain where operations become irregular or difficulties arise (Waters, 2002).

Another quality measurement method involves suppliers running their own check routines on a routinized/randomized basis, and forwarding their data to the MCC information system as a confirmatory/expository measure. Such check routines could be carried out in the presence of an MCC quality inspector, and/or at the unscheduled request of an MCC inspector.

Benchmarks indicating average frequency of substandard components or tool failure would be established. For example, if the probability of a press degrading increases after 100 parts processed, downtime for replacement, reconditioning, or recalibration of the press can be forecasted and the delay countered. Once benchmarks have been established, pre-emptive maintenance, device redundancy, and/or substitution could be employed to maintain productivity flow and quality (Schonberger, 1982).

Wilding’s “Three Ts” (2003) also provide a solid framework for efficiency, minimization of coordination failures, and eradication of quality issues.

Supplementary Methods of Quality Assurance

In the case of engines – which are not made on site – quality checks (random or regular) should be performed by the supplier prior to dispatch, or on arrival at line side by the supplier or an MCC worker.

Tier 1 suppliers will also push quality metrics on their suppliers (Tier 2), so that materials are delivered in a primed state. Tier 2 suppliers might be subjected to quality testing on a random, periodic, or volume basis. Single sourcing, which is mandatory in the Smartville system, should bind the interests of Tier 2 suppliers to those of Tier 1, ideally reducing disparity in objectives and further lowering risk of quality issues occurring at the inter-tier phases of the supply chain.

The centrally located “marketplace” (see Figure 1) functions as a locus of communication, a platform for idea sharing, and a station for MCC/supplier interaction and mutual observation. Inside the marketplace, standardized performance measures of each work centre are displayed. The efficiency of each participant in the chain is readily visible, encouraging positive work practice.

The performance measures displayed on the marketplace’s electronic boards include the following (Harrison and van Hoek, 2003):

  • Assembly line stopping times
  • Delivery performance
  • Product reclamation and scrap
  • Productivity targets and trends
  • Qualifications of the teams/sections along the line These measures assist MCC and their suppliers in monitoring productivity and rate of flow. Data collected can be computationally incorporated into algorithms that may contribute to kaizen practices such as improvements to the manufacturing process and quality control procedures (Slack et al, 2006).[3]

[1] RFP: “request for proposal”.

[2] JIT operations require backward information flow, but forward information flow is also useful here.

[3] Additional notes on measurement and quality assurance are provided in Appendix A.5.

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