Figure 18: Approach to define solution specifications
This obstacle demonstrates the lack of decision-making support methods to predict the benefits and trade-offs of implementing material efficiency.
II. Too little information for decision-making and prioritization (Abdul Rashid 2009, pp. 218; Biebeler 2014b, pp. 75)
Companies lack information to make informed decisions to navigate the abovementioned goal-conflicts or to prioritize material efficiency in a set of goals.
This obstacle indicates deficits in the understanding of the causation of material waste and the interdependencies within the production system between material efficiency and other cost-and market goals.
III. Measurement and target-setting (Abdul Rashid 2009, pp. 218)
Even if material efficiency is recognized as a high priority, it is difficult to measure material efficiency in a multiple material facility with a multitude of material waste forms. The potential for improvement within existing facilities may be unknown; therefore, setting an achievable, measurable goal is unlikely.
This obstacle presents the preliminary need for a material efficiency measuring method, and not only a method to improve material efficiency.
IV. Lack of time or human resources (Baron et al. 2005, pp. 62; Abdul Rashid 2009, pp. 218; Wied et al. 2009, pp. 47; Biebeler 2014b, pp. 75) Managers, particularly in small or mid-size companies, lack the time to anchor material efficiency initiatives or make informed decisions about material efficiency. Similarly, companies may lack qualified staff to handle the planning and operationalization of material efficiency strategies (Baron et al.
2005, pp. 62).
This obstacle underlines the need for a low-effort method with a well-defined data collection procedure.
V. Complacent attitudes for companies within industry norm (Baron et al. 2005, pp. 62)
Baron’s interviews with industry leaders revealed an attitude of complacency with regard to material efficiency, as long as the material cost percentage is within the normal range for their respective branch (Baron et al. 2005, pp. 62).
Logic serves that costs will be cut where companies suspect they are performing poorly against the competition, not where they are in the normal cost range. Since few companies have focused on cutting material costs, there is little pressure to improve.
Though a method for increasing material efficiency cannot remedy this attitude alone, a method that demonstrates the material-saving effects of small changes in operative decision-making may catch the interest of companies eager to profit from low-hanging fruits.
VI. Technology not available/ Machinery industry has cut R&D (Baron et al. 2005, pp. 62; Wied et al. 2009, pp. 47; Biebeler 2014b, pp. 75)
Some material waste forms are fixed for a process technology. Depending on the application, no process alternatives may exist, which may be attributed to the constraints of the product design (Abdul Rashid 2009, pp. 218). The unwillingness of machine builders to invest in R&D may also contribute to the lack of technical alternatives (Baron et al. 2005, pp. 62).
If a technology-induced material waste form represents the majority of the material waste costs for a manufacturing system, companies may become frustrated and perceive material efficiency as an unachievable goal, overlooking influencable material waste forms, which are smaller in mass.
Therefore it is important for the system to distinguish between the material waste that in attributed to the utilized technologies, and the portion that can be controlled though better operative decision-making.
VII. High investment/Long amortization period (Wied et al. 2009, pp. 47;
Biebeler 2014a, pp. 75)
If alternative process technology is available, the required capital investment
depending on the achievable material savings, its amortization period may be too long to be financially viable.
Analogous to the previous obstacle, companies with technology-attributed material waste, where a solution is available but not financially viable, may discount material efficiency as unachievable and ignore smaller, yet more easily influencable material waste forms. The method must demonstrate which share of material waste can be prevented within the factory system.
VIII. Too high quality standards (Baron et al. 2005, pp. 62)
Manufacturers have set unattainably tight specifications for e.g. part surface quality, leading to high defect rates (Baron et al. 2005).
This serves as an example of the disparity between customer requirements and readiness of process technologies. While the developed method cannot redefine market demand or the specifications of products to meet that demand, the method should present which role quality defects play in the overall material efficiency of the factory.
IX. Customer-driven product variety product customization / high product variety / short product lifecycles (Baron et al. 2005, pp. 62; Abdul Rashid 2009, pp. 218)
Manufacturers have been under pressure for the last 50 years to meet increasingly diversified customer demand, at the cost of any economies of scale and more specifically material efficiency. This push from the market has led to more engineer-to-order (individual) production, making it virtually impossible to fully utilize stock sheets in cutting operations, and causing frequent machine setups and frequent periods of unstable, ramp-up production. Shorter product lifecycles, another trend, inhibit manufacturers from benefitting from process learning curves.
X. Organizational barriers (Abdul Rashid 2009, pp. 218; Wied et al. 2009, pp. 47; Biebeler 2014b, pp. 75)
Most companies lack a centralized function to execute and monitor a variety of material saving measures. Material efficiency may be championed either by quality management (defects), manufacturing (trim loss), warehouse management (for transport losses and inventory shrinkage), maintenance (lubricants), or an environmental management function, resulting in uncoordinated and potentially conflicting activities (Shahbazi 2015, pp. 73).
For that reason, the method must be easy to learn for both users with and without technical backgrounds. A straightforward procedure for practical application should specify how the required data is to be collected and prepared.
After reviewing the obstacles addressed in industry surveys, requirements from a business perspective were defined, keeping the scope of this work in mind (see 1.3 and 1.4).
Obstacles I and II address the need for clarity regarding the benefits of material efficiency activities and the trade-offs in cost and market goals. Obstacle III highlights the need for a target-setting procedure. Obstacles VI and VII confirm the importance of investigating the potential to increase material efficiency within the constraints of the existing system, especially in cases where technologies are not yet available or not viable for industrial application.
In order to set reasonable improvement goals, the method should be able to estimate the potential material savings within the constraints of the current manufacturing system. The method should be able to model accumulated material waste while monitoring other system performance metrics. Through scenario building, the effects of material efficiency activities on each material waste form and system performance are demonstrated and potentially conflicting goals are identified. Therefore the following two requirements are defined:
R2: Recommend material efficiency activities considering goal-conflicts Obstacles IV, V, and X describe the need for a low-effort solution that enables the user to collect the relevant data quickly from relevant departments, and provides results after a short computation time. The method should be easy to learn, accessible to managers at low cost, and provide decision support within an acceptable data processing time. Therefore the following solution requirement is defined:
R3: Fast and low-effort
Obstacle IX describes the need for an easily repeatable method for different scenarios for a system with a high-variety, frequently updated product spectrum. This indicates that the required data must be easily collected, even for new product variants that are not yet in series production. To address this need, the following requirement is defined:
R4: Adaptable to fast-changing product spectrums
Figure 19 depicts the clustering of the obstacles and the derivation of four solution requirements.
Figure 19: Formulation of business requirements