'Linear Growth Curve Model, Path Specification' NPSOL returned a non-zero status code 1

Can someone give me a hand on what I'm doing wrong, please?

Thanks,
Carlos.
___________________________
require(OpenMx)
#data
myLongitudinalData <- read.table("/home/pos/carlosdenner/Desktop/membersovertime.txt",header=TRUE)
names(myLongitudinalData)

growthCurveModel <- mxModel("Linear Growth Curve Model, Path Specification",
type="RAM",
mxData(myLongitudinalData,
type="raw"),
manifestVars=c("members1", "members2", "members3"),
latentVars=c("intercept","slope"),
# residual variances
mxPath(from=c("members1", "members2", "members3"),
arrows=2,
free=TRUE,
values = c(0.8, 0.8, 0.8),
labels=c("residual","residual","residual")
),
# latent variances and covariance
mxPath(from=c("intercept","slope"),
arrows=2,
all=TRUE,
free=TRUE,
values=c(0.8, 0.5, 0.5, 0.8),
labels=c("vari", "cov", "cov", "vars")
),
# intercept loadings
mxPath(from="intercept",
to=c("members1", "members2", "members3"),
arrows=1,
free=FALSE,
values=c(1, 1, 1)
),
# slope loadings
mxPath(from="slope",
to=c("members1", "members2", "members3"),
arrows=1,
free=FALSE,
values=c(0, 1, 2)),
# manifest means
mxPath(from="one",
to=c("members1", "members2", "members3"),
arrows=1,
free=TRUE,
values=c(0.2, 0.2, 0.2)),
# latent means
mxPath(from="one",
to=c("intercept", "slope"),
arrows=1,
free=TRUE,
values=c(0.2, 0.2),
labels=c("meani", "means")
)
) # close model
growthCurveFit <- mxRun(growthCurveModel)
_____________________________
Warning message:
In model 'Linear Growth Curve Model, Path Specification' NPSOL returned a non-zero status code 1. The final iterate satisfies the optimality conditions to the accuracy requested, but the sequence of iterates has not yet converged. NPSOL was terminated because no further improvement could be made in the merit function (Mx status GREEN).